• Watch global leaders discuss the future of industrial intelligence: Register now 
• Get the latest insights on industrial transformation: Get the e-book 
• New: The Procurement Agent in Dynamics 365 Supply Chain Management 

Three global industrial leaders—ABB, Krones, and TK Elevator (TKE)—are redefining their industries by using advanced AI and trusted cloud platforms to become Frontier industrial organizations. With Microsoft, they’re turning data, processes, and context into intelligence that drives efficiency, agility, and innovation. Every Frontier organization gets two fundamental things right: intelligence and trust. They amplify what’s unique in their people and operations with AI that is governed securely on their own terms. Trust isn’t added at the end; it ensures intelligence is used responsibly and outcomes happen as intended. Hannover Messe 2026 is where these transformations take center stage, showing how Frontier organizations are shaping the next era of manufacturing.  

• ABB—AI as a Real-Time Industrial Co-Pilot: ABB, a global technology leader in electrification and automation, will showcase its cloud-powered Genix Industrial AI platform running on Microsoft Azure. Genix acts as a real-time industrial co-pilot on the factory floor by analyzing streaming data from equipment and sensors and delivering actionable insights and recommendations to operators and managers in real-time. At Hannover, ABB’s demos illustrate how Genix enables closed-loop, AI-driven optimization of production processes on the fly, for example, by automatically adjusting parameters to improve energy efficiency, asset performance, and reduce unplanned downtime. Designed with a modular, scalable architecture, Genix integrates seamlessly with existing industrial systems, eliminating the need for large‑scale platform replacements and enabling rapid time to value. With the integration of generative and agentic AI, the platform not only provides insights, but also automates actions, while keeping humans “in the loop” for all critical decisions to ensure safety and operational decisions. This approach demonstrates how ABB is moving toward autonomous, self-optimizing operations without sacrificing human oversight, a hallmark of a Frontier organization. 

• Krones—From Bottling Machines to “Bottle-as-a-Service”: Krones, one of the world’s largest bottling equipment manufacturers, is using AI to reinvent its business model and engineering process. With Microsoft’s help and the ecosystem of trusted partners Ansys (part of Synopsys), NVIDIA, Softserve, and CADFEM, Krones integrated advanced AI-based fluid simulation into its digital twin of a filling line, packaged with a multi-agent experience, for their engineers to create these complex simulations with natural language queries. This innovation has slashed simulation times from four hours to under five minutes (a 95% reduction), allowing engineers to optimize machine parameters virtually and dramatically shorten commissioning time. The payoff is huge—Krones can now rapidly tailor designs for each customer and ensure optimal throughput. At Hannover Messe 2026, Krones will demonstrate how these AI-powered digital twins let them forecast and fine-tune production faster and more flexibly than ever, turning a traditional machinery business into a Frontier digital services company. 

• TK Elevator—Digital-Native Elevators and Agentic AI: TK Elevator (TKE) is revolutionizing mobility for 1.5 billion users by combining digital-native products, secure cloud and data platforms, and agentic AI, all in partnership with Microsoft. At Hannover Messe, TKE highlights its EOX and HELIX elevators, which are eco-efficient, AI-ready, and IoT-enabled as part of the MAX on Azure platform. Azure Databricks supports their unified analytics, ensuring data governance and enabling scalable AI workflows. TKE’s specialized AI agents, alongside the Digital Operations Center, streamline service by assembling contextual briefings before technician visits and capturing insights afterward, turning technician knowledge into organization-wide intelligence. 

These three examples are among many Microsoft customers and partners joining us at Hannover Messe 2026, with live demos showing how industrial intelligence turns data into faster decisions, safer operations, and more resilient manufacturing. 

Industrial Intelligence Unlocked, Microsoft’s overarching theme for Hannover Messe 2026, reflects the belief that manufacturing’s next era will be driven by human ingenuity and AI—grounded in trust. Microsoft provides a unified intelligence layer for the tools your employees use; Work IQ understands how people collaborate and decide. Fabric IQ delivers real-time visibility across assets, production, and supply chains. And Foundry IQ combines institutional knowledge like procedures, standards, and history with AI. Together, they help manufacturers connect teams, processes, and technology across the value chain. 

1. Redefine product lifecycle intelligence

This neighborhood focuses on uniting engineering and operations through data-driven intelligence, so manufacturers can design and deliver better products in less time. Here you’ll see how Microsoft is helping companies create a closed-loop product lifecycle —connecting every stage from design and simulation to production feedback. For example, Microsoft and NVIDIA are collaborating to power the next generation of physical AI by integrating NVIDIA Omniverse libraries with Microsoft Fabric.  

By blending real-time data, AI, and virtual simulation in one environment, companies can iterate designs faster with greater confidence. Imagine optimizing a new machine design virtually (with accurate physics and live data) before anything is built—reducing costly physical prototypes and accelerating time-to-market.  

In short, the product lifecycle intelligence zone shows how integrating data + simulation + AI yields smarter product decisions and faster innovation. 

Microsoft ecosystem partners showcased in this area: Aras, Brembo Solutions, Celebal Technology, NVIDIA, PTC, Tata Consultancy Services (TCS) 

2. Run AI-powered factories 

In our AI-Powered Factories area, we demonstrate how to coordinate machines, materials, and people with AI, turning traditional facilities into adaptive, self-optimizing operations. Microsoft supports the ability to scale these operations with a unified intelligence layer powering AI insights and a consistent framework for managing agents, models, data and infrastructure with the adaptive cloud approach. 

A highlight here is Microsoft’s approach to industrial edge AI. Foundry Local on Azure Local enables manufacturers to deploy and run AI models, including those from the Foundry model catalog —directly on factory equipment or on-premises servers for scenarios that require ultra-low latency, data locality, or offline operation. This capability supports high-speed vision inference for quality inspection, anomaly detection, and predictive maintenance, all in real time without relying on constant cloud connectivity. Manufacturers can choose curated open-source models from the managed catalog or deploy custom OCI/Docker models on CPU or GPU systems. 

Discover how the latest Azure IoT Operations release simplifies OT data management—now with no-code pipelines, seamless device control from cloud to edge, and direct support for third-party MQTT brokers and Litmus Edge gateways. In addition, upgrades to Azure IoT Hub and firmware analysis, enabled by Azure Arc make it easier for industrial organizations to securely manage and update large device fleets with unified Azure security and certificate management via Azure Device Registry integration. Learn more about how Microsoft and our partners are providing the foundation to initiate and scale industrial AI projects in our two-part blog series: Making Physical AI Practical for Real-World Industrial Operations: Part 1 and Part 2. 

Together, these capabilities come to life in Microsoft’s Factory of the Future demo—showing how adaptive cloud, edge intelligence, and Physical AI work together in a real manufacturing environment. The Factory of the Future demo shows how Physical AI comes to life when design, simulation, and execution are connected into a single, adaptive manufacturing system. In collaboration with Hexagon, Siemens, NVIDIA, KUKA, and others, Microsoft demonstrates an end-to-end scenario where AI-assisted product design is validated in simulation and then executed in a live manufacturing cell. Real-time telemetry flows from the factory floor through Azure IoT Operations at the edge and into Microsoft Fabric, where AI agents’ reason across operational signals to proactively detect issues and support action.  

Microsoft ecosystem partners showcased in this area: Accenture Avanade, AVEVA, Hexagon, Kuka, NVIDIA, Schneider Electric, Siemens, Sight Machine, Rockwell Automation 

3. Build trust across human–agentic teams

As AI agents move from pilots to daily operations, trust becomes the factor that separates insight from impact. In manufacturing environments, AI only delivers value when people are confident enough to act on its recommendations. For frontline workers, trust means clarity at the moment of action. AI agents assemble contextual briefings that bring together equipment performance, recent alerts, maintenance history, and safety guidance, so technicians arrive informed and prepared. Recommendations are visible, explainable, and designed to support human judgment, not replace it. For engineers, planners, and operational leaders, trust means confidence at scale. As AI agents operate across factories, service networks, and supply chains, organizations need visibility into how decisions are made, what data is used, and when human approval is required. Governance, auditability, and clear accountability ensure AI actions align with operational priorities and policies. 

Manufacturers can now use Researcher in Microsoft 365 Copilot in Dynamics 365 Field Service. Powered by WorkIQ, teams can bring together signals from work orders, service history, parts availability, and Microsoft 365 context to investigate issues faster and take informed action, improving first-time fix rates, reducing downtime, and maintaining governance. 

This human–agent operating model reflects Microsoft’s approach to industrial AI. Intelligence proposes that. People decide. Trust is built into the system so AI can move beyond insights and support real operational action across the enterprise. 

Microsoft ecosystem partners showcased in this area: Bosch Connected Industry, Cognite, Kongsberg Digital, SymphonyAI. 

4. Orchestrate supply chains with AI agents

The fourth booth zone looks beyond the factory floor to the end-to-end value chain, where volatility, constraints, and customer expectations converge. Here we show how manufacturers can go from reactive coordination to agentic supply chains. From networks of suppliers, plants, and logistics partners connected by AI agents that continuously scan for change, reason across data, and support action in real time. These systems go beyond visibility, helping leaders anticipate disruption and respond with speed and confidence. 

Procurement is often first to feel disruption, where speed, context, and control matter most. The Procurement Agent in Dynamics 365 Supply Chain Management helps teams handle supplier communications and exceptions, assess downstream impact, and keep people in review.  

AI-assisted agents reduce manual effort while keeping our people in control…strengthening collaboration and improving outcomes.

—Andre Scheepers, Chief Digital Officer, Farmlands Cooperative

AI agents help organizations move from delayed reaction to proactive control. By detecting demand volatility, supplier risk, or inventory imbalances earlier, teams can evaluate tradeoffs, align cross functional responses, and act before issues escalate into revenue loss or excess cost. Embedding these insights directly into operational workflows shortens decision cycles, reduces manual intervention, and improves outcomes such as on-time, in full delivery, inventory turns, and working capital efficiency. 

This approach reflects a shift in how supply chains create value. AI strengthens human decision‑making by improving speed, consistency, and coordination across the value chain. Thus, enabling supply chains to operate with greater predictability, control, and customer confidence, even in volatile environments. 

Microsoft ecosystem partners showcased in this area: Resilinc, Fractal, C3.ai 

Join us—onsite or online—Live from Hannover Messe 2026

Microsoft is hosting a series of executive conversations at our Hannover Messe booth, where top manufacturing leaders will share how they’re navigating the journey to an AI-powered, data-driven future. The conversations feature voices from companies like Siemens, Accenture, Schneider Electric, TK Elevator, Bosch Connected Industries, and more. Register here to watch for strategic insights into how global manufacturers are using AI to connect data, systems, and workflows.  

We’re also thrilled to invite everyone to the Hannover Messe Center Stage keynote by Deb Cupp, Microsoft’s President and Chief Revenue Officer. Deb will present “Return on Intelligence: The Next Frontier of Manufacturing,” exploring how organizations can move beyond incremental efficiency gains to achieve transformative growth with AI. This keynote takes place on April 20 at 2:00 PM CET (opening Monday) on the main stage.  

For a quick recap of Microsoft’s Hannover Messe 2025 presence and to see what to expect in 2026, check out the 2025 recap video: 

Learn more about how Microsoft helps Frontier organizations prioritize efficiency, agility, and innovation 

• The Industrial Frontier: Four ways manufacturers can unlock intelligence across the value chain. Get the e-book

The post Industrial intelligence unlocked: Microsoft at Hannover Messe 2026 appeared first on The Microsoft Cloud Blog.

Exactly one year ago, we outlined how generative AI is creating a new era of efficiency and innovation for logistics and supply chain. We mapped AI use cases across the value chain, from demand forecasting to AI-based customer service, and introduced two new reference architectures for logistics and supply chains: adaptive cloud and AI‑enhanced experiences, alongside innovations in Microsoft Dynamics 365.

Since then, technology has rapidly evolved. We are now in the agentic era of AI with agents being capable of reasoning, planning, and taking action across complex supply chain workflows. End-to-end agent hosting like in Microsoft Foundry and open protocols such as Model Context Protocol (MCP) have made it easier for AI agents to connect with each other as well as enterprise systems, tools, and data.

Additionally, there have been significant advances in 3D simulations, robotics, and embodied intelligence. Open platforms for physical AI like NVIDIA Cosmos with world foundation models (WFMs) as well as the OSMO edge-to-cloud compute framework on Azure enable machines and humanoid robots to act more effectively in the physical world, resulting in broader automation across warehouses, distribution centers, and transportation. This new article picks up Microsoft’s perspective on supply chain and logistics one year after our previous blog article and explores how our own logistics teams as well as frontier customers and partners use this new wave of innovations together with Microsoft.

