Maritime trade accounts for more than 80% of global trade by volume, making ports a foundational pillar of the global economy, according to UN Trade & Development (UNCTAD).¹ As trade volumes grow and supply chains become more interconnected, ports are asked to do more than move goods efficiently. They must coordinate increasingly complex operations, integrate data across fragmented systems, and enable safer, more predictable decision-making across a diverse ecosystem of stakeholders.

Meeting these demands requires a fundamental shift in how ports modernize their operating models to meet these demands, moving from siloed, reactive operations toward integrated, data‑driven, and intelligently orchestrated systems.

From Port 4.0 to Port 5.0: Capability over complexity

Port 4.0—widely used across the industry as shorthand for digitalized, connected port operations—laid the foundations through shared data, connected infrastructure, and more informed decision-making.

In our Ports of the Future framework, Port 5.0 is how we envision the next stage of operational capability—where ports orchestrate flows of goods, data, energy, and trust through integrated platforms and governed intelligence.

At a high level, Port 5.0 is about:

• Moving from visibility to coordinated action
• Embedding intelligence into daily decisions, with people in control
• Designing collaboration, governance, and security from the outset

This evolution is shaped by interconnected building blocks—from AI-supported control towers and connected inland corridors, to energy aware operations, trusted data collaboration, advanced optimization, immersive digital twins, and all hazards infrastructure resilience.

A new wave of enabling technologies

In the Ports of the Future framework, Port 5.0 is defined by a set of core operational capabilities. What has changed in the last 12–18 months is the maturity of technologies that now make these capabilities practical to deploy at scale.

• AI-supported operations
  AI systems can now assist with multistep operational workflows—monitoring conditions, proposing replans, and surfacing high impact exceptions for human decisionmakers—moving control towers from visibility toward orchestration, while remaining governed.
• Confidential computing for sensitive collaboration
  Hardware- based trusted environments enable organizations to process sensitive data while maintaining strong protections, supporting cross agency analytics and collaboration without compromising established data handling policies.
• Advanced optimization approaches
  Quantum-inspired and heuristic optimization methods help ports address complex scheduling and routing challenges—berths, yards, rail paths, labor, and inspections—particularly under disruption, when suboptimal decisions compound quickly.
• Digital twins and simulation
  Immersive digital twins increasingly serve as shared operational environments, integrating real-time data with simulation to support planning, training, and coordinated decision-making. AI-based simulation contributed to improved vessel punctuality and measurable operational gains, according to a case study of Busan Port,² illustrating the potential of these approaches when deployed thoughtfully.
• Security and governance by design
  As ports become data hubs, cybersecurity, identity management, and access controls are increasingly embedded into platform architecture from the outset.

Together, these capabilities help ports move from reactive operations to coordinated, system level performance—while keeping people in control and governance at the center.

Develop core operational capabilities

The Ports of the Future whitepaper explores these building blocks in depth, with real world examples and a pragmatic 24–36 month roadmap that helps ports move from vision to execution.

Explore Microsoft for public finance to help reignite the economy and drive financial accountability with public finance technology solutions.

¹ Shipping data: UNCTAD releases new seaborne trade statistics 

² In August container ship punctuality at 65.3% — World Ports Org 

The post Ports of the future: Building a framework for the modern port appeared first on The Microsoft Cloud Blog.

Yet despite broad cloud adoption, migration and modernization remain complex. Legacy architectures, fragmented environments, and persistent skills gaps continue to slow progress, pushing organizations to find ways to migrate faster while minimizing operational risk. 

The IDC study highlights agentic AI as a critical unlock. These intelligent systems automate assessments, orchestrate migration and modernization efforts, and optimize operations across hybrid environments—helping organizations shift from periodic, manual initiatives to continuous, adaptive modernization. This momentum is driving unprecedented growth, with IDC forecasting the public cloud services market will reach USD1.9 trillion by 2029. 

While migration frameworks may be horizontal, their real-world impact is industry-specific. Healthcare, financial services, and manufacturing each face unique constraints shaped by regulation, operational risk, and mission-critical systems. 

In this blog, we explore the key migration and modernization challenges across these three industries—healthcare, manufacturing, and financial services—through real customer stories that highlight the tangible impact cloud adoption is delivering today.

Healthcare: Modernizing securely while powering next-generation clinical experiences

Healthcare faces the toughest modernization headwinds: strict regulations (HIPAA/HITECH, HITRUST), fragmented clinical data across electronic health records (EHRs) and imaging systems, aging on-premises infrastructure resulting in high Capex, and heightened exposure to ransomware.¹ Clinical environments also demand extremely low latency and high reliability.

The IDC study notes that these constraints slow modernization—but accelerate the need for it, as organizations push to scale telehealth, imaging workloads, genomics pipelines, and AI-powered clinical workflows.¹ 

What healthcare organizations need, according to the IDC study: 

• Secure, compliant integration across EHRs, picture archiving and communication systems (PACS), genomics systems, and Internet of Things (IoT) medical devices.¹
• Elastic compute for high-throughput imaging and genomics. 
• Stronger disaster recovery and recovery time performance.¹
• Ambient documentation and AI-supported diagnostics.
• Secure clinician collaboration and modern patient digital front doors.

Customer spotlight: Franciscan Health

Facing aging infrastructure and disaster recovery risks, Franciscan adopted a pragmatic workload placement strategy—moving its Epic EHR to Microsoft Azure.

The results included: 

• $45 million in savings over five years after migrating Epic to Azure.
• 90% faster disaster recovery compared to the prior environment.
• Around a 30-minute failover, reduced from hours.
• $10–$12 million per day in potential downtime risk avoided.

Learn more about Franciscan Health’s journey to migrate its Epic EHR to Azure.

Healthcare’s modernization mandate is clear: reduce operational risk, meet regulatory demands, and harness cloud AI to improve patient outcomes. 

Financial services: Enabling real-time intelligence and automated compliance

Financial institutions operate in one of the most regulated environments, including the payment card industry data security standard (PCI DSS), the Sarbanes-Oxley Act (SOX), the Gramm-Leach-Bliley Act (GLBA), Basel capital frameworks, and know your customer (KYC) and anti-money laundering (AML) requirements, and rely heavily on legacy mainframes that are difficult to modernize. Today, regulatory pressure is intensifying further as new frameworks such as the EU’s Digital Operational Resilience Act (DORA) and the EU AI Act raise the bar for operational resilience, third-party risk management, model transparency, and ongoing compliance monitoring. Under DORA, financial services firms must demonstrate continuous information and communication technology (ICT) risk management, advanced incident reporting, and resilience testing across critical systems and cloud service providers. Meanwhile, the EU AI Act introduces governance requirements for high-risk AI systems, including explainability, data lineage, human oversight, and auditability—with direct implications for fraud models, credit scoring, and customer decisioning platforms.

IDC interviews highlight accelerating demand for real-time risk analytics, fraud detection, digital onboarding, and infrastructure elasticity to support peak activity—capabilities that are increasingly mandated, not optional.¹

Key challenges the IDC study identifies: 

• Strict data residency, model risk governance, explainability, and eDiscovery requirements.¹
• Heightened expectations for operational resilience, cyber defense, and third-party risk oversight.
• Legacy systems and common business-oriented language (COBOL)-based batch processes resistant to change.
• Rapidly evolving regulatory mandates requiring continuous compliance rather than point-in-time audits.

Cloud—especially especially platform as a service (PaaS) and managed services—helps financial institutions shift from static, batch-driven compliance to continuous controls and real-time observability. By reducing batch windows from hours to minutes, modern cloud platforms enable real-time insights, automated evidence collection, resilient architectures, and policy-driven compliance workflows aligned with DORA and AI governance requirements.¹ Learn more about how Microsoft can help financial institutions navigate these requirements. 

Customer spotlight: Crediclub

To accelerate product innovation and meet expectations from Mexico’s national banking and securities commission (CNBV), Mexican fintech Crediclub modernized its databases to a serverless platform as a service (PaaS) architecture and adopted microservices.¹

The impact:

• Uptime improved from around 80% to 99.5%.
• 90% reduction in network latency through Multiprotocol Label Switching (MPLS) and dark fiber.
• Rapid deployment of new financial products via Kubernetes and DevSecOps.

For financial institutions, modernization is no longer just about efficiency—it is foundational to resilience, trustworthy AI, and regulatory compliance at scale. 

Manufacturing: Unifying IT and OT for predictive, data-driven industrial operations

Manufacturers operate in one of the most complex operating environments—defined by legacy and proprietary operational technology (OT) protocols, historically air-gapped manufacturing execution systems (MES) and supervisory control and data acquisition (SCADA) systems, and globally distributed supply chains. Stringent low-latency requirements for safety-critical systems, intermittent connectivity at the edge, and the need to protect intellectual property further compound the challenge. The ability to modernize and unify these environments—without compromising safety, reliability, or performance—represents a critical inflection point for industrial transformation.

Unique modernization challenges according to the IDC study:

• Ultra-low latency requirements for safety-critical operations.
• Massive telemetry ingestion and time-series analytics at scale.
• Operational complexity across global, distributed supply chains.
• Secure protection of intellectual property across edge and cloud environments.

Opportunities unlocked by cloud:

• Predictive maintenance with IoT ingestion.¹ 
• Reduced unplanned downtime and improved overall equipment effectiveness (OEE).
• Digital twins for plants, lines, and products.
• Computer vision for real-time quality and safety. 
• High-performance computing (HPC) simulations for engineering and design. 
• Standardized, global data models.

Customer spotlight: ASTEC Industries

ASTEC unified fragmented systems across its rock to road value chain—from aggregate processing through asphalt production and paving—by adopting Azure, modernizing to timeseries databases, and building a universal connectivity platform using Azure IoT Hub, Azure Events Hub, and Power BI.¹

The results:

• Realtime operational visibility across fleets.
• Predictive maintenance for reducing downtime.
• New digital services supported by connected equipment.

Manufacturing’s modernization imperative: unify OT and IT, scale real-time intelligence, and enable global efficiency. 

Microsoft’s approach: Continuous, intelligent, collaborative modernization 

Microsoft’s strategy is grounded in a simple principle: modernization should be continuous, intelligent, and collaborative. The IDC study emphasizes that successful enterprises adopt a balanced, multipath migration strategy, blending rehost, replatform, refactor, and software as a service (SaaS) substitution based on workload criticality.¹

Microsoft enables this approach through a comprehensive set of tools and offerings, including Azure Copilot and GitHub Copilot. Agentic automation enables:

• Discovery and dependency mapping.
• Security assessment and 6R recommendations.
• Application refactoring, code remediation, and modernization. 

Azure Migrate provides unified discovery, assessment, migration execution, and modernization services. Azure Accelerate complements this with a coordinated framework that includes:

• Guided deployments through Cloud Accelerate Factory.¹ 
• Funding and Azure credits for planning, pilot, and rollout. 
• Expert partners and tailored skilling programs.

The IDC study concludes that organizations using Microsoft Azure for migration and modernization achieve lower operational costs, improved resiliency, faster modernization timelines, and stronger security postures—especially in regulated industries.¹

Looking ahead: Agentic modernization as the foundation for AI-ready enterprises

Across all industries, IDC’s findings are consistent: agentic AI is emerging as the new force multiplier for modernization, enabling organizations to keep pace with rising complexity, regulatory demands, and competitive pressure. 

Healthcare, financial services, and manufacturing each face unique constraints—but cloud modernization remains the foundation for innovation, operational excellence, and enterprise AI. 

Microsoft’s approach gives organizations the unified automation, intelligence, and tooling they need to modernize securely and at scale. 

• Explore how Azure Copilot accelerates cloud migration.
• Discover GitHub Copilot for app modernization.
• See how Azure Accelerate supports transformation.

¹ IDC White Paper, Cloud Migration and Modernization Strategies for Healthcare, Financial Services, and Manufacturing, February 2026.

The post Modernizing regulated industries with cloud and agentic AI 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.

We’re thrilled to announce the public preview of the Product Change Management agent template—an AI-powered solution that transforms how manufacturers manage the process of change across equipment, products, processes, and more. Built on Microsoft Copilot Studio, the agent automates workflows and connects systems, helping teams cut approval times from weeks to days, reduce errors, and bring innovations to market, faster.

Learn how Copilot Studio can help build and customize agents that work for your operations.  

Reenergizing change management with AI

Engineering change management (ECM) is how manufacturers manage change without causing production chaos. Changes move through a complex, controlled path with requests reviewed, approved, and rolled out to multiple stakeholders and systems. Whether responding to market shifts, regulatory updates, or quality improvements, manufacturers initiate millions of change requests each year.

Today, ECM is slow. While highly collaborative, the process is easily bogged down by siloed information, manual steps, and disconnected processes. When it breaks down, costs from scrap, stoppages, and delayed product launches pile up.

The Product Change Management agent template addresses these pain points by infusing intelligence, automation, and orchestration into this otherwise manual process. The agent provides a managed solution that can be tailored to specific business needs—accelerating deployment while ensuring consistency and governance. Connecting people, data, and systems together with Microsoft AI, it simplifies execution—cutting approval times to days, improving uptime, and ensuring change traceability.

Powering AI change management end-to-end

The Product Change Management agent template is an AI-powered orchestrator, built in Copilot Studio. It autonomously manages engineering change processes through a series of specialized sub-agents, collaborating with your team to ensure every change is executed efficiently and accurately. Using Microsoft 365 Copilot and Microsoft Teams, the agent shifts manual tasks to focused reviews and refinement—delivering faster, safer changes with fewer errors and less review turmoil, while maintaining compliance and alignment. maintaining compliance and alignment.

Some key capabilities set it apart:

• Automated workflow orchestration. Accelerate approvals by coordinating the entire change process, from request to closure, autonomously. Embedded into Microsoft 365 Copilot and Teams, the agent initiates impact analysis, routes approvals, and updates records—keeping stakeholders informed.
• System of record synchronization. Keep engineering and operations systems aligned. The agent ensures updates are consistently reflected across product lifecycle management (PLM) and enterprise resource planning (ERP) platforms, eliminating rework and maintaining alignment from design through delivery.
• Collaborative stakeholder engagement. Simplify communication across engineering, quality, and operations with natural language interfaces and intelligent routing. This ensures that the right people are engaged at the right time, reducing bottlenecks and accelerating approvals.
• Data-driven impact analysis. Evaluate proposed changes across inventory, suppliers, and production. The agent surfaces real-time insights to guide decision-making and flag potential risks early—empowering teams to act.
• Built-in compliance and traceability. Document and audit changes at every step. The agent enforces governance policies, tracks decisions, and supports regulatory compliance without adding complexity.

In short, product change management lays the agentic foundation for manufacturing digital threads—enabling agility, transparency, and reliability for every stakeholder.

Transforming change management at Coca-Cola Beverages Africa

Coca-Cola Beverages Africa (CCBA) is the eighth largest authorized Coca-Cola bottler in the world by revenue, and the largest on the continent—operating in 14 countries. Serving more than 800,000 customers, CCBA accounts for 40% of all Coca-Cola ready-to-drink beverages sold in Africa through a host of international and local brands.