Microsoft supply chains: Our own “customer zero” story

Microsoft operates one of the world’s most far-reaching cloud supply chains spanning more than 70 Azure regions, over 400 datacenters, and a network of more than 600,000 km of fiber. Our datacenters are the backbone of Microsoft Azure powering everything from AI infrastructure and collaboration tools to networking and security. Microsoft also runs supply chains for Microsoft Windows and Devices with Surface hardware and PC accessories as well as Xbox consoles and gaming hardware.

All of our supply chains have undergone a fundamental transformation over the past decade, evolving from a reactive, manual environment into a rapidly emerging autonomous, agentic supply chain. In the past, our operations were dominated by Excel-based reporting, limited visibility, and siloed data. In 2018, we consolidated more than 30 systems into a single supply chain supply chain data lake on Azure, enabling predictive analytics and the first generation of cognitive supply chain capabilities. In 2022, we began experimenting with generative AI, followed by the development of an AI platform to operationalize agents at scale. Today, this foundation is accelerating to fully autonomous agents, and more than 25 AI agents and applications have been deployed. Below are three examples:

• The Demand Planning Agent drives AI‑based demand–simulations for non‑IT rack components—improving forecast accuracy and reducing manual reconciliation.
• The Multi‑Agent DC Spare‑Part Space Solver uses computer‑vision‑driven monitoring and multi‑agent reasoning to forecast spare‑part storage needs and proactively mitigates space or stockout risks.
• The CargoPilot Agent continuously analyses transport modes, routes, cost structures, carbon impact, and cycle times—providing optimized shipment recommendations that balance speed, sustainability, and efficiency.

The goal is to operate over 100 agents by the end of 2026 and equip every employee with agentic support. The impact today is already huge: AI in logistics is saving our teams hundreds of hours each month demonstrating how agentic operations are translating directly into efficiency and business value. Both in our own Microsoft supply chain transformation and Frontier customers we work with, we have seen that unifying the data estate is key. Yet, it’s what organizations do next that truly generates value with AI.

In supply chain, we believe real value gets unlocked by driving three elements:

• Enabling AI-powered supply chain simulations.
• Building agentic supply chains.
• Integrating first physical AI innovations.

Simulations: The digital twins of supply chains

As supply chains become larger, more interconnected, and more exposed to global volatility, simulating scenarios before they unfold is becoming a critical capability to reduce risk and increase resilience. Discrete event-based simulations (DES) within supply chains enable the development of a virtual risk-free model to test how a complex system reacts to interventions and variables before implementation. With Microsoft’s advanced modelling tools such as Azure Machine Learning and the new machine learning model in Microsoft Fabric with Power BI semantic models, organizations in supply chain and logistics can simulate demand patterns, shortages, or supply chain disruptions.

Our partner paiqo offers with prognotix an AI-powered Forecasting Platform available on the Microsoft Marketplace. More than 70 algorithms enable supply chain experts to generate and optimize highly accurate demand forecasts directly within their Azure environment. Cosmo Tech offers an AI simulation platform for Advanced Supply Chain Risk Management on Azure, offering enterprise customers dynamic digital twins that simulate how disruptions and decisions impact system-wide performance. InstaDeep uses Azure in high-performance compute for AI-enabling deep reinforcement learning and predictive analytics that optimize last-mile delivery, inventory levels, and fleet utilization.

The next level of simulation combines multiple physical simulations in 3D environments and discrete event-based simulations to enable teams to build comprehensive digital twins of warehouses, distribution centers, production lines, and logistics networks. These virtual environments allow organizations to model both the physical behavior of assets and the dynamic flow of operations. By integrating these simulation methods within a digital twin and applying AI, teams can predict future outcomes, optimize performance, and prescribe actions that drive continuous operational improvements. This can help customers lower capital expenditure, shorten commissioning, and ramp up phases, as well as improve operational key performance indicators (KPIs).

Taking warehouses as an example, customers and partners can build advanced, AI-enabled 3D visualizations for four key scenarios:

• Warehouse planning (such as greenfield and brownfield).
• Warehouse monitoring (like real-time monitoring and people movement heatmaps).
• Warehouse improvement (for example trailer dwell time optimization and collision detection for safety and automation).
• Warehouse maintenance (like asset monitoring in real-time, detect quality issues, and reduce rework).

In collaboration with NVIDIA we offer access to NVIDIA libraries and frameworks including NVIDIA Omniverse™, NVIDIA Isaac Sim™, and NVIDIA Omniverse Kit App Streaming that enable developers to build applications and workflows to simulate and test intelligent machines in digital twins before building or deploying anything in the real world. Applications built on these libraries and frameworks allow developers seamlessly integrate geometry data (such as 2D, 3D, and point clouds), AI capabilities (for example large language models, Volume Shadow Copy Service (VSS), and Solvers), and Internet of Things (IoT) signals across operational technology (OT) environments.

The reference architecture below illustrates how to combine cloud and edge computing using NVIDIA Omniverse Kit App Streaming to visualize warehouse operations in real-time with graphics processing unit (GPU) accelerated Kubernetes clusters natively deployed on Azure to remotely monitor, analyze, and optimize warehouse performance with greater precision and situational awareness.

Inside the physical warehouse, operational data from robotic arms, conveyors, and warehouse sensors are captured on the edge using Azure IoT Operations running on Arc-enabled Kubernetes and using MQTT broker. The architecture adopts the Universal Scene Description format (OpenUSD) to ensure that 2D, 3D, and point cloud geometry from the warehouse can be seamlessly integrated into the digital twin. Microsoft Fabric takes up the data in the cloud to provide a unified analytics foundation. Eventstream and eventhouse capture incoming telemetry as real-time streams or batch data. Microsoft OneLake acts as the governed, centralized data lake that consolidates all warehouse data. Digital twin builder transforms raw IoT signals into a contextualized virtual representation by mapping telemetry to the warehouse’s digital model. Powered by NVIDIA Omniverse, high-fidelity simulation and spatial computing occur creating a real digital twin which is streamed directly to the browser—eliminating the need for high-end local hardware. Tools such as Microsoft Copilot Studio and Microsoft Foundry enable natural language interaction. Across all stages, security is maintained through Azure Arc, ensuring consistent governance, configuration, and policy enforcement across edge and cloud.

SoftServe has proven to be an excellent delivery partner for digital twin applications. Together with Microsoft, they seamlessly integrated AI agents built on NVIDIA libraries and open models into beverage production simulations at Krones, enabling physical-accurate digital twins that reduced cycle times from hours to under five minutes. Similarly, at Toyota Material Handling Europe, SoftServe built a digital twin for simulating autonomous forklifts in virtual warehouse environments, enabling rapid testing, optimization, and safer deployments, helping to reduce the training times of autonomous systems by more than 30%.

TeamViewer’s augmented reality platform Frontline provides an additional simulation angle. Wearables such as smart glasses or wrist-mounted devices bring data seamlessly to frontline workers to get guidance in a hands-free manner for picking and packing as well as AI‑assisted counting. At DHL Supply Chain, TeamViewer’s solution is deployed globally to support vision picking of over 1,500 workers across 25 United States sites with fully hands‑free processes.

Agentic supply chains: The multi-agentic web

Agentic supply chains mark a new era of autonomous AI systems that proactively manage and optimize end-to-end supply chain operations. These agentic systems aim to continuously improve overarching KPIs like operating margin or cash conversion as well as specific KPIs such as lead time or freight cost per unit, ensuring that every agentic action contributes to measurable business impact.

Agentic supply chains are built on today’s human-driven tasks and encode the underlying decision-making logic. They include single purpose agents such as “troubleshooters” that constantly diagnose issues and propose fixes as well as “orchestrator agents” like planners or organizers that coordinate multistep workflows. These agents become functional through modern data fabrics, robust systems of record, and event-driven architectures that provide real-time information and governance.

Below is an overview of supply chain agents we have identified along the value chain through multiple customer and partner discussions.

Frontier Firms have already created value with multi-agentic systems.

• CSX Transportation has deployed a multiagent system that validates customer eligibility, routes complex requests, and supports rail operations with multistage coordination.
• Dow Chemical operates invoice analysis agents that review thousands of freight invoices each day, automatically detecting discrepancies and saving the company millions across its global shipping network.
• C.H. Robinson has rolled out a large fleet of generative AI agents including fast quoting agents that deliver tailored freight quotes and automating key steps along the shipping lifecycle.
• Blue Yonder has created an off-the-shelve Inventory Ops Agent on the Microsoft Marketplace that identifies supply–demand mismatches in real-time and recommends corrective actions such as alternate sourcing or demand swaps to keep inventory levels optimized.
• Resilinc offers an agentic supplier risk platform on Azure with pre-built AI agents (like for disruption, tariffs, and compliance) that autonomously evaluate potential impacts, initiate supplier engagement and recommend mitigation strategies.
• o9’s Digital Brain platform on Azure has been enhanced with various AI agents taking over simple tasks like getting specific data and more complex like creating full demand reviews.
• GEP recently added to their source-to-pay GEP SMART and supply chain solution GEP NEXXE (both built natively on Azure), a portfolio of AI agents that cover sourcing, negotiation, contract lifecycle, spend analysis, and market intelligence.
• Kinaxis offers its Maestro supply chain planning platform including AI agents that sense disruptions, run scenario simulations, and provide prescriptive insights through natural language.

Additionally, several delivery partners have used Microsoft tools like Microsoft Foundry and Copilot Studio to build agents for customers at high speed.

• Avanade, for example, offers concrete off-the-shelf agents including a trade compliance agent, a digital twin agent, and lead-2-cash agents.
• Softserve offers a catalyst with 3 customized agents in 30 days.
• NTT DATA is developing a simulation-driven, agentic AI-powered decision-support system for supply chain network agentic rebalancing platform.
• PwC delivers end-to-end agentic AI consulting services, powered by distinctive industry expertise.
• Capgemini is currently building an agentic end-to-end offering using the latest Microsoft IQ technology to be released at Hannover Messe in April 2026.

Microsoft Work IQ, Foundry IQ and Fabric IQ together form an intelligence layer for supply chains—from demand planning to inventory and customer service—that connects how people work, how the business operates, and what the organization knows. This gives AI agents full enterprise context so that agents can reason, simulate scenarios, and act in line with real-world constraints and KPIs such as inventory turnover to support better decisions.

Together with our strategic partner Celonis we have developed a new reference architecture leveraging Fabric IQ and the Celonis Process Intelligence Graph to transform fragmented supply chain data into agentic workflows. A collaborative stack that integrates raw data at the bottom and creates intelligent, automated actions at the top.

On the System of Record (SoR) layer, data is often siloed and does not “speak the same language,” leading to a fragmented understanding within the supply chain. Microsoft Fabric unifies this data through mirroring, streaming, or multi-cloud shortcuts with the goal to create a zero-copy connection and ensure the data is fresh and accessible without the weight of traditional extract, transform, and load (ETL) processes. Fabric IQ provides a reasoning layer that translates raw, unified data in OneLake into context-aware insights. This is the basis for Celonis’ Process Intelligence (PI) Graph which sits between data and the automation and uses process mining to map out how the supply chain actually runs—generating operational supply chain insights and suggesting improvement potentials from a process point of view. It communicates with Microsoft Fabric through Rest APIs, providing the knowledge and context that AI needs to make sense of the data. The agentic layer is divided into three functions:

• Building: Use Copilot Studio, Microsoft Foundry, and Power Automate to create custom AI agents.
• Orchestrating: Use MCP and Agent2Agent Protocol (A2A) to manage how different agents work together.
• Overseeing: Use the control plane for agents in Agent 365 (generally available in May 2026) to monitor agent activities and ensure performance as expected.

On the top layer, with the help of Microsoft Entra ID, insights and suggested actions are shown in tools employees use, such as Microsoft Teams, Microsoft 365 Copilot, Dynamics 365, Power Apps or in the Celonis UI.

A large global pharmaceutical company is using the above architecture to unify fragmented logistics data, enabling real-time identification of temperature-critical pharmaceutical returns and designing an agentic return process that unlocks multi-million euro annual productivity gains. Uniper automated material and service needs with Celonis and Microsoft. Microsoft Copilot in Teams and Power Automate orchestrate approvals, SAP actions, and replace manual component planning with proactive, agentic workflows that ensure timely material availability.

Physical AI: From warehouse handling to last mile deliveries

Physical AI is the final evolution of supply chain intelligence, building on simulations and agentic AI and embodying that intelligence directly in the physical world. In the near future, humanoid robots and robotic systems will physically take over more and more operational tasks along supply chains and logistics: from trailer unloading and sorting, pallet handling and replenishment, to packing and labelling and autonomous last‑mile deliveries. As intelligence moves from screens into machines, supply chains and logistics may gain a new level of physical agility.