With thousands of stock keeping units (SKUs), multiple packaging formats, and a relentless focus on sustainability, CCBA runs one of the most complex beverage supply chains in Africa. Agility is critical especially when managing formulation and packaging changes that ripple across multiple production lines, inventory systems, and financial models.

Every year, CCBA makes more than 1,000 changes to its bottle molds alone, often driven by material availability or sustainability initiatives. Historically, these changes relied on manual workflows: engineers drafting requests, planners emailing spreadsheets, and multiple handoffs across departments. This process was slow, error-prone, and risky. A single misalignment could mean production downtime, inaccurate cost data, or compliance gaps. The Product Change Management agent template from Microsoft is transforming this process.

Acting as a digital orchestrator, the agent brings intelligence, speed, and reliability to the CCBA change lifecycle. Here’s how:

• Smart initiation. When a planner or engineer triggers a change, such as switching a supplier or updating a packaging component, the agent immediately identifies all affected products and plants. It auto-drafts the request, applies the standard template, and fills in known details like part numbers and descriptions—eliminating repetitive manual work.
• Automated routing. The agent ensures the request moves to the right reviewers in the correct sequence, removing guesswork and delays. Notifications flow through familiar tools like Teams and Outlook, alerting stakeholders when action is required.
• Instant system updates. Once approvals are complete, the agent updates Microsoft Dynamics 365 in real time, syncing bill-of-material data. It confirms changes immediately, rather than days of manual checks.

The Product Change Management agent is streamlining equipment management across CCBA’s capital assets and products, enabling faster identification of impact areas and responsible individuals, and improving operational efficiency

—Joshua Motsuenyane, Chief Information Officer, CCBA

While this strategic collaboration is still new, CCBA is already seeing results. Actions that once took days of back-and-forth now happen in hours or less. Product change management also represents a major milestone in its Frontier Firm journey—making change management a focus across one of Africa’s most dynamic manufacturing networks.

Creating the future of change management in manufacturing, together with partners

AI-powered change management is now imperative. As changes proliferate across more assets and systems, manufacturers need governed, AI-guided workflows to maintain speed and quality. Discrete manufacturers—building complex products from computers to cars—feel it the most: disconnected systems and manual handoffs slow adoption, raise error rates, and suppress productivity. PTC and Microsoft are changing that.

Together, we’re building an agentic architecture that bridges operations and engineering systems, enabling faster decisions with enterprise visibility. Enabled by technologies such as model context protocol (MCP), native PLM agents in Windchill and ERP agents in Dynamics 365 interoperate to surface problem reports, collate data from multiple systems, and drive automation in PLM workflows such as change impact analysis, where data governance rules are established, ensuring AI agents work in the right context and within the right controls.

Ready to simplify change and accelerate execution?

Product Change Management agent template

Join the public preview

In combining Microsoft for Manufacturing with expertise from partners, we can deliver better, more comprehensive industry solutions. As we expand this ecosystem, manufacturers will gain even broader interoperability, deeper insights, and more resiliency across their value chain.

Shaping the manufacturing Frontier

With the Product Change Management agent template, manufacturers gain a trusted technology partner in navigating every engineering change. Part of a broader vision to enable intelligent digital treads across manufacturing, product change management is about empowering teams to innovate with confidence, backed by data and AI automation.

Industrial AI can accelerate product design and engineering outcomes. Learn how with our latest Signals Report.

The post Accelerate innovation with AI: Introducing the Product Change Management agent template appeared first on The Microsoft Cloud Blog.

What are OSS and BSS?

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Modernizing OSS and BSS: From reactive to agentic AI

OSS and BSS have long been the operational and commercial backbone of telecoms. Generally speaking, OSS manages network operations—provisioning, inventory, and fault detection—while BSS handles transactional functions like billing and customer management. Traditionally, these environments have remained fragmented, hindering a unified view spanning the customer, the network, and the business.

Thanks to advances in data management, AI and generative AI, these systems can now move beyond reactive troubleshooting to automated, predictive, and—even more significantly—agentic solutions, in which AI autonomously orchestrates tasks end-to-end. Whether it’s proactively responding to service degradations or autonomously managing resolving customer issues, agentic AI promises unprecedented cost mitigation, efficiency, and agility. 

However, effectively harnessing the proactive benefits of agentic AI requires telecom providers to establish a unified source of data truth through seamless data accessibility, rather than trying to consolidate all data onto a single platform. By enabling unified access to network, operational, and business data through a singular data catalog—such as Microsoft Fabric, which utilizes shortcuts and mirroring—telecoms ensure AI-powered insights are accurate and comprehensive. Without cohesive access to high-quality data, AI-powered insights risk becoming fragmented or misleading, limiting the transformative potential of autonomous decision-making and potentially leading to inaccurate, risky decisions. 

The critical importance of data accessibility and cohesion is exemplified by AT&T’s migration to Azure Databricks, highlighting tangible benefits: 

1. Unified data access and operational visibility: Instead of traditional consolidation, unified data access through platforms like Microsoft Fabric provides comprehensive context, enabling AI algorithms to generate precise, actionable insights. AT&T’s migration to Azure Databricks illustrates how improving accessibility to quality data across silos empowers technical staff, enhances analytical capabilities, and improves decision-making accuracy—dramatically reducing the risk of overlooking critical dependencies or making suboptimal decisions.
2. It enables closed-loop intelligence: Agentic AI extends beyond merely analyzing data; it proactively acts in near real-time. A cohesive data access approach, like the one implemented by AT&T, facilitates rapid anomaly detection and automated corrective actions within network and revenue systems. This closed-loop intelligence is crucial for next-generation AIOps, enabling seamless and automated responses across the entire telecom infrastructure. 
3. It accelerates new revenue opportunities: Providing cohesive access to operational and business data creates agile, scalable monetization pathways. AT&T’s adoption of Azure Databricks accelerated its ability to launch new services by automating complex data processing and analytics tasks. Similarly, telecoms leveraging unified data access solutions can rapidly provision and monetize services such as customized 5G and 6G experiences or on-demand network slicing—shifting from manual processes to dynamic, programmable offerings.

A modern, agentic, cloud-native OSS and BSS environment built on public cloud principles doesn’t just serve the operator; it also creates a frictionless platform for third-party and ecosystem partners to plug in. Whether it’s Internet of Things (IoT) device vendors, over-the-top content providers, or enterprise service integrators, cloud-native OSS with open APIs allows rapid partner onboarding and co-creation. In turn, operators can easily expand their portfolio with new revenue streams—bolstering the business to business to everything (B2B2X) model—while still maintaining centralized oversight and robust security at scale. 

Agentic AI in action: From insight to autonomous operations

Faster time-to-market for new services

Traditionally, launching a new offering in telecom could take upward of 50 weeks, hindered by lengthy approvals, hardware provisioning, and siloed systems. In a cloud-native environment, operators can test, iterate, and deploy new products—like on-demand network slicing or advanced IoT bundles—in days or even hours. This speed is a game changer for operators transitioning from ‘telcos’ to ‘tech-cos,’ where continuous experimentation and rapid scaling of successful pilots are essential to staying competitive. Coupled with agentic AI that autonomously manages tasks, cloud-based OSS and BSS ensures you don’t just move faster—you move smarter. Leading telecoms are already laying the groundwork for agentic AI by adopting:

• Predictive analytics for network health: For instance, AI-powered anomaly detection can preempt equipment failures, but true autonomy means the system itself orders the replacement part, dispatches a technician, and reroutes traffic in the meantime—all driven by integrated data across OSS and field service management. 
• Proactive policy and billing: In a unified data environment, usage spikes or new IoT device activations can trigger dynamic policy updates in real time—while simultaneously adjusting billing parameters. This end-to-end automation requires that the network layer (OSS) and the revenue layer (BSS) share data instantly and accurately. 