Microsoft is pushing the frontier of physical AI with it’s new Rho‑alpha robotics model that combines natural language, visual perception, and tactile feedback to make robots more adaptive and autonomous. Microsoft has launched an early access research program with selected partners to advance co‑training and domain adaptation and aims to integrate the model in Microsoft Foundry in the coming months. Already today, customers and partners may take the below robotics toolchain reference architecture to train and deploy warehouse robotics with NVIDIA Osmo on Azure.

This toolchain is an open-source, production-ready framework that integrates Azure cloud services with NVIDIA’s physical AI stack, from simulation to training and deployment. It combines Azure Machine Learning, Azure Kubernetes Services (AKS), Microsoft Fabric, Azure Arc, and NVIDIA’s robotics and AI stack. NVIDIA Isaac Sim and Isaac Lab enable high-fidelity simulation and reinforcement learning, while NVIDIA OSMO orchestrates scalable training workflows across cloud and edge environments.

Detailed information can be found here.

Hexagon Robotics has started to deploy this architecture using Azure IoT Operations as well as Fabric Real-Time Intelligence in Microsoft Fabric to provide production-ready humanoid robotic solutions. Their industrial humanoid robot, AEON, combines dexterity, locomotion, and unique spatial intelligence to tackle complex industrial use cases for warehousing and logistics such as inspection and inventory taking.

Figure AI, funded by Microsoft, enables the deployment of their humanoid robots in real-world logistics environments using Azure’s AI infrastructure. Their latest model Figure 03 can take over warehouse tasks such as sorting packages at conveyor belt speeds and help at last-mile delivery with near human-level precision.

KUKA and Microsoft jointly developed iiQWorks.Copilot, an AI-powered assistant that enables natural language robot programming and significantly simplifies automation tasks. By integrating Azure AI services, the solution allows users to design, test, and deploy robot workflows faster and more safely—cutting programming time for simple tasks by up to 80%. This has benefitted all KUKA robotics deployed in warehouses and logistics.

Wandelbots’ NOVA software layer combined with Azure cloud services unifies heterogeneous robots and brings adaptive automation to the shop floor. Wandelbots NOVA streamlines warehouse and fulfillment operations such as palletizing by simplifying robot programming, accelerating deployment, and enabling AI-powered path planning and scaling across multiple robot brands. Together, these capabilities position Wandelbots NOVA as a physical AI platform for orchestrating and scaling AI-powered automation across supply chain operations.

Get in touch with us

Contact us directly at screquests@microsoft.com or go to Microsoft for Manufacturing to explore how Microsoft technologies can transform your supply chain. Join us at Hannover Messe in April 2026 to hear directly from our industry leaders, explore cutting-edge ideas, and connect with peers.

The post Supply Chain 2.0: How Microsoft is powering simulations, AI agents, and physical AI appeared first on The Microsoft Cloud Blog.

AI is delivering real, measurable returns for telecom

AI is already delivering measurable business impact across industries, and telecom is among the leaders. A recent IDC study shows operators are achieving 2.8 times return on generative and agentic AI investments, with many leading companies reaching up to 5 times return. Frontier telecoms are realizing even greater returns from AI by making it foundational to how their business operates—from employees and core workflows to the end‑to‑end value chain. These leaders are moving beyond incremental efficiency by using an end-to-end AI platform and unified data approach that embeds AI into everyday operations, enabling faster decisions, tighter execution, and continuous performance improvements across their organization.

With more than 80% of the Fortune 500 building active AI agents, Microsoft Copilot is rapidly becoming essential to how employees think, collaborate, and deliver results. As AI proves its value, telecoms are moving beyond pilots to connected intelligence that elevates customer experiences, replaces manual workflows with autonomous operations, hardens and self‑heals networks, and drives new revenue opportunities. Connected intelligence will differentiate fast-moving telecoms across every area of business operation.

Read more about Frontier telecoms here.

Return on intelligence and trust

For telecoms, achieving value from scalable AI depends on two factors: intelligence and trust. Built from three complementary IQ elements—Work IQ, Fabric IQ, and Foundry IQ—Microsoft IQ is the intelligence layer that connects AI, data, and context across the business. It gives AI agents deep awareness of how people work, how the business operates, and how decisions are made. This intelligence layer accelerates decisions, improves customer experiences, automates operations and networks, and unlocks new ways to monetize AI‑based services. Trust is built through Microsoft’s carrier‑grade control plane, which provides built‑in monitoring and governance across the entire AI platform, including AI agents from our partner ecosystem, to allow telecoms to innovate responsibly, support regulatory compliance, and scale AI with confidence.

At MWC 2026, Microsoft is announcing new technologies that will help telecoms move forward with AI and use intelligence to drive the business.  Microsoft delivers this through a single platform that brings AI, unified data, trust, and governance together to enable telecoms with connected, actionable insights to accelerate innovation and growth.

Building the sovereign, AI-ready edge for telecom

For telecoms, thriving in the era of agentic intelligence begins with a resilient foundation. Today, we’re advancing Microsoft Sovereign Cloud with fully disconnected operations, extending cloud capabilities and AI-ready infrastructure deeper into operator networks than ever before. As demand accelerates for low-latency services, real-time processing, and stronger assurances around data sovereignty and regulatory compliance, the edge has become a critical extension of telecom networks and foundational layer of modern digital infrastructure. This is especially true for regulated industries and mission-critical scenarios where operational resilience and control over data are paramount.

To support these confidential environments, Azure Local offers full stack capabilities that support customers across connected, intermittently connected, and fully disconnected modes. This is essential for sovereign environments where uninterrupted access to operational, network, or customer-facing systems is non-negotiable. Azure Local disconnected operations keeps critical services running securely without connectivity to the cloud. At the same time, Foundry Local will be able to offer modern infrastructure and support for large AI models. Using the latest graphics processing unit (GPU) infrastructure from partners like NVIDIA means customers with sovereign needs will now be able to run models locally on their own hardware, inside strict sovereign boundaries enabling powerful, local AI inferencing in fully disconnected environments.

Customers can deploy and govern workloads inside their own datacenters, using familiar Microsoft Azure experiences and consistent policies, without depending on continuous connection to public cloud services.

AT&T uses Azure to support its cloud and edge strategy, enabling consistent operations across a distributed network footprint. By applying Azure’s management and governance capabilities across environments, AT&T can bring compute and data processing closer to where services are delivered while maintaining strong security and operational oversight.

“As we expand our network edge capabilities, Azure plays a key role in helping us apply cloud-native principles across our distributed infrastructure. The scalability and flexibility of Azure’s adaptive cloud approach allow us to deploy services closer to our customers, maintaining control while providing the reliability and performance they expect from AT&T. This long-standing partnership enables us to innovate and deliver next-generation experiences at the edge.”

—Sherry McCaughan, Vice President, Mobility Core and Services

Azure’s cloud-native management capabilities and global platform enable organizations like AT&T to modernize and scale edge environments, supporting next-generation services while maintaining consistent governance, security, and operational control. Native management capabilities and a global platform enable organizations like AT&T to modernize and scale edge environments, supporting next generation services while maintaining consistent governance, security, and operational control. 

We’re also investing in multi-rack deployment capabilities for Azure Local, extending scale points to support large-scale infrastructure for the most demanding, mission-critical workloads. Customers will be able to expand from single-node and cluster deployments to multi-rack environments designed for high availability, fault isolation, and operational simplicity at scale. Multi-rack deployment on Azure Local is currently in preview and will be available in the coming months.

Microsoft is collaborating with telecom operators to deliver sovereign cloud platforms and managed services that combine hyperscale innovation with local control, enabling enterprises to meet data residency, regulatory, and security requirements while accelerating trusted digital and AI transformation.

Agentic customer experiences that drive growth

With this foundation in place, telecoms can move beyond isolated use cases to scale intelligence across experiences and growth models. The same agentic capabilities that transform customer engagement also unlock new ways to monetize services, reduce cost to serve, and create differentiated value.

Today, telecom customer journeys are fragmented. Customers often switch channels to complete tasks, driving abandonment and cost. AI agents turn customer intent into end‑to‑end action across systems. Microsoft is now offering a telecom agentic store reference framework to replace click‑based journeys with natural‑language interaction. Coordinated AI agents handle discovery, sales, service, billing, and partner offers in the background—customers state their goal and agents deliver the outcome. The result is higher digital completion, faster resolution, and better experiences. This framework also creates a new monetization platform, enabling federated AI marketplaces with built‑in identity, billing, and sovereign deployment for trusted ecosystem commerce at scale. Telecoms are already working with Microsoft and system integrators to adopt this architecture—unifying sales and service, reducing cost‑to‑serve, and creating a scalable foundation for partner‑led innovation. 

FiberCop modernizes edge cloud and contact center

FiberCop runs Italy’s most advanced, far-reaching and pervasive digital network infrastructure. FiberCop recently announced that it has integrated Azure Local into its network, transforming the access infrastructure into an edge cloud platform capable of delivering cloud-native services, virtualized network functions, and advanced workloads while meeting sovereignty and compliance requirements. Today, FiberCop announces that it is accelerating its agentic transformation, moving to an AI‑first contact center model where autonomous AI agents, Copilot, and human expertise work together. By adopting Dynamics 365 Contact Center, FiberCop has begun modernizing customer engagement with unified data, intelligent routing, and AI‑powered self‑service and assisted service that delivers more efficient operations and better customer experiences at scale.

Introducing Ericsson Enterprise 5G Connect to reimagine customer experience

Ericsson announces ongoing collaboration with Microsoft introducing the Ericsson Enterprise 5G Connect solution—validated on Microsoft Surface 5G Copilot+ PCs and built on top of Windows 11’s Enterprise Cellular Managed Connectivity (ECMC) capabilities. This new offering enables enterprises to centrally manage secure, seamless 5G connectivity for mobile and hybrid employees, using automatic network switching and robust policy enforcement to enhance productivity and security. IT teams gain scalable management and control, while end users benefit from uninterrupted, AI-powered experiences across private and public 5G networks. The solution is currently being piloted by Ericsson and is in private preview. To learn more, visit our Windows IT Pro blog.

Intelligent business operations, built for telecom

Delivering connected customer experiences depends on what happens behind the scenes. Telecom operations require trusted, governed access to network and customer data. That’s why operators are moving from legacy data warehouses to a modern lakehouse that unifies business and network data.

Microsoft Fabric provides a single, policy‑governed data foundation for real‑time, operational, and analytical data to speed AI insights at scale. Building on this foundation, today we’re announcing Azure Databricks Lakebase will be available in March 2026, giving telecom operators a managed PostgreSQL environment with next generation separation of storage and compute for transactional data, providing instant availability, instant clones, and scale-to-zero. This brings online transaction processing (OLTP) capabilities to the Databricks Data Intelligence Platform on Azure designed for developer performance with low total cost of ownership (TCO), eliminating the traditional gap between operational systems and the lakehouse.

Partners are building on this data foundation as well. For example, Nokia integrates its data suite with Fabric to securely unify network telemetry and reduce AI use case development time by up to 80%.

MTN transforms fraud prevention with AI

In today’s rapidly evolving digital landscape, identity theft and first-party fraud are escalating at alarming rates, posing significant risks to individuals and businesses across South Africa. MTN has made a bold move to transform its fraud management approach by harnessing advanced Microsoft technologies. Shifting from traditional, reactive methods to a proactive, AI-powered ecosystem, MTN is not only protecting its customers and strengthening revenue defenses but also reinforcing national digital resilience and contributing to a safer, more secure digital economy for all.

Amdocs powers intelligent business operations

Amdocs is making several announcements with Microsoft that deepen integration to deliver next-generation solutions. The first is AI-powered application modernization through the Amdocs Agentic Services platform, embedding Microsoft AI solutions such as Azure OpenAI and Microsoft Foundry into end-to-end modernization and migration to Azure. Second, Amdocs Cognitive Core platform built on amAIz, offering prebuilt agent libraries, cross-domain insights, and telecom-specific AI that integrates with any business or operating system stack and runs securely on Azure. Colt Technology is working with Amdocs and Microsoft to streamline operations and accelerate service delivery with real-time insight.

To learn more about transforming the OSS/BSS with agentic AI, read this blog.

Power autonomous networks with built-in trust and control

As intelligence is embedded across data and operations, the next frontier is the network itself. Agent-driven operations enables networks to move from reactive management to autonomous executions that respond faster, reduce risk, and improve resilience at scale.

To help operators move from pilots to production at scale, Microsoft is evolving its network operations agent (NOA) reference architecture—a proven framework shaped by real world deployments, industry collaboration, and learnings from Microsoft’s NetAI program.