Why run OSS on the public cloud?

As service catalogs explode and customer demands evolve more rapidly, operators need elastic, scalable infrastructure to shorten time-to-market and accommodate fluctuating loads. Public cloud delivers on-demand compute and storage, reducing capital expenses and enabling rapid innovation with built-in AI and machine learning services. Moreover, the global reach and reliability of platforms such as Microsoft Azure allow telecoms to replicate, secure, and manage their OSS across regions far more easily than traditional on-premises setups. By shifting OSS to a cloud-native model, operators can pivot from lengthy, monolithic upgrade cycles to nimble, iterative releases—critical for accelerating 5G and 6G services, IoT offerings, and B2B2X monetization scenarios.

Self-optimizing networks and beyond

While self-optimizing networks (SON) currently manages aspects of radio access networks, next-generation AI solutions extend self-optimization to the entire telecom domain. Microsoft Project Janus is an early example of how real-time AI-powered telemetry can proactively detect network anomalies, predict service degradations, and dynamically optimize network resources—laying the foundation for fully autonomous network operations. Telefónica España, for example, leveraged Azure AI and machine learning to achieve significant improvements in network performance and efficiency. By incorporating AI and big data technologies, Telefónica España is developing more intelligent networks capable of self-optimization and adaptation. This intelligence allows for a reduction in time to market for new solutions, enabling the company to swiftly implement innovations that enhance network performance and customer satisfaction. With advanced generative AI, AI-powered instructions can autonomously fine-tune network configurations, adapt capacity, and realign resources based on live traffic patterns. This orchestration is feasible only when AI has an enterprise-wide view of network, business, and operational data.

Embracing open standards and ecosystem collaboration

Just as critical as data consolidation is ensuring interoperability and flexibility. Many telecoms are turning to TM Forum’s Open APIs and adopting Open Digital Architecture (ODA) principles. These frameworks reduce vendor lock-in, streamline data exchange, and allow AI solutions to operate across heterogeneous environments. 

For example, TM Forum’s collaboration with Microsoft has accelerated the adoption of carrier-grade, open-source ODA canvases. By aligning Azure’s robust cloud capabilities with ODA standards, operators are now better equipped to innovate rapidly, simplify complex integrations, and significantly reduce the operational hurdles associated with legacy systems.

Microsoft plays a pivotal role in supporting these open standards, providing a cloud-native, modular approach fully aligned with ODA. A practical illustration is Sure Telecom’s adoption of Azure, where leveraging Microsoft’s open API framework allowed them to consolidate disparate data sources and achieve enhanced customer insights and operational efficiency. Microsoft’s platform delivers out-of-the-box integrations and open APIs that empower operators to harness AI-powered analytics and intelligent automation workflows, minimizing friction traditionally encountered during legacy system modernization. 

Achieving scale with cloud-native AI

A robust, cloud-native foundation is essential for scaling AI across complex telecommunication environments. Containerized microservices, DevOps practices, and serverless compute reduce operational overhead, allowing teams to focus on innovating rather than managing infrastructure. Within such environments: 

• Azure AI services streamlines the training, deployment, and monitoring of AI models across OSS and BSS workloads. 
• Microsoft Fabric fosters seamless data ingestion, orchestration, and transformation—critical for building that unified data estate necessary for agentic AI. 

By converging data and AI workloads in the cloud, telecoms can more quickly test and deploy innovative services that leverage advanced analytics for both operational efficiency and new revenue streams.

In addition to the operational and technical upsides, running on public cloud offers a more predictable and flexible cost model. Instead of large capital expenditures tied to peak capacity, operators pay only for what they consume. This shift in economics not only aligns with sporadic traffic spikes—common in modern usage-based and event-driven architectures—but also frees up budget to invest in strategic AI initiatives. By reducing hardware overhead, maintenance, and upgrade costs, telecoms can reinvest in higher-value activities such as AI-powered product innovation and partner ecosystem growth. 

Microsoft’s unique value: Building a telecom foundation for agentic AI

Microsoft combines a partner-centric approach with end-to-end technology solutions—bringing actionable capabilities to telecoms that want to realize AI-powered OSS and BSS at scale.

Key value streams include: 

1. Telecom-specific cloud and data services: Telecom-optimized solutions from Microsoft and its partners help unify network, operational, and customer data into a single source of truth. 
2. First-party AI agents: Microsoft’s growing suite of autonomous agents, such as those integrated within Dynamics 365, automate complex business processes—enhancing efficiency and decision-making across various telecom operations. 
3. Alignment with industry standards: Microsoft’s active support for TM Forum and ODA ensures an open, interoperable environment. Operators can adopt AI without overhauling existing infrastructure or incurring vendor lock-in. 
4. Security and compliance: As AI-powered automations become central to business functions, Microsoft provides enterprise-grade security and governance—critical for protecting sensitive network and customer data. 
5. Partner ecosystem: Collaborations with leading vendors—such as Amdocs, CSG, Blue Planet, ServiceNow, Netcracker, and system integrators—create end-to-end workflows that accelerate modernization and reduce complexity. Through these partnerships, Microsoft’s AI tools seamlessly integrate with telecom-specific applications.

Positioning for revenue impact and the autonomous future

When OSS and BSS data is unified and AI-powered processes take over routine tasks, telecoms can prioritize innovation that directly impacts the bottom line. Whether rolling out new network services or offering real-time network slicing for enterprise customers, the ability to act on consolidated data in an autonomous fashion sets operators apart in a hyper-competitive market.

Short-term gains include faster time-to-market for new services, reduced operational costs, and improved customer experiences. Longer term, fully autonomous, self-healing networks that optimize themselves and require minimal manual intervention, unlock new revenue streams through AI-powered insights. Project Janus is already demonstrating this shift—showcasing how AI-powered network intelligence moves beyond predictive analytics into autonomous, self-optimizing operations that reduce operational overhead and ensure peak performance with minimal human intervention.

Project Janus demonstrates how AI-powered network intelligence can move beyond predictive analytics into autonomous, self-optimizing networks—reducing operational overhead and ensuring peak performance with minimal human intervention. 

Ready to transform your operations?

The industry is moving beyond point solutions toward a future where agentic AI and unified data estates power autonomous operations. For telecom leaders, now is the time to ensure OSS and BSS modernization strategies align with open standards, prioritize data consolidation, and prepare for the emergence of fully autonomous networks.

Microsoft and its partners are here to guide you on this journey—from building robust cloud-native foundations and consolidating your data estate to delivering intelligent, revenue-focused transformations across OSS and BSS. By embracing this approach today, you’ll ensure your operations not only keep pace with evolving market demands but lead the next era of telecommunications innovation. 

Learn more about our AI and generative AI solutions for telecommunications and discover how we can help you lay the groundwork for the agentic AI revolution—starting with your most strategic asset: your data.

The post The transformative impact of AI and generative AI on OSS and BSS in telecommunications appeared first on The Microsoft Cloud Blog.

To help answer these questions, Microsoft leaders and industry partners will showcase the very latest AI innovation for manufacturers designed to help address today’s most critical challenges.