NOA is built for today’s telecom realities: exploding event volumes, rising complexity, and persistent skills gaps. The latest evolution deepens integration with Microsoft AI and collaboration platforms, strengthens alignment with open standards, and delivers a modular, production-ready path to autonomy—without compromising telco-grade safety, governance, or human oversight. Operators engage AI directly through Microsoft 365 Copilot and Microsoft Teams, while Microsoft Foundry and the Microsoft Agent Framework provide a governed, observable runtime for multi-agent orchestration at scale. Expanded support for TM Forum Open APIs helps ensure interoperability across existing business and operations support systems, making NOA an open, secure foundation for autonomous networks. Read more about NOA.

Leading operators such as Far EasTone Telecom and Vodafone are already applying this blueprint to modernize network operations, reduce human error, accelerate recovery times, and enable engineers to focus on higher value work.

Far EasTone Telecom (FET) is turning agentic AI into real operations impact 

FET exemplifies how leading operators are turning this architecture into real operational impact. FET is using the NOA framework to redefine cloud native network operations by embedding agentic AI across its NOC and change management workflows. Today, nearly 60% of its NOC operations are AI-assisted, with about 10,500 operational tasks executed per month, including incident summaries, automated ticket closure, network checks, and proactive voice notifications. AI agents now handle largescale alarm correlation and root cause analysis in seconds, supporting nearly 7,000 monthly operational queries with an average response time of 16 seconds, and enabling most maintenance actions to complete within one minute. This shift has significantly reduced human error, accelerated recovery times, and allowed engineers to focus on higher value work.

Vodafone’s journey toward intelligent network operations

Vodafone is working with Microsoft to apply this proven AI‑powered blueprint for autonomous network operations across transport infrastructure and field‑force management. The collaboration combines Vodafone’s deep network expertise with Microsoft Foundry and the NOA framework to modernize how large‑scale telecom networks are operated.

This blueprint is built on Microsoft’s own experience running autonomous agents across its global Azure transport network, where AI continuously monitors performance, identifies root causes, and autonomously manages more than 65% of fiber‑break field dispatches—improving time to repair by up to 25% and accelerating root‑cause analysis by 80%. By applying these proven capabilities to Vodafone’s transport network, the two companies are accelerating the shift toward intelligent, automated transport network operations across the telecom industry.

“By working with Microsoft, we’re combining deep network expertise with proven AI‑powered operations to create something greater than either could achieve alone. Together, we’re building intelligent, automated transport network operations that empower our teams and deliver faster, more resilient connectivity networks for our customers.”

—Alberto Ripepi, Chief Network Officer, Vodafone

Other operators, including AT&T, T-Mobile, Telefónica, and MEO, are adopting Microsoft Foundry as a blueprint for scaling agentic AI across complex, multi-vendor networks. 

Today, Kenmei announces it is collaborating with Microsoft to help operators accelerate their path toward autonomous networks by combining Kenmei’s telecom intelligence offer with Azure and Microsoft Fabric to enable scalable analytics and agentic AI–powered operations. Already in use at leading operators like Telefónica and Etisalat (e&), this collaboration brings proven deployments into a broader cloud and AI ecosystem designed to reduce manual effort, speed decision‑making, and unlock new levels of network automation.

Microsoft achieves global milestone to extend internet access with Starlink

As telecoms scale intelligence across networks, operations, and experiences, connectivity remains the starting point. Because AI only delivers impact where access exists, expanding internet access is foundational to an intelligent and inclusive telecom future.

Today, 2.2 billion people around the world remain unconnected.¹ To help overcome this barrier, Microsoft pledged to bring access to 250 million people by 2025. We are pleased to share that we’ve expanded internet access to 299 million people through the power of technology and partnerships in communities around the globe. But we know there is more work to do to support unconnected communities and enable global participation in the AI economy.

In support of this on-going effort, we are unveiling a new collaboration with Starlink designed to bring Microsoft’s experience with governments, local operators, and community partners together. With more than 9,000 satellites in low-Earth orbit, Starlink will extend digital infrastructure to rural, agricultural, and hard-to-reach communities. You can read more about how we met this milestone and are continuing to extend AI-enabled connectivity aligned with community needs.

Join us at MWC 2026 to learn more

Frontier telecoms are already proving what’s possible when AI, data, trust, and governance come together on a single platform to power faster operations, autonomous networks, intent-driven engagement, and real return on intelligence.

Join Microsoft At MWC 2026 to see how operators and partners are moving from AI promise to production through real deployments, live demos, and customer stories.

¹Facts and Figures 2025, ITU.

The post Microsoft accelerates telecom return on intelligence with a unified, trusted AI platform appeared first on The Microsoft Cloud Blog.

Manufacturing’s moment: Why AI, why now?

Today, AI isn’t just a buzzword or a distant promise. It’s a practical lever for manufacturers to unlock new value, drive efficiency, and build resilience for the future.

At Microsoft Ignite 2025, our team explored how industrial AI is reshaping the economics of manufacturing. Drawing from real-world customer stories and the latest research, we’ll unpack where the ROI is real, what’s driving it, and how you can take the next step on your own AI journey.

u003cpu003eDrive measurable outcomes with AIu003c/pu003e

Return on Intelligence: Scaling Business Value with Industrial AI

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From siloed data to intelligence on tap

Every manufacturer knows the pain points: unplanned downtime, inefficiencies that eat into margins, and supply chain blind spots that disrupt delivery. Too often, these issues are compounded by fragmented systems and a lack of real-time data visibility. The result? Slow decision-making and missed opportunities.

But the landscape is changing. According to a 2025 commissioned  Forrester Consulting Total Economic Impact™ study on the economic impact of industrial transformation with Microsoft AI, manufacturers that invest in unified data platform and bring together data across IT and Operations Technology (OT) systems could see the following benefits¹:

• Up to 50% reduction in defects
• Up to 50% fewer inventory shortages
• Up to 40% decrease in frequency of equipment failures
• Up to 457% projected ROI over three years

Take KUKA, a global automation leader. Facing fragmented systems and a growing robotics skills gap, KUKA turned to Microsoft Azure AI and Microsoft Foundry Models. The result? Programming time cut by up to 80%, democratizing robotics and accelerating workflow deployment. With predictive insights and real-time analytics, KUKA broke down data silos and empowered teams to innovate faster.

Sustainability: A greener, more profitable path

Manufacturers today are under intensifying pressure from regulators, customers, and their own boards to reduce emissions, increase energy efficiency, and eliminate waste. Yet many sustainability challenges stem from the same root problem: disconnected systems that make it difficult to measure, optimize, and scale improvements across facilities.

But the momentum is shifting. According to the Forrester study on the economic impact of Microsoft’s industrial AI capabilities, manufacturers see AI as a critical lever to drive measurable environmental and financial gains by optimizing energy usage, refining processes, and reducing carbon emissions. With Microsoft AI solutions, surveyed manufacturers who are Microsoft Azure customers expect to achieve:

• 78% expect to reduce energy consumption
• 88% expect to improve energy efficiency
• 53% expect to reduce CO₂ emissions

Take Schneider Electric, a global leader in energy management with ambitious sustainability goals to reduce environmental impact and improve efficiency across its operations. By integrating Azure OpenAI and Azure Machine Learning into its EcoStruxure platform, Schneider gained real‑time insight into energy usage, carbon‑related performance, and optimization opportunities. The impact? AI‑powered models that surface efficiency recommendations, accelerate sustainability decision‑making, and help facilities cut waste at scale. And because EcoStruxure underpins thousands of customer deployments, these AI‑powered insights also lets its customers pursue their own sustainability goals with greater speed, accuracy, and measurable operational improvements.

Empowering people: AI as a workforce multiplier

Labor shortages, rising workload complexity, and persistent training bottlenecks continue to stretch manufacturing teams thin. Many frontline and knowledge workers spend too much time searching for information, navigating outdated systems, or performing repetitive tasks that slow productivity and sap morale.

But AI is shifting this dynamic. Manufacturers are adopting intelligent assistants, predictive tools, and automated workflows that free employees to focus on higher‑value work. According to recent industry data, organizations are already seeing material gains:

• 66% of repetitive tasks automated
• 70% of organizations report productivity gains
• 75% reduction in onboarding time

Take Audi AG, a global automotive leader navigating rising internal demand for support and process guidance. To alleviate mounting human resources and IT strain, Audi launched its first AI-powered self-service assistant using Foundry that was deployed in just two weeks. The impact? Faster access to information, fewer routine queries, and more time for teams to focus on meaningful, high-value work. Audi’s example shows how AI doesn’t replace people but amplifies them.

The agentic era: What’s next?

Manufacturers are moving beyond task‑level automation toward a new operating model where AI works alongside teams to coordinate decisions, optimize workflows, and adapt to changing conditions in real time. This next era isn’t about experimenting on the margins, but about treating AI as a core capability that strengthens every part of the enterprise.

Platforms like Azure OpenAI, Microsoft Fabric, Foundry Models, and Microsoft 365 Copilot are already helping organizations make that shift. And the economic signal is strong. Forrester’s Total Economic Impact study attributes the financial upside of the broader Industrial AI value stack to improvements across operations, productivity, and supply chain performance:

• Up to 457% projected ROI over three years

These gains compound as AI becomes embedded across the business, accelerating impact as intelligent systems take on more routine work, surface insights faster, and support teams in making better decisions at every stage of production. Manufacturers who fail to operationalize AI risk falling behind peers who are building intelligence directly into their processes, products, and customer experiences.

A practical path forward: How to get started

To fully realize this next chapter, manufacturers need a clear, actionable roadmap grounded in governed data, scalable AI systems, and measurable business outcomes.

Here’s a practical roadmap from aspiration to action:

• Identify high-impact use cases: Focus on areas like predictive maintenance, supply chain optimization, and quality control where AI can deliver quick, measurable wins.
• Define success metrics: Set clear key performance indicators (KPIs) to track ROI and impact across teams and facilities. What gets measured gets managed.
• Leverage proven platforms and partners: Don’t reinvent the wheel. Use established AI platforms like Azure and work with partners who understand both technology and manufacturing.
• Start small, scale fast: Begin with urgent, actionable business challenges. Build on proven frameworks and architect for scale. As Audi AG showed, operational AI can be deployed at enterprise scale in weeks, not years.
• Invest in data foundations: Migrating legacy systems to the cloud and breaking down data silos are essential. Unified, AI-ready data is the backbone of successful industrial AI initiatives.

Learn how industrial AI can transform your business

Industrial AI is no longer a vision for the future, but a proven source of measurable value today. The manufacturers pulling ahead are the ones building AI into how they operate, scale, and compete. Whether you’re laying the groundwork or accelerating existing initiatives, now is the moment to turn momentum into impact.

Return on Intelligence: Scaling Business Value with Industrial AI

Deeper insights, real-world case studies, and a practical roadmap

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Start your journey toward smarter, more resilient, and more competitive manufacturing.

¹ New Tech: The Projected Total Economic Impact™ Of Microsoft Artificial Intelligence Solutions For Industrial Transformation. Results are over three years for a composite organization based on interviewed and surveyed customers.

The post The ROI of AI in manufacturing: Where adoption becomes advantage appeared first on The Microsoft Cloud Blog.

What is a Frontier Firm?

Microsoft defines a Frontier Firm as a human-led but AI-operated organization that integrates AI agents as core team members—enabling rapid scaling, agile operations, and enhanced productivity through hybrid human-agent collaboration and on-demand intelligence.

Microsoft identifies four key pillars of AI transformation:

1. Enrich employee experiences: Empower people with AI tools that remove friction and unlock creativity.
2. Reinvent customer engagement: Deliver transparency, personalization, and trust at scale.
3. Reshape business processes: Automate and optimize operations for speed, safety, and sustainability.
4. Bend the curve on innovation: Move beyond pilots to bold, repeatable frameworks that accelerate transformation.

Microsoft mining and metals customers Ma’aden, Petrosea, and Outokumpu bring these pillars to life and drive efficiency, productivity, cost reduction, safety, and sustainability. I’ll talk more about each one below.

From reactive to proactive: How AI and agents transform mining operations

Frontier Firms are deploying AI and agents across the mining value chain—not just to automate tasks, but to enable supervised autonomous systems that can monitor, reason, and act. AI-powered innovations are already delivering measurable results. For example, BHP and Microsoft have partnered to use advanced AI and machine learning technologies to enhance copper recovery at the world’s largest copper mine. AI-powered systems adapt in real-time to more variability. This optimizes recovery rates, improves throughput, and grade control. It also reduces downtime, waste, water usage, energy consumption, and costs.

With AI and agents, mining companies are not only addressing today’s challenges but are also building resilience and agility for the future—empowering their workforce, optimizing operations, and accelerating progress toward sustainability and growth.

The Frontier Firm in action: Empowering people with Microsoft Copilot and agents

Ma’aden, a leading mining and metals company, aimed to transform into a Frontier Firm by using digital innovation and AI to stay competitive in a resource-intensive industry while supporting sustainability and growth.