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AI agents will transform manufacturing in 2025 and beyond

Moving forward, four transformative trends will set the pace of growth and success in the evolving manufacturing landscape:

• Improving supply chain operations
• Driving operational excellence with operational technology data from siloed sources
• Delivering great customer experience
• Increasing energy efficiency and employee productivity

At the Microsoft expo booth, manufacturers will learn how they can achieve these trends by using agents across critical business processes and workflows with Microsoft Dynamics 365 autonomous ERP solutions.

Improving supply chain operations with AI agents

Manufacturers face increasing supply chain challenges, from fluctuating customer demand to geopolitical uncertainties that can pressure organizations to restructure supply chains or reshore operations to unaffected regions. It’s imperative to have the agility to adapt to rapid demand shifts while operating profitably and keeping costs in check.

AI agents can play a crucial role in manufacturing operations, autonomously monitoring processes for potential disruptions, with the ability to proactively mitigate potential issues before they’re serious issues.

The Supplier Communications Agent in Dynamics 365 autonomously manages interactions with vendors and suppliers to help ensure on-time delivery of purchase orders helping to avoid downstream delays to customers. The agent provides visibility into the supplier’s supply chain and allows teams to spend more time improving supplier relationships and negotiating better contracts, rather than firefighting shortages.

Lifetime Products—a global manufacturer of products ranging from basketball hoops to picnic tables, sheds, and kayaks—depends on Microsoft Dynamics 365 Supply Chain Management to optimize operational capabilities. In addition to handling logistics and supply chain management more effectively, the manufacturer is implementing AI agents to “rebalance” its knowledge workforce to do more with same and be more efficient rather than reduce labor.

“One of our biggest learnings has been to let the autonomous agent run its own calculations. You’ll get a more comprehensive, better result.”

—Sinahi Lopez, Global IT Functional Manager at Lifetime Products

The company is now preparing to deploy the Supplier Communications Agent in Dynamics 365, to autonomously communicate with suppliers to proactively mitigate order delays and supply chain disruptions.

Based on study with IDC, $3.5 million in annual inventory-related cost savings using Dynamics 365, optimizing working capital​.¹

Achieving operational excellence with operational technology data from various silos

To stay competitive, manufacturers need to optimize operations by reducing costs, minimizing downtime, improving agility, and ensuring efficient production. This requires data-driven decision making that takes advantage of the industrial Internet of Things (IoT), AI-driven automation, integrated data clouds, and edge-to-cloud architectures to enable real-time insights, predictive maintenance, and quality control. Microsoft Dynamics 365 includes applications to manage finance, supply chain, sales, and customer relationships, designed to unify business data, improve efficiency, and simplify decision-making. The applications work seamlessly with Microsoft 365, which enhances productivity and collaboration with leading applications like Word, Excel, and Microsoft Teams, while Azure provides cloud infrastructure and IoT capabilities.

A key innovation is the AI agent, powered by Microsoft Copilot Studio, that automates tasks and streamlines workflows, securely grounded on data sourced from various systems by using Microsoft Dataverse as a central hub. Microsoft Fabric enhances analytics, helping businesses turn data into insights. For customization, Microsoft Power Platform offers low-code tools to build apps and automate processes, while Microsoft AppSource provides industry-specific solutions from Microsoft partners.

Together, these technologies create a connected ecosystem, reducing data silos and enabling businesses to operate more efficiently. With everything working seamlessly, organizations can focus on growth, innovation, and smarter decision-making.

Enerjisa Üretim, Türkiye’s largest private electricity generation company, replaced its legacy asset management system with Dynamics 365—a modern, user-friendly solution that provides end-to-end lifecycle management of all 312,500 assets across 29 power plants.

The organization is also transforming operations with Dynamics 365 and Azure, achieving efficiency, cost reduction, and workforce empowerment. Integration of asset management, IoT, and Microsoft Azure Digital Twins provides real-time insights for predictive maintenance. Unified systems improve data consistency, streamline workflows, and enhance collaboration, setting new standards for operational excellence in energy.

“Our equipment data is the key to operational efficiency. The Asset Management [capabilities] in Dynamics 365 extends the lifespan of critical infrastructure. By leveraging real-time data and advanced analytics, we can predict equipment failures before they happen.”

—Alper Serçe, Deputy General Manager, Enerjisa Üretim

Dynamics 365 integrates seamlessly with Enerjisa Üretim’s external systems like SAP, streamlining operations and enhancing efficiency. Real-time inventory updates from SAP into Dynamics 365 helps ensures that technicians have the right materials. And integration with HRweb and Yüklenici Entegre Sistemi (YES) optimizes resource allocation, matching skills and qualifications to work orders.

Based on study with IDC, 85% reduction in unplanned asset downtime using Dynamics 365, ensuring smoother operations​.¹

Deliver better customer experiences

Manufacturers are facing intense global competition, making customer experience essential to maintain relevance. To differentiate and retain customer trust, they must reconsider traditional business models and explore new revenue streams like product-as-a-service and aftermarket services.

Dynamics 365 assists manufacturers in transitioning to a product-as-a-service (PaaS) model by integrating IoT, AI, automation, and flexible financial frameworks.

• Dynamics 365 Supply Chain Management and Microsoft Azure IoT enable real-time product performance monitoring and predictive maintenance, reducing downtime, helping to ensure timely spare parts delivery and streamlined logistics, which are important for service-based models.
• Microsoft Dynamics 365 Field Service uses AI and IoT data for a predictive service model, enhancing efficiency and optimizing service contracts to improve customer satisfaction.
• Microsoft Dynamics 365 Finance supports flexible pricing, pay-per-use, and subscription models, converting products into ongoing services.

Hobart Corporation, a provider of commercial food equipment, needed to modernize its field operations to better support nearly 400,000 customers across the United States and Canada and solve inefficiencies in service delivery.

By adopting Microsoft Dynamics 365 Customer Service and Field Service, Hobart standardized processes, improved dispatch accuracy, and provided field technicians with mobile access to real-time inventory and customer data. This transformation enabled quicker response times, improved first-time fix rates, and better parts availability. The solution also facilitated predictive maintenance, ensuring proactive issue resolution before failures occurred.

As a result, Hobart significantly enhanced operational efficiency, customer satisfaction, and workforce productivity, reinforcing its reputation for high-quality service.

Organizations facing similar issues can also use the recently announced Scheduling Operations Agent (SOA) for Dynamics 365 Field Service, now in preview. This AI agent creates optimized schedules for technicians, even as conditions change throughout the workday. Whether it’s traffic delays, double bookings, or last-minute cancellations, the SOA helps ensure that schedules remain efficient.

The SOA uses advanced algorithms to address common scheduling challenges. By considering factors such as technician skill sets, territories, and promised time windows, the SOA maximizes technician utilization and prioritizes work orders effectively. This enhances productivity and helps ensure that customer commitments are met accurately.

Based on study with IDC, 40% faster order and product delivery times using Dynamics 365, increasing customer satisfaction.¹

Operating sustainably by driving energy and employee efficiencies

Manufacturers are under increasing pressure to improve energy efficiency and reduce their carbon footprint while maintaining productivity. By integrating Microsoft Dynamics 365 ERP solutions and Sustainability Manager in Microsoft Cloud for Sustainability, manufacturers can gain real-time visibility, AI-driven insights, and automated tracking to drive sustainability at scale.

Dynamics 365 ERP collects energy consumption data from IoT sensors, smart meters, and production systems, offering a comprehensive view of energy usage across facilities. This data flows into Microsoft Sustainability Manager, where AI-powered analytics identify inefficiencies, benchmark performance, and recommend optimizations. Manufacturers can track carbon emissions in real time, ensuring they meet sustainability targets.

With predictive analytics and AI-driven workload balancing, manufacturers can optimize machine usage, reduce energy waste, and lower costs. Additionally, optimized supply chain operations help minimize environmental impact through smarter logistics and material sourcing.