The company faced pressure to modernize operations without disrupting workforce roles—balancing efficiency gains with its commitment to empower employees rather than replace them and ensuring adoption of AI tools aligned with cultural and operational needs.

Ma’aden deployed Microsoft 365 Copilot and agentic AI capabilities across workflows—integrating generative AI into collaboration and decision-making. The focus was on augmenting human expertise, enabling employees to automate routine tasks, and free time for strategic thinking.

The transformation improved productivity, saved time, and enriched employee experiences—positioning Ma’aden as a Frontier Firm in mining. Employees reported higher engagement and confidence, as AI functioned as a trusted assistant, not a substitute—driving faster decisions, better collaboration, and sustainable growth.

“We intentionally gave Copilot to early adopters—people who are excited about technology—because they would act as change agents for the rest of their teams.”

—Khalid AlMutairi, Vice President, IT at Ma’aden

Turning obstacles into intelligent opportunities

Petrosea, a leading Indonesian mining and energy services firm, faced intense price wars and operational inefficiencies. To sustain growth and environmental, social, and governance (ESG) commitments, it needed to differentiate beyond cost and embrace innovation.

Legacy batch processes and limited data access hindered real-time decision-making. Remote sites and rising sustainability requirements amplified complexity, requiring a shift to advanced digital capabilities for competitive resilience.

Petrosea launched its 3D strategy: diversification, digitalization, and decarbonization—deploying the Minerva Digital Platform on Microsoft Azure, integrating Internet of Things (IoT) sensors, predictive analytics, and digital twins. It adopted Microsoft Azure OpenAI, Copilot Stack, automation agents, and advanced security.

The company achieved a 15% increase in productivity, a 9% reduction in operational costs, improved safety, and was selected by the World Economic Forum to join its Global Lighthouse Network. Petrosea transformed adversity into innovation, building competitive differentiation as a Frontier Firm through AI-powered workflows.

The integration of IoT sensors, predictive maintenance, and a Remote Operations Center reshaped their business processes—shifting from manual, site-based oversight to centralized, data-driven control that improved efficiency and safety.

“All these innovations led to a 9% reduction in operation costs, decrease in incidents, and enhanced safety measures with real-time corrective actions.”

—Krishna Nawacandra, Digital Project Manager, Petrosea

AI-powered sustainability as strategy

Outokumpu, a global stainless-steel leader, faced mounting pressure to meet ambitious climate targets and comply with Corporate Sustainability Reporting Directive (CSRD) reporting while embedding sustainability into its core strategy. Steel accounts for 10% of global greenhouse gas (GHG) emissions, making decarbonization critical.

Manual, fragmented sustainability reporting hindered transparency and efficiency. Outokumpu needed a unified, intelligent data approach to accelerate green value creation and explore AI-powered ESG innovations for competitive advantage.

Outokumpu partnered with Microsoft to deploy the Intelligent Data Platform, Microsoft Fabric, and Sustainability Manager—automating environmental data processes, enabling advanced analytics, and training leaders through the AI data-driven green value creation program.

Outokumpu achieved up to 75% lower carbon footprint versus industry average, launched Circle Green® stainless steel with 93% lower carbon footprint, and helps customers cut 10 million tons of CO₂ annually. Data and AI now fuel new business models, cost savings, and sustainable growth.

By using Microsoft Intelligent Data Platform and AI capabilities, Outokumpu is not just improving sustainability reporting—it is bending the curve on innovation by accelerating the development of new low-emission products and unlocking green business models that deliver both environmental and commercial impact.

“We have set a very clear goal for ourselves. We want to achieve something remarkable.”

—Heidi Peltonen, Vice President of Sustainability at Outokumpu

Advancing the Frontier for mining organizations

Across these three customer stories, a common thread emerges: transformation is not accidental—it is intentional. Frontier Firms combine human ambition with AI, Copilot, and agents to create scalable impact. Ma’aden reimagined productivity, while Petrosea transformed adversity into innovation, and Outokumpu turned data into a strategic asset.

What sets these leaders apart is discipline: they do not stop at adoption. They measure outcomes, codify frameworks, and scale with intent. Technology is a purpose multiplier, enabling safer operations, faster innovation, and sustainable growth.

As Frontier Firms continue to redefine what’s possible in mining, the horizon is filled with opportunities for AI-powered solutions—from predictive maintenance and autonomous operations to intelligent exploration, workflow automation, and sustainability platforms—each poised to unlock new levels of efficiency, safety, and innovation across the industry. The Microsoft GenAI for Energy Permitting Solution Accelerator applied to mining represents a promising step for Frontier Firms seeking to transform permitting from a bottleneck into a strategic advantage. Built on the Microsoft Cloud, the accelerator aims to help mining companies accelerate permitting timelines, improve compliance confidence, and enhance transparency with regulators and communities.

With these and other innovative solutions, the future belongs to Frontier Firms. Are you ready?

Discover solutions

Using Copilot in energy and resources

Explore the possibilities of AI transformation

Learn more

• Visit Microsoft for energy and resources and Microsoft for the mining industry.
• Explore Azure Arc.
• Learn more about Microsoft Security for enterprise.
• Discover over 1,000 AI customer use cases in the blog AI-powered success—with more than 1,000 stories of customer transformation and innovation.
• Read the latest International Energy Agency’s World Energy Outlook 2025.

The post Transforming mining: How Frontier Firms lead with AI and agentic innovation appeared first on The Microsoft Cloud Blog.

Over the past year, Microsoft engineers have road-tested that combination with executives, technicians, customer support representatives, and developers. Regardless of geography or market, operators voiced three universal priorities: break down operational silos, unlock data’s latent value, increase efficiency, and accelerate innovation without eroding trust. At TM Forum DTW Ignite 2025 in Copenhagen, Microsoft is demonstrating how the complementary relationship between ODA and agentic AI converts those ambitions into measurable business outcomes. 

Microsoft’s next chapter with the Open Digital Architecture 

Microsoft has been a hands-on contributor to TM Forum initiatives for well over two decades, coauthoring Open APIs, chairing working groups, and donating production hardened code that turns standards into deployable solutions. The ODA has become a focal point of that collaboration. By aligning Microsoft Azure cloud-native foundations with ODA’s composable blueprint, Microsoft helps operators assemble best-of-breed solutions without the drag of proprietary silos. 

Engineering teams from Microsoft work with communications service providers (CSPs) and industry suppliers to validate specifications, publish reference implementations, and channel field experience back into the standard. The result for operators is faster interoperability, reduced integration cost, and quicker time-to-value for new digital services. 

Yet a common obstacle remains: fragmented observability. Every vendor captures telemetry differently, leaving operations teams to deploy ad hoc log aggregators and parsers that inflate costs and slow incident response. Microsoft’s latest ODA contribution addresses this head-on. 

• ODA Observability Operator (open source on GitHub)
  The operator prescribes a common logging contract, integrates with Azure Monitor, and exposes health data through TM Forum nonfunctional APIs. In early trials, carriers shrank the meantime to detect billing anomalies significantly, freeing teams to focus on proactive optimization rather than forensic log diving.
• ODA Landing Zone for Azure
  Guidance and a best practice guide on infrastructure-as-code templates that hydrate into an ODA compliant environment—policy, security, and monitoring.

The “Growing B2B with autonomous agents” catalyst project, involving players like Microsoft, Vodafone, and various industry partners, leverages the ODA Accelerator to transform B2B sales for mid-tier enterprise customers by enabling flexible quoting and commerce through generative AI. It enables flexible quoting and commerce, allowing customers to find relevant products using semantic search and create customized solutions that meet their specific business requirements, budgets, and timelines. 

These assets illustrate a simple truth: standards only matter when they migrate from documentation into running code. By operationalizing TM Forum guidance, Microsoft accelerates engineering productivity, slashes integration costs, and strengthens the capabilities of telecoms, as well as providing a feedback loop for continual improvement. 

Empowering network monetization through network APIs 

Through our engagement with CAMARA and GSMA Open Gateway, Microsoft has played a pivotal role in helping operators monetize their networks via a robust partner ecosystem. This ecosystem supports the provisioning, aggregation, and routing of network API requests, enabling seamless integration and enhanced functionality. Our collaboration with industry leaders such as Aduna, Infobip, and Vonage brings aggregated network APIs directly to the Azure Marketplace. This integration grants Microsoft’s global community of developers and enterprises effortless access to essential network functions, including SIM swap detection, phone number verification, real-time device location, and on-demand quality-of-service controls. Standardized through the CAMARA open-source project—co-led by GSMA and the Linux Foundation—these APIs are designed for seamless integration, ensuring that operators can efficiently use network capabilities to drive innovation and growth. 

Giving the network a trusted Copilot 

Anyone who has joined a major incident conference bridge understands the sense of urgency—and the expense. Multiple teams chase clues, minutes feel like hours, and every second of downtime erodes customer experience and brand equity. Network Operations Agents built with Azure AI Foundry offer another path to successful resolutions. As Cristina Moura Rebelo, Head of AI Community and Ecosystem Engagement at MEO, describes it: 

“MEO is transforming into an AI-powered techco, infusing AI into key domain areas and leveraging innovation and technology to create a competitive advantage, business growth, and operational excellency. The first steps made with Azure AI Foundry were key in unlocking the potential of use cases to streamline operations with ChatGOC and the HekaBot, in a scalable, iterative, and agile way, within a very short period of time, delivering outcomes and scaled efficiency to the teams. This is our path to becoming an AI-powered techco.”   

—Cristina Moura Rebelo, Head of AI Community and Ecosystem Engagement, MEO

These AI companions ingest real-time telemetry, topology graphs, historical tickets, and vendor manuals; reason over anomalies; then recommend—or even execute—remediation steps under strict guardrails. Every action is logged, policy checked, and auditable so that safety and compliance are part of the operational flow.

“At a time when pressure to grow has never been greater, data and AI are illuminating the path forward, helping telcos simultaneously achieve three critical goals of growth, efficiency, and security.”

—Praveen Shankar, Executive Vice President I Capgemini 

At TM Forum DTW Ignite 2025, Microsoft will be presenting on how we are transforming telecom operations with agentic AI, and unveiling the Network Operations Agent Framework, a reference architecture and working pilot environment that operators can explore hands-on. The package includes infrastructure-as-code templates, sample knowledgebase content, and step-by-step guidance for integrating Azure AI Foundry with existing telemetry pipelines. With these assets, communications service providers can progress from proof of concept to production in a matter of weeks—and do so with the assurance that every remediation action remains within corporate risk tolerance. 

Unifying data with the Telco Analytics POC Accelerator 

Data is the fuel for agentic AI, yet it often sits stranded across disparate clusters, data marts, and line-of-business applications. The Telco Analytics POC Accelerator removes that friction, deploying a domain specific data estate on Microsoft Fabric complete with service assurance, revenue management, and subscriber 360 schemas; lineage policies aligned to data mesh principles; and guidance to connect your backend data sources. 

Beyond core ingestion pipelines, the accelerator provides predefined tables for service assurance, revenue management, and subscriber 360, alongside sample queries and dashboards that surface quick wins. Built-in sample data allows developers to prototype AI workloads safely—accelerating experimentation while protecting customer privacy.

When operators gain control of their data estate, they monetize faster, govern better, and feed AI models richer context. Microsoft provides the launch pad.

“Fabric let us build on the familiarity, security, and scalability of Azure. It unites data flows, storage, analytics, and machine learning in a single experience.”

—Jerod Ridge, Director of Data Engineering, Lumen

This unified approach empowers operators to achieve real-time insights and smarter decisions, driving business growth and innovation.

Reimagining business support systems for an agentic world 

Business support systems (BSS) are the commercial nerve center of a telco, yet many still feel like 1990s ERP software: dense menus, arcane codes, and labor-intensive workflows. Microsoft’s agentic BSS proof of concept charts a different course. 

At its heart is Microsoft Copilot Studio, which leverages TM Forum Open APIs, the Model Context Protocol, and secure tool registration to let AI agents act on behalf of customer care reps. Consider an agent who says, “Upgrade Alessia’s plan to unlimited data and add a family hotspot.” The AI agent validates entitlements, calculates prorated charges, and triggers fulfilment—no swivel chair required. Subscribers upgrade in the time it takes to sip coffee.

Microsoft is equally optimistic about the potential of an Order Fallout Agent. Up to 3% of orders stall in fragmented fulfilment chains. The agent monitors the queue, diagnoses failure patterns, and either self heals or curates a guided fix. In short, the Order Fallout Agent turns a perennial pain point into an autonomous, closed loop process—freeing care agents to focus on higher value conversations and giving customers the seamless experience they expect.