Camfil, a leading manufacturer of premium clean air filtration solutions, is using Dynamics 365 to enhance sustainability and profitability. By implementing Dynamics 365 with a standardized data model, Camfil has harmonized its processes across more than 30 production facilities and nearly 6,000 employees.

The integration of Dynamics 365 Finance, Dynamics 365 Supply Chain Management, Dynamics 365 Project Operations, Dynamics 365 Customer Service, and Dynamics 365 Sales has improved operations such as ordering, manufacturing, warehousing, shipping, and invoicing. This harmonization enabled by Dynamics 365 has led to better resource utilization, improved energy efficiency, a more connected and collaborative culture, and enhanced customer satisfaction through continuous innovation in air filtration systems—all contributing to a more sustainable and cost-effective manufacturing operation.

A well-empowered workforce can better manage inventory, demand planning, and supplier interactions, reducing waste and inefficiencies.

Based on study with IDC, 27% more manufacturing processes automated, 20% improvement of productivity across supply chain, procurement, and inventory management teams by using Dynamics 365 AI-powered ERP solutions.¹

Future-proof your manufacturing operations in 2025 

AI-powered solutions for ERP and service systems are more than a technological upgrade. They’re a strategic imperative for manufacturers aiming to improve the supply chain, drive operational excellence on the factory floor, deliver great customer experience, and operate sustainably and efficiently.

If you’re registered for Hannover Messe, we invite you to visit the Microsoft booth (#G06, hall 17) and join Sameer Verma, Microsoft’s GM, Dynamics 365 AI ERP, to learn how Dynamics 365 drives manufacturing excellence with AI agents. The session will take place on Monday, March 31, 2025, at 12 PM Central European Time (UTC +1).

Also, continue to visit the Dynamics 365 blog to learn more about how Dynamics 365 and Microsoft Power Platform are helping retailers reimagine the road ahead; and feel free to contact us to learn more about the Dynamics 365 AI-powered ERP system solutions. 

Source

¹ IDC White Paper, sponsored by Microsoft, The Business Value of Microsoft Dynamics 365 for Manufacturers, doc #US53226425

The post The future of manufacturing with Microsoft Dynamics 365 is here—are you ready? appeared first on The Microsoft Cloud Blog.

Agility helps retail and consumer goods supply chains:

• Quickly switch suppliers, develop more flexible sourcing strategies, and mitigate disruptions from potential tariffs¹
• Adapt product offerings and pricing strategies to combat the lingering effects of inflation
• Adopt more real-time demand forecasting tools and flexible warehousing solutions to keep up with shopping patterns
• Augment human labor with automation to improve productivity and address labor shortages

Retail and consumer goods organizations that develop greater agility will catapult themselves forward by using insights from their supply chains as a critical enabler.

Nonetheless, many retailers’ supply chains struggle with agility because warehouse data is often still on-premises—and that’s holding them back from the latest technologies. Because data is central to all business processes, it’s data that either fuels or inhibits supply chain growth. Reliance on on-premises data and legacy systems likely inhibits supply chain growth because it:

• Causes latency that slows decision-making since leaders lack access to real-time data and often rely on outdated snapshots of old data
• Prevents visibility and collaboration since data is often fragmented and siloed
• Limits scale because systems can’t efficiently process increased data volumes and fluctuating demand
• Impedes flexibility when systems can’t adapt quickly to shifting market conditions and demand
• Impairs adoption of new technologies and processes when existing platforms aren’t adaptable

The warehouse is the ideal starting place for increased digitalization because investments made at the warehouse create value that extends to other parts of the supply chain and enterprise.

Digitalizing the warehouse enables operational excellence and innovation through:

• Data-driven decision-making through real-time insights that help managers make more informed decisions and get teams unified around the same information so retailers can get ahead of demand.
• Reduced operating costs related to warehousing operations through enhanced efficiencies gained by automation and robotics—and improved warehouse throughput through layout optimization, labor efficiencies, and automation. This includes reduced time and labor required for tasks such as picking, packing, and shipping.
• Seamless integration throughout supply chain systems, such as enterprise resource planning (ERP) and warehouse management systems. It also sets the stage for other powerful capabilities, such as intelligent stores.
• More scalability, making it easier for retailers to handle seasonal demand fluctuations or rapid growth without disrupting operations.

Agility helps supply chain leaders drive operational excellence and innovation. Nothing enables that level of agility like the cloud. Here are three compelling reasons to start digitizing your warehouse today with Microsoft and its partner ecosystem.

1. Help warehouse managers drive operational excellence with agentic AI

The role of the warehouse manager is pivotal in the supply chain ecosystem, yet warehouse managers are overloaded with information from multiple sources, making it hard to parse what’s relevant and useful.

Blue Yonder’s warehouse manager AI agent offers an easy-to-digest, interactive report designed to help warehouse managers stay up to date with the most important data and information. The agent delivers those key insights when they’re needed, helping ensure operational excellence every day.

Instead of sifting through hundreds of charts and dashboards, pages and pages of report analysis, or piecing together fragments of information from their teams, warehouse managers get a simplified view of what’s happening, what caused the issue, and what to do about it.

It’s like having a personal analyst working alongside the warehouse manager who knows all about their role, their company, and warehouse. That partnership helps the manager move much more quickly from information overwhelm to clear, decisive action.

Blue Yonder expects more developments coming soon, including more data highlights, summaries, and suggested actions, as well as an expanding list of tasks the agents can perform with human guidance.

2. Optimize warehouse design, planning, and operations with simulation

Today’s customers expect retailers to have what they want and deliver it fast to their store or home. Warehouses are critical nodes in the supply chain where optimizations can improve growth and profitability. From receiving shipments to sorting, picking, and packaging, every step of warehouse operations is being modernized with AI that analyzes changes in the physical world.

Simulating facility designs and layouts, processes, and discrete events in fulfillment and distribution centers helps retail and consumer goods enterprises make more informed and faster decisions without the need to physically install systems to evaluate use cases. Simulation also lets enterprises create and use synthetic data to orchestrate between manual labor and automation systems applying AI, machine learning, robotics, sensor technology, management systems, cloud platforms, and data analytics. How can warehouses achieve operational excellence at every step of the orchestration?

NVIDIA Omniverse is a platform for developing and deploying physical AI and simulation applications for industrial digitalization. Developers use Universal Scene Description (OpenUSD) to build solutions on a platform that enables warehouse scale, digital twins, and simulations to optimize layouts and achieve operational efficiencies. These digital twins also serve as virtual training grounds for autonomous systems and robotic fleets that increasingly operate inside these facilities.

Today, leading retailers and consumer goods companies use applications and solutions built on NVIDIA Omniverse to design and simulate greenfield and brownfield warehouses from scratch, establishing an optimal layout and process flow all in a physically accurate digital space. They can evaluate technologies like robotic shelving systems, robotic grid-based storage, or vertical lift modules (VLM) for high-density storage.

Solutions built on Omniverse let retailers integrate data from different enterprise and industrial systems to create, test, and measure design, process, and operational twins before spending precious capital or stepping foot in the building. For greenfield sites, this means a fully optimized virtual version of the entire design before construction begins. For brownfield sites, retailers can seamlessly integrate new automation technologies with existing systems, ensuring the entire warehouse achieves its operational benchmarks and performs as one cohesive unit.

Applications developed with the Omniverse platform also allow supply chain leaders to understand the impact of discreet events that impact efficiency so they can make decisions that improve key performance metrics like warehouse throughput without the risk of costly physical trials.