KPN has extended the use of AI companions to their sales operations with Microsoft 365 Copilot. KPN used Microsoft 365 Copilot to enhance their sales operations, streamlining processes, improving customer engagement, and driving business outcomes.

“From the moment a customer contact becomes an opportunity, we link to that information in Microsoft 365 Copilot for Sales, so we can see all relevant data to prepare for a conversation with the customer,”

—Pierrette de Leeuw-Koumans, Lead Generation Team, KPN

Copilot provides real-time data analysis, predictive insights, and automated workflows, enabling the sales team to focus on strategic activities and deliver personalized experiences. 

These demonstrations illustrate how BSS complexity can melt away, replaced by conversational experiences powered by open APIs and trustworthy automation. The journey is incremental—operators can start with a single fallout queue or upgrade flow and expand outward. 

Momentum stretching from lab to live network 

Innovation without adoption is theatre. Microsoft’s ecosystem partners are translating blueprints into operational gains: 

• Microsoft and leading BSS suppliers are exploring joint proof of concepts that integrate the Telco Analytics POC Accelerator and Observability Operator into next generation revenue assurance workflows.
• PLDT has implemented the Amdocs Customer Engagement Platform, a robust, telco-grade solution jointly engineered by Amdocs and Microsoft elevate customer experience management. “By combining the AI, generative AI, cloud, and deep telecom expertise of Amdocs and Microsoft, PLDT an end-to-end solution that will drive higher agent productivity, operational efficiency, and significantly improve customer loyalty,” said Anthony Goonetilleke, Group President of Technology and Head of Strategy at Amdocs.
• Nokia’s NetGuard Cybersecurity Dome is providing comprehensive security for 5G networks, leveraging AI and automation to detect, manage, and respond to threats in real-time.
• Accenture, Capgemini, TCS, Tech Mahindra, and other global SIs are collaborating with Microsoft on service offerings that accelerate deployment of AI-ready data estates—combining migration expertise, reference architectures, and operator specific best practices. 

The breadth of deployments demonstrates that Microsoft’s approach scales across geographies, regulatory regimes, and network generations. 

Charting the first step 

Building toward autonomous operations seldom begins with a blank slate. The most effective starting point is a business moment that already matters—whether it’s easing congestion at a busy urban cell site or clearing a stubborn order backlog. Instrument that scenario end to end, unify the supporting data, introduce a focused agent, and track the results with discipline. Momentum builds quickly when measurable wins are visible to both engineers and executives. 

Microsoft and its partners stand ready to help, whether through co-innovation blueprints, rapid pilots leveraging the ODA Accelerator for Azure, or structured engagements that blend domain expertise with change management. 

Telecommunications remains, at its core, a human endeavor: engineers who safeguard critical infrastructure, customer care teams who build loyalty, strategists who spot the next market opportunity. Agentic AI amplifies that expertise—it automates repetitive analysis, highlights hidden insights, and executes well understood actions—while judgment, creativity, and empathy stay firmly in human hands. By pairing people with autonomous assistance, operators can scale excellence without sacrificing the personalized touch that defines great service. Microsoft invites the industry to explore that partnership at TM Forum DTW Ignite 2025 and beyond. 

Join the journey 

Learn more by visiting the Microsoft Telecommunications Industry hub, where solution briefs, customer stories, and partner offers provide actionable next steps. Together, the industry can turn aspiration into action and chart the next great wave of telecom innovation. 

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The post Powering the future of telecom: Microsoft brings agentic AI to life at TM Forum DTW appeared first on The Microsoft Cloud Blog.

Build AI agents to drive business processes with Model Context Protocol servers
To provide some context, generative AI is fundamentally reshaping the way organizations work, introducing a new way of interacting with technology—using natural language to simplify and accelerate tasks. This innovation is driving unprecedented productivity gains, streamlining complex processes that once required manual effort and specialized tools. As this technology matures, we’re entering the next phase: the autonomous enterprise, where organizations and people use technology, particularly AI and automation, to operate and adapt in an age of rapid transformation and innovation. Where there once was “an app for that,” there will now be “an agent for that”.

This transformation isn’t just about automation—it’s about people. By putting intelligent agents in the hands of every employee, organizations are empowering individuals to focus on higher-value work, make decisions faster, and drive innovation. Sales teams can deepen customer relationships without being bogged down by administrative tasks. Finance professionals can move from manual reconciliation to strategic forecasting. Marketers can go from idea to execution, and product managers can orchestrate complex workflows with clarity and speed.

The Autonomous Enterprise is the future of business. Business applications will work with agents built by Microsoft and our partners. In this new era, organizations aren’t just streamlining operations, they’re amplifying human potential and accelerating their journey to the autonomous enterprise.

This is why we’re so excited about the Dynamics 365 ERP and CRM MCP servers. These servers help eliminate data and application silos, allowing agents to work seamlessly across processes and enable new autonomous scenarios for improved business functionality and productivity.

Dynamics 365: Agent-ready business applications
Agentic AI is an AI system that can take actions generated by the system, with very limited or even no direct human intervention. Autonomous actions built into agents operating across various business processes, industries, and segments, can make businesses more efficient and responsive. Designed not just to support tasks, but to operate autonomously, AI agents can intelligently orchestrate workflows and make context-aware selections. But how do you create a context-aware agent when data, information, and processes are ever-changing?

MCP standardizes how applications provide context to language models, enabling seamless integration with different data sources and tools. This open standard connects AI assistants and agents to various systems where data resides, such as content repositories, business tools, and development environments. An MCP-compliant agent uses rich contextual information to act efficiently, unlike a non-MCP-compliant agent, which lacks necessary context.

Using the MCP server, makers can easily connect agents to existing knowledge sources and APIs, enabling them to interface directly with Dynamics 365 applications. Actions and knowledge synchronize automatically, facilitating real-time updates and the evolution of functionality. This model significantly simplifies agent development and minimizes ongoing maintenance efforts.

Diagram illustrating how different agents and clients connect to an MCP-compliant server to access data and actions from Dynamics 365 and other business applications.
Central to this innovation is Microsoft Copilot Studio, which provides a standardized protocol for agents to seamlessly interact with Dynamics 365 applications, helping to ensure consistency, reliability, and scalability. Security and governance are also prioritized from the start as Dynamics 365 MCP servers require authentication and enforce authorization. Agents that access Dynamics 365 through the MCP server must authenticate as a valid Dynamics 365 user, helping to ensure the benefits of Entra ID identity protection. This also prevents escalation of privileges, meaning the agent will only be able to perform the MCP actions that they are authorized to do. The MCP servers are also made available to Microsoft Copilot Studio using connector infrastructure. This means they can employ enterprise security and governance controls such as Data Loss Prevention controls and multiple authentication methods. 

For partners and customers, MCP standardization dramatically reduces complexity, accelerates development, and increases time to value.

MCP-compliant agentic AI
At Microsoft, we bring a deep understanding of critical business processes for small and medium business (SMB) as well as large enterprise organizations through our market-leading Dynamics 365 ERP and CRM business solutions—combined with our industry-specific expertise delivered through our Microsoft Cloud for Industry solutions. This combination of experience and expertise uniquely positions us to deliver on the needs of customers across size, business process, industry, or region.

Our newly introduced set of MCP servers enable multiple scenarios across business processes. Below are a few examples of what’s possible with Dynamics 365, Microsoft Cloud for Industry, and our broad ecosystem of partners.

Sales and service
Custom agents and AI assistants can now be connected to Microsoft Dynamics 365 Sales, Microsoft Dynamics 365 Customer Service, and Microsoft Dynamics 365 Business Central applications through MCP servers. Agents can retrieve and update CRM data, create quotes, and complete orders. They can also complete orders, get order/case summaries, and email drafts. These MCP servers open endless possibilities in automating tedious jobs in sales and service functions, irrespective of company size or industry.

For example, telesales representatives can use intelligent assistants, such as Claude, connected to Dynamics 365 MCP servers to prioritize leads, qualify them, generate quotes, and send personalized emails—without needing to switch contexts or rely on complex integrations. And when customers encounter an order issue, service representatives can resolve it quickly by using Dynamics 365 Customer Service data to retrieve/update case information and create replacement orders in real time.

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Supply chain and finance
The AI procurement agent illustrated below efficiently validates purchase requisitions against company policies, existing inventory, and delivery records to identify a suitable supplier that meets the criteria for cost, speed, sustainability, and reliability. It further consolidates multiple items from the same supplier into one purchase order and sends it for purchase. The agent can significantly enhance efficiency in procurement processes, where timely and budget-conscious supply delivery is critical.

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Business Central
For small and medium size businesses, for example, looking to optimize sourcing information and vendor compliance, the custom agent demonstrated here can quickly identify shipments containing materials that require compliance checks. The agent provides guidance on recycling requirements and updated sourcing standards, reads supplier contracts, and suggests next steps like confirming vendor certifications and updating shipment checklists. A solution like this could streamline the compliance process, which can help customers gain a competitive advantage.

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Partners using the MCP server
Our partners play a crucial role in driving innovation and delivering value to customers. We’re dedicated to making Dynamics 365 MCP servers accessible, enabling our customers and partners to develop diverse agent scenarios across industries and business processes, regardless of their business application vendor. Today we’re also announcing the creation of an “AI business applications” coalition with XX and XX as founding members. These organizations along with Microsoft are committed to delivering MCP standard compliant solutions.

With MCP server becoming the standard of the future for agents, partners can use it to more quickly and efficiently orchestrate headless business services in ERP and external systems. It turns simple intent into action, automating procurement for faster, efficient, and resilient supply chain operations. Our ecosystem of partners has started using MCP server for Dynamics 365 to create a host of industry-specific agents.

Avanade, an early adopter of Microsoft 365 Copilot for Sales and a leading Microsoft partner, is excited to use MCP servers for Dynamics 365 to enrich their AI-powered request for proposal (RFP) Insights agent. This agent helps sellers summarize, evaluate, and respond to RFPs using historical Dynamics 365 data, further streamlining proposal generation. While initially for internal use, Avanade is exploring deployment for clients in engineering, construction, and professional services.
Emission AI agent by Fellowmind will use AI and MCP servers for Dynamics 365 to automatically classify and organize purchase transactions to prepare it for Greenhouse gas (GHG) emission accounting purposes by categorizing spend-types (e.g. office supplies, raw materials, travel expenses) through data extraction, classification, algorithms, taxonomy mapping, and real-time feedback and learning. The agent provides support to procurement and environmental, social, and governance (ESG) professionals, helping them streamline their processes and achieve more accurate results.
HSO’s PayFlow Agent improves invoice payment efficiency in accounts payable. Streamlining timely payments and reducing inquiries that require manual intervention leads to faster resolutions and enhanced supplier relationships. Using MCP server for Dynamics ERP MCP, PayFlow processes seller payment inquiries, identifies invoice statuses, matches them against buyer receipts, and retrieves tracking information to notify responsible parties to either remit payment promptly or set an expectation of when payment can be received. 
JourneyTeam is enriching its Strategic Account Manager agent that accesses MCP servers for Dynamics 365 to optimize lead engagement. The agent summarizes historical services and projects, compares lead summaries and interests, compiles recommendations, then, after manual reviews, will initiate next steps by utilizing MCP servers, Microsoft Azure AI Search, and Document Intelligence.
MCA Connect is building a smart sourcing agent that accesses MCP servers for Dynamics 365 to automate requisition processing, supplier assignment, and workflow submission. The MCP servers give the agent access to actions like getting open requisitions, approving vendors, and assigning suppliers based on supplier performance metrics without the need to create new APIs and integrate with Dynamics 365.
Publicis Sapient Hummingbird is building an agent to improve lead management using MCP servers for Dynamics 365 to access data that will streamline the process of managing business-to-business leads. This agent automates lead qualification, scoring, and personalized engagement, accelerating hot leads to quotes faster and nurturing warm leads through a series of targeted emails. This innovative approach enhances efficiency, improves customer experience, and drives higher conversion rates and revenue growth.
RSM is building intelligent, secure, and context-aware agents that accelerate workflows, improve decisions, and expand capabilities by embedding them directly into real-world business processes. These agents, developed using Microsoft Copilot Studio, will access MCP servers for Dynamics 365 to support humanitarian logistics by coordinating critical supply chains, helping to ensure timely delivery of life-saving equipment, and automating procurement tasks.
TTEC is building a post-service upselling agent that accesses MCP servers for Dynamics 365 to prospect for warranty plans after a purchase, turning each sale into an upsell opportunity. The agent will help drive personalized sales and service conversations at scale by using the knowledge, tools, and actions from the MCP server.
As we look ahead, the convergence of intelligent agents, standardized platforms, and deep domain expertise will define the next frontier of business transformation. The ability to harness autonomous capabilities will define tomorrow’s market leaders. Businesses that act now will gain a decisive competitive edge and chart a course toward sustained success. The autonomous enterprise is no longer a vision of the future—it’s here, built with Microsoft and its partner ecosystem.