In the fast-paced world of commerce, time to value is everything. But platform technologies are never the end-all, be-all. That’s why collaborating with the right partners and experts is crucial for retail and consumer goods enterprises. By bringing together integration partners like Accenture to simplify the development and implementation of end-to-end advanced automation and robotics solutions and services, Microsoft’s powerful cloud solutions, and NVIDIA’s cutting-edge accelerated computing, AI, and simulation platforms, retailers can accelerate warehouse transformation and realize value faster than ever.

3. Boost productivity and collaboration with robotics-enabled automation and intelligent orchestration

Warehouse managers have traditionally relied on manual processes and human labor to keep their operations running smoothly. But labor shortages and rising operational costs are making it increasingly difficult to maintain efficiency and productivity. Additionally, the complexity of managing inventory and ensuring timely order fulfillment often leads to bottlenecks and errors.

Advancements in robotics can help supply chains augment staffing, improve employee safety, and drive warehouse productivity. New capabilities are emerging every day and startups are the ones embracing these new capabilities.

Intelligent orchestration and sortation with Unbox Robotics

The last mile can be a significant chunk of the cost in getting the supply chain right. Unbox Robotics is one of hundreds of startups Microsoft works with to deliver retail supply chain solutions. Unbox Robotics can help automate the last mile process by using robots and swarm intelligence that mimics what a swarm of bees or ants do by carrying goods from one place to another. These robots pick items, sort them, and put them in one lot lightning fast so they can easily be picked up and delivered. And because robots can work around the clock, Unbox Robotics can help retailers offset labor challenges with “always on” reliability.

Smart redistributions with YDISTRI—a new era in inventory optimization

Even the best demand forecasting systems can’t fully prevent real-time overstock and understock issues. YDISTRI doesn’t compete with these systems—it complements them by providing an AI-based reactive inventory redistribution solution. For example, in a supermarket chain, YDISTRI analyzes sales patterns, local demand, and product turnover to identify overstocked items—such as specialty foods or seasonal goods—and moves them to stores where they will sell faster at full price, reducing markdowns and waste.

By weighing transfer costs against the risk of discounts or write-offs, YDISTRI helps retailers maximize revenue from existing stock, improving inventory efficiency without relying on heavy markdowns.

Bend the curve on innovation by digitalizing your warehouse in 2025

Improving agility gives retailers the ability to future-proof their business, flex and scale their operations, and be more responsive and adaptive to consumer demands. Supply chain leaders can achieve operational excellence and catapult themselves forward with generative AI, digital twins, and robotics.

Microsoft partners with Blue Yonder, an organization that provides complete solutions across the entire supply chain, and with hundreds of today’s most innovative startups to complement a retailer’s existing technologies. Start using your supply chain as a business enabler by digitalizing your warehouse in 2025 and gain more agility for years to come.

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• Microsoft’s responsible AI principles

• Enhancing supply chain efficiency in the retail and consumer goods industry with agentic systems

• Delivering your supply chain copilot: Prioritizing areas of ROI

• Delivering your supply chain copilot: Getting started on ideation

¹ “Tariffs: What Retailers Need to Know,” Bain & Company, January 2025.

The post AI-powered retail: 3 reasons to start digitalizing your warehouse in 2025 appeared first on The Microsoft Cloud Blog.

The Department of Veterans Affairs DEAN’s (Discovery, Education, and Affiliate Networks) Office in partnership with the National Artificial Intelligence Institute (NAII), SimLEARN, and the Office of Primary Care, conducted a 120-Day AI Tech Sprint competition that began in January 2024. More than 150 companies participated. At the awards ceremony held in Washington D.C on May 21, 2024, DAX Copilot, the latest AI technology from Microsoft, was chosen as the top solution in the ambient clinical encounter category.

We are honored and thrilled to be chosen as the winner of this Tech Sprint. DAX Copilot, already in use across hundreds of healthcare organizations, builds on the years of proven success delivering ambient documentation and workflow capabilities to improve clinician-patient experiences and reduce administrative burdens.

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Reducing administrative burden and associated burnout

Supporting our frontline healthcare workers by providing cutting edge AI technology to reduce administrative burden and associated burnout was the theme of the Tech Sprint, which consisted of three phases. More than 150 companies entered the Tech Sprint, which was whittled down over the three-phase competition to a final five. DAX Copilot was selected as the winning solution. Microsoft will donate the monetary prize to the National Veterans Legal Services Program (NVLSP), a national non-profit organization that works to ensure that veterans and active-duty personnel receive the benefits they are entitled to due to disabilities resulting from their military service.

Automating clinical documentation and workflows

The primary objective of Track One of the Tech Sprint was to showcase an AI-enabled solution that can securely capture patient-clinician conversations ambiently and extract key information to create clinical documentation automatically. It also needed to have a high degree of security, compliant with Veterans Affairs (VA) privacy and security standards, to protect patient data.

Advanced desired capabilities included those that follow a responsible AI framework and automate and assist clinical workflows such as populating existing heterogenous note templates, generating an after-visit patient summary, and referral letters.

Exceeding expectations

Not only can DAX Copilot securely record encounters ambiently and automatically convert them into clinical documentation in seconds, but it also has a robust set of AI-powered capabilities to assist clinicians with their everyday tasks beyond note creation. It’s based on the Dragon Medical platform, an award-winning, Federal Risk and Authorization Management Program (FedRAMP) authorized speech recognition solution with hundreds of features relied on by more than 20,000 clinicians across the VA network and 600,000 users worldwide. And it’s all built on Microsoft Azure, the most trusted and comprehensive cloud, governed by a responsible AI framework, and core set of principles.

The post DAX Copilot—AI-powered solution wins AI Tech Sprint to reduce clinician burnout appeared first on The Microsoft Cloud Blog.

In a world where market complexity and disruptions are common, retail organizations must learn to navigate and be ready to adapt to new challenges. Retailers seek to get ahead of supply chain disruptions, embrace workforce transformation, and address economic uncertainties—all in the context of a “new era of AI” that has emerged with generative AI, where technology serves a pivotal role in future-proofing businesses.

Microsoft Cloud for Retail accelerates business growth by providing retail-specific capabilities across the Microsoft Cloud portfolio to seamlessly connect your customers, people, and data. Together with Blue Yonder, Microsoft’s generative AI-powered scenarios are enabling retail organizations to create agile, resilient, and sustainable supply chains by connecting data across their ecosystems to identify issues and optimize performance. Microsoft and Blue Yonder have been at the forefront of a cognitive revolution of supply chain innovation, laying the foundation for a truly intelligent, autonomous supply chain, with a predictive and generative AI copilot, delivering faster and better decision making.

Retail and consumer goods companies are turning to AI, including generative AI, predictive AI, machine learning, and automation, to respond faster and in an agile and scalable way to a myriad of problems. These emerging technologies reimagine the user experience, unlock productivity, and drive greater efficiencies in a way that was previously not possible. Harnessing AI, machine learning, and generative AI in this way affords greater visibility and insights into the next best actions. When integrated into retail planning and execution workflows, generative AI can transform the way teams respond to evolving market dynamics, continuously adjusting decision-making based on demand and supply signals, while considering exponentially more scenarios in a fraction of the time it would take the team to compile.

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Gain efficiency and profitable growth with the power of AI and machine learning for retailers

In the evolving landscape of supply chain management, the integration of AI is becoming a popular strategy for enhancing efficiency and innovation. While the journey of implementing AI and machine learning technologies can be challenging, with some initiatives possibly not fully achieving their expected outcomes, this doesn’t detract from the potential value AI brings to the table. The effectiveness of AI doesn’t solely rely on its application to existing processes but rather on a transformative approach towards how these technologies are embedded within the organizational fabric. Embracing AI is about more than just technological adoption; it’s about reshaping the foundational elements of workflows and processes to truly leverage the power of predictive insights, automation, and data-driven recommendations.