Join us at Microsoft Build 2025 to explore how MCP servers are transforming Dynamics 365 and the broader Microsoft Cloud–MCP server focused sessions at Microsoft Build 2025.

Let’s shape what’s next, together.

The post The autonomous enterprise: How generative AI is reshaping business applications appeared first on The Microsoft Cloud Blog.

Because of the immense preparation and specialization required, less than 1% of these patients have access to these personalized treatment plans, which have demonstrably improved patient outcomes.  

A recent American Society of Clinical Oncology (ASCO) study highlighted that clinicians spend between 1.5 to 2.5 hours per patient, meticulously reviewing imaging, pathology slides, clinical notes, and genomic data.² And cancer care is just one example of the complex data analysis healthcare requires. Agentic AI holds the potential to reduce administrative friction and further transform care delivery.

The healthcare agent orchestrator is available now in the Azure AI Foundry Agent Catalog. It features pre-configured agents with multi-agent orchestration and open-source customization options that allow developers and researchers to build agents that coordinate multi-disciplinary multimodal healthcare data workflows, such as tumor boards, and streamline deployment into healthcare enterprise productivity tools (such as Microsoft Teams and Word). Modular, general reasoners as well as specialized, multimodal AI agents work together to address tasks that would take hours, with the goal to effectively augment clinician specialists with customized cutting-edge agentic AI.  

By integrating the latest capabilities from across Microsoft, the healthcare agent orchestrator can manage analysis and reasoning over diverse healthcare data types—ranging from imaging (DICOM files) and pathology (whole-slide images) to genomics data and clinical notes from electronic health records (EHRs). Each agent is equipped with advanced AI models from Azure AI Foundry, combining general-purpose reasoning capabilities with healthcare-specific modality models to drive actionable insights grounded in multimodal clinical data.

Key capabilities of healthcare agent orchestrator

• Orchestrating agentic capabilities that can reason over complex EHR data and augment time-consuming tasks like building a chronological patient timeline, determining cancer stage, using specific reference guidelines, reviewing radiology and pathology images, synthesizing current medical literature, referencing treatment guidelines, surfacing relevant clinical trials, and generating customized reports. 

• Providing tools that connect enterprise healthcare data through Microsoft Fabric and the fast healthcare interoperability resources (FHIR) data service.  

• Allowing developers to create, customize, and fine-tune each agent with their own models, tools, instructions, and data sources; test performance in a guided playground experience; and extend agents by setting up using Microsoft Copilot Studio to integrate a Model Context Protocol (MCP) server with sample implementation provided.  

• Ensuring interoperability and integration into existing workflows, including distribution to familiar tools the majority of healthcare organizations already use—Teams, Word, PowerPoint, and Microsoft 365 Copilot—where users can interact with AI agents. 

• Providing robust explainability capabilities in agentic AI-generated outputs, such as grounding responses to the source EHR data—critical for validation, trust, and adoption in high-stakes healthcare environments. 

Researchers and developers at leading cancer care institutions—including Stanford University, Johns Hopkins, Providence Genomics, Mass General Brigham, and the University of Wisconsin School of Medicine and Public Health—are currently exploring the healthcare agent orchestrator to study how agentic AI could deliver value to complex clinical tasks such as cancer care. 

“Stanford Medicine sees 4,000 tumor board patients a year, and our clinicians are already using foundation model generated summaries in tumor board meetings today (via a PHI safe instance of GPT on Azure). The new healthcare agent orchestrator has the power to streamline this existing workflow by reducing fragmentation (saving time by avoiding copy-pasting) and enables surfacing new insights from data elements that were challenging to search, such as trial eligibility criteria, treatment guidelines, and real-world evidence. Stanford Health Care is excited further research the potential of using the healthcare agent orchestrator to build the first generative AI agent solution used in a production setting for real-world care for our cancer patients.”

—Dr. Mike Pfeffer, Chief Information Officer, Stanford Health Care and Stanford School of Medicine

“The vision of the healthcare agent orchestrator is to rapidly surface, summarize, and take action on relevant multimodal medical information for each complex cancer case, so hours of review can become minutes. Collaborating with Microsoft allows us to explore the value of these models for tumor boards and beyond.”

—Dr. Joshua Warner, Radiologist at UW Health and Assistant Professor of Radiology, UW School of Medicine and Public Health

Early development collaborations featured the integration of this multi-agent workflow into Teams chats, where, for example, group chats enabled conversations between multiple human experts and specialized healthcare AI agents connected to specific healthcare data. It demonstrated the promise to significantly enhance efficiency and collaboration among clinical providers. This capability is already bringing clinicians and developers together to build the agentic healthcare applications of the future: the catalyst is the powerful combination of healthcare-specific agents using general reasoning models and multimodal healthcare foundation models alongside the ability to interact directly with custom agents using Teams.  

For example, Johns Hopkins oncologists Dr. Vasan Yegnasubramanian, Dr. Elsa Anagnostou, and Dr. Taxiarchis Botsis and their developer teams in the Johns Hopkins inHealth Precision Medicine program and Molecular Tumor Board are providing their expertise to refine and test the system to ensure it would have high utility if used in their clinical and precision medicine applications.  

Coordinating collaboration of specialized agents

The healthcare agent orchestrator builds upon recent research and releases from Microsoft Research and our collaborators. It coordinates collaboration of specialized agents designed explicitly for complex multidisciplinary clinical workflows like cancer care.  

• The orchestrator leverages Semantic Kernel and Magentic-One to coordinate agents, maintain shared memory, and interact with the human in the loop.  

• The patient history agent leverages Universal Medical Abstraction to organize patient data chronologically.³ Manual work that can take experts over three hours happens in minutes.   

• The radiology agent leverages customer fine-tuned models like CXRRepotGen/MAIRA-2 to analyze radiology images for a second read.⁴  

• The pathology agent demonstrates how to connect to external agents like Paige.ai’s “Alba” pathology agent to address complex queries related to pathology images (available in preview).⁵  

• The cancer staging agent refers to the American Joint Committee on Cancer (AJCC) clinical guidelines to support accurate cancer staging. 

• The clinical guidelines agent refers to the National Comprehensive Cancer Network (NCCN) clinical guidelines to suggest recommended treatment plans.  

• The clinical trials agent identifies eligible clinical trials by matching patient profiles against databases such as ClinicalTrials.gov. This can result in more than double the recall improvement compared to the publicly available Critera2Query baseline.⁶  

• The medical research agent delivers actionable, evidence-based guidance grounded on graph-based knowledge from trusted medical journals.

• The report creation agent automates comprehensive, integrated, richly formatted reporting that serves as a trusted reference during multidisciplinary meetings. 

“As we progress towards the routine use of multi-agent systems, the healthcare agent orchestrator demonstrates the power to simplify the integration of various models and agents with productivity tools that clinicians are already using. The flexible orchestration framework will make it easy for us at Paige to continue to focus on our pathology agents while enabling their integration into the larger cancer care workflow and leverage access to multi-modal data.”

—Razik Yousfi, Chief Executive Officer of Paige.ai

The orchestrator is intentionally open-ended: any approved agent—including third-party—that exposes an API, tool wrapper, or MCP endpoint can be pulled into a Teams conversational thread. Paige.ai is shipping their Alba agent in preview, the first example of an external agent that can be connected to healthcare agent orchestrator. Built on Paige’s foundation-scale vision models and coupled with a conversational large language model (LLM) front-end, Alba delivers real-time conversational digital pathology insights such as tumor grade, morphology, and biomarker status directly from whole-slide images.  

“Providence clinical researchers have begun leveraging advanced AI capabilities provided by the healthcare agent orchestrator to quickly and efficiently parse through large sets of publications, clinical trials and electronic health records. We are excited about its potential to enhance our ability to interpret genomics and match clinical trials in the molecular tumor boards, ultimately benefiting patient care by providing more precise and timely treatment options. Its integration into our workflows also will help streamline communication and collaboration among clinical providers, ensuring that critical clinical information is shared promptly and accurately. As we continue to explore new ways to understand the biology of cancer, its capabilities will be instrumental in driving medical discoveries and advancing cancer treatment.”

—Carlo Bifulco, MD, Chief Medical Officer of Providence Genomics and research faculty at the Earle A. Chiles Research Institute

Empowering developers to accelerate innovations for care teams

As clinical care complexity escalates, the healthcare agent orchestrator empowers developers to confidently navigate the accelerating era of agentic AI, collaborate with clinicians, and democratize precision medicine tools by surfacing these capabilities into existing workflows. The initial framework is designed to study the opportunity of assisting tumor boards. The ultimate vision is to empower healthcare and life science developers to research how agentic AI capabilities could impact clinicians and patients more widely by providing real-time support to multidisciplinary care teams across the healthcare ecosystem. 

Healthcare developers and clinical organizations are invited to explore healthcare agent orchestrator, available through the Azure AI Foundry Agent Catalog. Engage with the next generation of AI-powered healthcare agents today.  

¹ Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries, CA: A Cancer Journal for Clinicians, April 4, 2024.

² Using an Adapted Tumor Board Evaluation Tool for Quality Assessment of a Thoracic Multidisciplinary Cancer Conference: A Pilot Study, JCO Clinical Cancer Informatics, October 5, 2023.

³ Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale, February 2, 2025

⁴ MAIRA-2: Grounded Radiology Report Generation, June 6, 2024

⁵ Nature Medicine, A foundation model for clinical-grade computational pathology and rare cancers detection, July 22, 2024

⁶ Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology, August 4, 2023

Disclaimer

Healthcare agent orchestrator is intended for research and development use. It is not designed or intended to be deployed in clinical settings as-is nor is it intended for use in the diagnosis or treatment of any health or medical condition, and its performance for such purposes has not been established. You bear sole responsibility and liability for any use of healthcare agent orchestrator, including verification of outputs and incorporation into any product or service intended for a medical purpose or to inform clinical decision-making, compliance with applicable healthcare laws and regulations, and obtaining any necessary clearances or approvals. 

The post Developing next-generation cancer care management with multi-agent orchestration appeared first on The Microsoft Cloud Blog.

As we witnessed in many leadership dialogues at CERAWeek 2025, AI adoption is taking place at an accelerated speed in the energy sector. The role of AI in meeting rising energy demand is multifaceted and transformative. AI can optimize operations, reduce  energy consumption, enhance grid capacity and reliability, and support renewable energy integration. It can also address energy security and sustainability efforts, such as carbon capture and storage, and methane management and mitigation. AI’s potential in the energy sector is robust. Critically, all these innovations are underpinned by the industry’s collective goal to mitigate environmental impact and continue to move towards a more sustainable future, while meeting the growing demand for energy.   

Microsoft is committed to helping to drive progress in the energy industry through technological innovation—working to empower the energy workforce, optimize operational efficiency and safety, advance net zero commitments, and grow sustainable, AI-powered businesses.  

CERAWeek 2025 takeaways 

In March 2025, we attended CERAWeek 2025, one of the most influential energy gatherings of the year, which provides a platform for over 8,000 attendees to connect, share and discuss insights, and explore where the industry is headed.  

This year, a few key takeaways from the event were: 

• AI is changing the game across industries, and energy is no exception.
  Jason Zander, Executive Vice President for Strategic Missions and Technologies at Microsoft, spoke in the session “Will AI Revolutionize the Energy Sector?” and discussed the ways in which AI is transforming the energy sector with innovative solutions that boost energy efficiency, optimize production, and integrate renewable resources. One of the recent breakthroughs that Jason highlighted is Microsoft’s Majorana 1, the world’s first Quantum Processing Unit (QPU) powered by a Topological Core, designed to scale to a million qubits on a single chip. This advancement has practical applications to help solve some of the most difficult global challenges. It brings the potential to revolutionize the energy industry with possibilities such as developing self-healing materials, enhancing safety, creating catalysts to break down plastics, and significantly advancing sustainability through more recyclable and reusable materials. 

• Powerful collaboration with industry-leading, strategic partners is key to growth and innovation.
  Several of our partners; Accenture, Cognite, Honeywell, Kongsberg Digital, Schneider Electric, and SLB showcased their industry-leading, real-world solutions in the Microsoft booth. These innovative AI-powered solutions illustrate the immense opportunity to transform the energy industry and empower the energy workforce with modern technology.
  
  One standout demo was Schneider Electric’s new One Digital Grid Platform, an AI-powered system that helps improve the reliability and efficiency of power grids. Using Microsoft Azure, this platform allows different software solutions to work together, helping utilities modernize their grids and provide cleaner, more affordable energy at a lower overall cost. Schneider Electric is leveraging Microsoft solutions to improve grid reliability, and is collaborating with Itron to do so. Solutions like these, built with strategic partners, address the need for a modern, digital grid to provide energy to all who need it.   

Transform and optimize resilient energy systems with AI 

AI’s potential in the energy industry is transformative, with the capability to optimize operations, strengthen security, and advance decarbonization. To provide the energy that the world will require, the energy industry needs intelligent solutions that address these needs with faster insights and increased productivity.  

The impact of AI solutions is directly correlated to the amount of data companies have at their disposal. For energy companies that may have a fractured data estate spanning diverse environments and proprietary data formats, establishing a unified data foundation is a difficult task. This is why Microsoft is committed to equipping industry leaders with powerful, enterprise platforms like the Microsoft Cloud to accelerate this transformation. And with Microsoft Fabric, data, AI, security, and applications are integrated to enable real-time data processing and AI-powered insights so that companies can make informed decisions more quickly. Microsoft Azure Data Manager for Energy is also an important piece of this energy data journey, and critical to carbon storage and planning. Most powerfully, it can create a repository for all of an organization’s data in a single location. Furthermore, by adopting our adaptive cloud approach and unifying siloed teams, distributed sites, and sprawling systems into a single operation, organizations can increase security, improve data modeling, and leverage cloud-native and AI technologies across hybrid, multicloud, edge, and Internet of Things (IoT) environments. 

From there, custom reports and insights can be generated with Microsoft 365 Copilot. These cutting-edge solutions are designed to help energy companies harness the full potential of their data with AI—enabling seamless integration, real-time insights, and predictive analytics to help drive efficiency and innovation across the sector.  

One vast opportunity for the energy sector when it comes to using AI is its power to help decarbonize the energy value chain. It’s clear that decarbonization is a critical step towards achieving a sustainable and net-zero future—involving reducing carbon emissions across all stages of energy production, distribution, and consumption. By integrating renewable energy sources and improving energy efficiency through adopting innovative technologies like AI, the energy sector has the potential to significantly lower its carbon footprint more quickly than was possible without the efficiency gains from AI. The recent International Energy Agency report, “Energy and AI” shares several potential examples of cost and energy savings in power plant operations and end-use sectors, such as manufacturing and transportation. For example, AI in transportation can enhance vehicle operation and management, potentially cutting energy consumption—and therefore emissions—up to 20%.² 

AI’s potential in enhancing security is immense, offering both vast implications and opportunities. Using AI to enhance security is already making a difference for companies, with a recent study of Copilot users showing that using Microsoft Security Copilot reduced mean time to resolution by 30%.³ Harnessing the power of AI to bolster security in the energy industry, we recently introduced six new Microsoft Security Copilot agents. These agents represent the power of AI to respond to an increasingly high volume of security threats that energy organizations face today. They are designed to autonomously manage high-volume security tasks, helping to provide robust protection for critical energy infrastructure. By leveraging advanced threat intelligence and machine learning, these agents can swiftly detect, investigate, and respond to security incidents, helping to mitigate risks associated with cyberattacks.  

Demonstrating the power of collaboration in AI innovation, new partner-developed agents will also be available in Security Copilot. These solutions offer industry-specific solutions, such as the ability to understand sector-specific compliance needs. This approach enhances operational efficiency and will help to strengthen the overall security posture for energy companies that adopt agents, allowing IT and operations teams to focus on their core operations while maintaining a resilient defense against ever-evolving threats.  

Our customers like Chevron are also already seeing the impact of AI in their operations, integrating real-time data from IoT devices, optimizing equipment and bandwidth costs, and accelerating decision-making with AI at the edge. 

Collaborating with Chevron on facilities of the future with Azure IoT Operations  

With its Facilities and Operations of the Future initiative, Chevron is reimagining the monitoring of its physical operations to support remote and autonomous operations through enhanced capabilities and real-time access to data. This includes ongoing efforts to use technology to unlock access to connected data across a vast network of IoT devices—ultimately for greater speed to decisions. Chevron worked closely with Microsoft to deploy Azure IoT Operations, enabled by Azure Arc. This edge-to-cloud data plane facilitates data capture from various devices like Wi-Fi cameras, thermal cameras, sensors, robots, and drones at the edge before sending it to the cloud.  Chevron chose Azure for its flexible infrastructure to control data and scale globally, unifying sites and systems into one AI-assisted control pane. Using AI at the edge, where sensors are located at the equipment, helps optimize equipment and bandwidth costs and accelerates speed to insights.  

Learn more about energy and resources solutions with Microsoft  

As we look to the future, AI is becoming an increasingly important force in the energy industry—enabling companies to achieve greater safety and efficiency, help secure their operations, and increase sustainability. Key to this growth and innovation is powerful collaboration with our strategic partners and secure, resilient solutions that meet the industry’s robust needs. Microsoft remains dedicated to supporting this journey, providing the tools and technologies needed to thrive in an ever-evolving energy landscape. 

• Explore CERAWeek 2025 highlights.
• Visit Microsoft for energy and resources.
• Learn more about Microsoft Security for Enterprise.
• Read about Microsoft responsible AI.

Microsoft for energy and resources

Drive innovation to achieve net zero

Explore solutions

¹ Global Energy Perspective 2024, McKinsey, September 2024. 

² Energy and AI, AI for energy optimization and innovation.  

³ Agentic AI and Microsoft Security Copilot: Revolutionizing cybersecurity, March 2025.

The post Empower a data and AI-powered, sustainable energy future with Microsoft appeared first on The Microsoft Cloud Blog.

Agentic AI as the hero 

At MWC 2025, Microsoft spotlighted how agentic AI is driving real industry transformation—turning innovation into impact for telecoms. Throughout the event, telecom leaders cited agentic AI as a game-changer, exploring new revenue streams, and automating complex tasks. From hyper-personalized marketing campaigns to proactive network management, these applications are already delivering measurable business value. AI is no longer a pilot or proof of concept; it’s a proven technology, a necessity, for operators to deliver transformative customer experiences at-scale. 

Attendees witnessed demos and theater sessions that showed how AI can assist in the automation of complex tasks, anticipate network bottlenecks, and enhance customer experiences at-scale. Industry leaders consistently emphasized that building trust in AI is paramount, especially as AI becomes more important in supporting decisions previously handled by humans. Microsoft’s approach—rooted in transparency, security, responsible AI and governance—stood out. Microsoft highlighted how integrating Azure’s robust compliance features offers operators and their customers peace of mind, showing that trust and AI innovation are complementary. 

Booming booth and demo showcase 

The Microsoft booth welcomed more than 11,500 unique visitors—interested in learning how Microsoft’s AI portfolio helps drive innovation. The energy was high around our experiential demos, bringing to life real-world applications. Attendees learned how Microsoft Fabric and Azure analytics unifies data to optimize network operations, and powers immersive applications. These showcases highlighted the practical benefits of modern AI-powered technologies. 

Packed theater sessions 

The energy in Microsoft’s theater sessions was electric—overflow crowds packed the aisles to hear how telecom operators are igniting innovation and growth with AI sessions like “Korea Telecom Accelerates AI Adoption” and “AI Ignites Innovation and Growth in Telecom,” where speakers spotlighted how agile customers and partners, such as Accenture, Nokia, and Amdocs, are taking decisive leaps forward in their AI journeys. Each of these sessions echoed a consistent message: whether it’s network modernization or harnessing data, customer and partner momentum is accelerating digital transformation with real business results.

Announcements and customer success stories 

In addition to the success stories shared onstage, Microsoft unveiled news and announcements at MWC 2025 (see my LinkedIn post for details) that reinforce our commitment to accelerating telecom innovation. Microsoft introduced extended agentic AI capabilities for proactively detecting and self-healing network anomalies, demonstrating how operators can achieve near-zero downtime while reducing operational expenses. Another focus was low-code expansion across Microsoft Dynamics 365 and Microsoft Power Platform, empowering telecoms to rapidly build and deploy AI-powered workflows—everything from personalized marketing funnels to simplified customer onboarding experiences. Microsoft also introduced two AI-powered sales agents—Sales Agent and Sales Chat—within Microsoft 365 Copilot to help sales teams close deals more efficiently by automating lead management, customer engagement, and sales tasks. ​ 

Microsoft showcased deepened partnerships with industry leaders like Amdocs and Nokia, geared toward modernizing network infrastructure and elevating customer touchpoints. These collaborations highlight Microsoft’s efforts with partners to tackle the sector’s biggest challenges, such as automating network rollouts, augmenting cybersecurity with AI defenses, and simplifying data monetization. Together, these new announcements reinforce how AI—and especially agentic AI—will continue to transform telecom, enabling telecoms to deliver faster, smarter, and more secure connectivity.

Attendee excitement also came in the form of customer success stories. Telecoms spoke about how agentic AI and other Microsoft AI solutions have already begun reshaping their business: 

• Vodafone described how adopting AI-powered network maintenance cut outages and boosted satisfaction scores.
• KT provided a real-time case study on scaling AI from niche pilot projects to a core tenet of corporate strategy. 

Each story illustrated tangible business value, resonating with attendees seeking proven outcomes.

Partner ecosystem and shared success 

One of the most energizing aspects of MWC 2025 was connecting with Microsoft’s dynamic ecosystem of partners. At this year’s customer and partner reception, conversations buzzed with ideas on how to unlock greater value by combining Microsoft’s cloud and AI capabilities with solutions from trusted partners like Amdocs, Accenture, Nokia, and more. 

The partner spotlight was on innovation—from co-developed analytics dashboards that simplify 5G rollouts to integrated AI modules that accelerate service provisioning. These collaborations underscore how Microsoft’s partnerships with leading telecom Software Development Companies (SDCs) and System Integrators (SIs) are delivering tangible business outcomes. Startups were also a key part of the story. Microsoft for Startups highlighted a new wave of innovative startup SDCs that are helping telecom customers improve customer experience, data insights, and operational efficiency. 

By bringing together Microsoft’s technological depth with the domain expertise of partners, the company is addressing some of the telecom industry’s most pressing concerns—reducing operational overhead, maximizing customer lifetime value, and accelerating innovation. This spirit of community sets the tone for continued innovation.  

What is next 

The momentum behind AI adoption in telecom is accelerating. According to a recent McKinsey report, the focus on scaling AI from one-off pilots to enterprise-wide initiatives will only intensify as data volumes grow and networks become more complex. Microsoft stands ready to help telecoms navigate the next phase through delivery of telecom-specific AI innovations that drive business results: 

• Telco data model in Microsoft Fabric 
  Provides a unified data framework enabling telecoms to run advanced agentic AI workflows across service assurance, customer care, and revenue management.
• Autonomous networks and self-healing operations 
  Leveraging Azure OpenAI Service and the Microsoft generative AI and agentic AI platform, Microsoft envisions proactive, self-healing networks that detect, diagnose, and remediate issues in real time—reducing truck rolls, lowering OPEX, and raising customer satisfaction.
• Open and intelligent Radio Access Network (RAN) optimization 
  Now open source, Project Janus enables dynamic service models and real-time telemetry in Open Radio Access Network (O-RAN) environments—empowering telecoms to build intelligent, AI-optimized RAN architectures using Microsoft’s agentic AI framework to enhance performance, flexibility, and innovation.
• Hyper-personalized customer experiences 
  AI agents within Dynamics 365 Customer Insights, Microsoft 365 Copilot and Amdocs Customer Engagement Platform can unify behavioral and usage data to deliver precise, timely engagements. Telecoms can reduce churn and boost average revenue per user (ARPU) by offering the right products and solutions.
• Expanding revenue beyond connectivity 
  With the embedding of AI-powered interactions directly into customer and developer ecosystems, telecoms can open new business models—such as vertical-specific APIs and AI marketplaces that monetize network APIs, network analytics and agentic automation. 

Microsoft is deeply committed to partnering with telecom operators to co-create the future of connectivity. By aligning agentic AI capabilities with the industry’s most urgent challenges, Microsoft helps telecoms unlock new value—securely, ethically, and at scale. Through strategic collaborations with partners like Nokia, Amdocs, and leading SDCs and SIs, Microsoft delivers scalable, trusted solutions that position telecoms as pioneers in the AI-powered era. 

Until next time, Barcelona 

The transformation of the telecom industry is accelerating—driven by bold investments in AI, deepened partnerships, and a shared commitment to innovation. As the industry moves beyond MWC 2025, one thing is clear: telecom operators are poised to lead in an era defined by intelligent networks, data-driven agility, and customer-centric growth. 

With Microsoft’s agentic AI capabilities, trusted cloud infrastructure, and collaborative partner ecosystem, telecoms can unlock new efficiencies, monetize new services, and deliver seamless experiences that generate lasting business value.

Learn more about how Microsoft is powering the next wave of telecom transformation with AI and agentic automation by visiting our Microsoft for telecommunications Industry Page.

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