Traditional, linear supply chains, business units and even data currently exist in silos, perpetuated by the inherently disjointed nature of how supply chains were originally constructed: every function contained within its respective walls. These silos can lead to slower decisions and hinder collaboration throughout the organization. Each functional team lacks visibility beyond their sphere of influence, and often doesn’t understand the impact of their actions on other business areas. When AI and machine learning are applied in this environment, quick decisions can conflict, and optimized key performance indicators (KPIs) can cancel each other out. It is therefore imperative that organizations centralize their data, standardized into a single data model that is ready for AI and machine learning consumption, and connect their workflows to reap the full benefits of AI and machine learning. Once connected, businesses can leverage AI to orchestrate the entire supply chain, allowing visibility and collaboration between all functional teams, all driving toward common goals: to fuel profitable growth and delight the end customer.

Unlocking the power of AI

There’s a lot of hype around generative AI right now, and for good reason. Its inherent creativity, speed, and automation have been viewed as a potential way to replace labor, but we would caution that view is an incomplete view of what this emerging technology can do and how it can be applied. Rather than seeing the technology as competing with human workers, generative AI offers an unprecedented opportunity to enhance industry expertise and experience, unlocking levels of productivity.  

Imagine: instead of having to search multiple systems to find the answer to your question, you have a dedicated assistant that can access the far reaches of your company’s system-wide knowledge, and in a moment return any answer to any question—in simple, everyday terms. Think about the impact this would have on your team’s productivity, quality of performance, and overall satisfaction. Or how this could dramatically accelerate the onboarding of new team members. The opportunities are endless, and as more use cases are discovered, generative AI can and should be used to supplement or redeploy the efforts of human workers in ways that empower and enable teams, not supplant the workforce. While these technologies cut down on manual processes, saving time and effort while providing robust recommendations and thorough data, the human touch will always be necessary to some degree. 

Adapting to new information and updates is vital to controlling your supply chain and making the best choices, and AI holds the key to greatly improved shopper experiences. By using automation and AI, stores can stay ahead of customer demand and keep their shelves stocked with the right product at the right time, and at the right price. Applying predictive analytics to internal and external data can help identify potential disruptions before they happen, empowering teams to proactively respond before it impacts end customers. And bringing holistic data from your warehouse, logistics network, staffing plans and more together with market conditions, seasonality, weather, and traffic patterns can provide a 360-degree view of how shoppers think, act, and what they will experience as consumers.  

By partnering with Blue Yonder and their strategic services team, an iconic fashion retailer will be able to align sales demand forecasting and replenishment by using Cognitive Merchandise Financial Planning throughout their supply chain to improve agility and efficiency. After introducing Cognitive Merchandise Financial Planning, the retailer will reduce time spent on set up and maintenance tasks like adjusting to trends, seasonality, and more. Because the solution dynamically adjusts to the latest marketing needs, there will be improved decision-making speed and automated accuracy, resulting in better performance and greater collaboration across teams while using fewer resources and improving global inventory control.  

Microsoft and Blue Yonder taking retail planning to new heights with AI and machine learning

Blue Yonder and Microsoft are transforming the way supply chains are run. The Blue Yonder Luminate Cognitive Platform, which runs on Microsoft Azure, is embedded with AI and machine learning and serves as the foundation for all systems and applications. Retailers can spin up unconstrained computing power to run hundreds of simulations in a matter of minutes, versus in a few hours—or days. Blue Yonder’s solutions also run on a single source of truth, eliminating batch so teams don’t have to sacrifice accuracy for speed. As a result, retailers are collapsing the time horizon between planning and execution to nearly zero, while working synchronously across their supply chain. Integrated generative AI serves as a force multiplier for productivity so teams can do more important things more frequently and drive continuous optimization. To enable this transformation, Blue Yonder recently announced the launch of two next-generation planning solutions for retail, Cognitive Demand Planning and Cognitive Merchandise Financial Planning, as well as its generative AI solution, Blue Yonder Orchestrator.

The Blue Yonder Cognitive Demand Planning solution utilizes patented Blue Yonder algorithms and machine learning models to forecast, shape, and sense demand while collecting inputs from all key stakeholders to produce an optimized plan. These capabilities reduce the effort required to simulate drivers in real-time while managing more complex scenarios, resulting in faster and more accurate results. By seamlessly bringing together AI and machine learning driven capabilities, Cognitive Demand Planning empowers teams to respond faster to problems while building supply chain resilience and managing more complex scenarios, providing a leg up for demand planners to deliver higher plan accuracy and more relevant AI-driven insights.

Traditional merchandise financial planning can be a manual and reactive process. Cognitive Merchandise Financial Planning from Blue Yonder solves these problems and more. Blue Yonder can take your manual process and transform them into long-range planning and workflows that span across stores, e-commerce, wholesale, and more. This planning solution adjusts to fit your needs, with planning processes that can be configured based on your priorities and business objectives. To more accurately predict upcoming challenges, AI-enabled ‘what if’ scenarios allow a multitude of roles in the company to make quality decisions based on all available data, enabling a true omnichannel planning process. Cognitive Merchandise Financial Planning also makes it easier to analyze data after the fact—from large aggregations to slicing down to granular data—or continuous learning and optimization.

Integrated within the Luminate Cognitive Platform, Blue Yonder Orchestrator brings together the power of generative AI, the natural language capabilities of large language models (LLMs) and the depth of Blue Yonder’s supply chain expertise to unlock the full value of data. This unique solution delivers dynamic decision-making and orchestration by allowing users to query in everyday language then providing recommendations and insights in an easy-to-use format. This approach accelerates the learning curve for new employees while increasing overall productivity by serving up insights and guided recommendations without needing to navigate multiple software applications. Because Blue Yonder Orchestrator is embedded within the Luminate Cognitive Platform, which runs on Azure, it inherently benefits from robust security measures, auditing, reliability, and cost control. With Blue Yonder Orchestrator, companies can also establish guardrails based on user permissions, protecting data access without inhibiting performance. No matter what your focus is, using generative AI can bring you closer to your goals.

Getting started with AI and machine learning

At the end of the day, these emerging technologies have been proven to help accelerate better business outcomes when the right foundation is in place. Supply chains are an excellent place to incorporate predictive AI, generative AI, and automation due to the number of moving parts and the massive amounts of data generated. AI can unlock the complete value of data in near real-time for better insights to increase efficiency of decision-making. For example, while a person can only create so many scenarios in a day, AI’s unconstrained computing powers enables it to process hundreds of scenarios in minutes. These data-driven insights allow teams to focus their time on making value-added, high-impact decisions rather than on manual data entry and analysis.

AI, machine learning, and automation are great tools that can act as a force multiplier for supply chain efficiency and profitability. While new solutions are cropping up every day, it’s imperative to look for business applications that run on a centralized, cloud-based platform, a single database, have connected workflows, and have AI and machine learning embedded throughout. With this foundation, retailers will be empowered to break down existing silos, foster both inter-and intra-enterprise collaboration, and drive their businesses towards a future of greater resilience and sustainability.

Explore solutions from Microsoft and Blue Yonder

• Learn more about Cognitive Demand Planning from Blue Yonder.
• Learn more about Cognitive Financial Merchandise Planning from Blue Yonder.
• Learn more about Blue Yonder Orchestrator.
• Build your own copilot and generative AI applications with Azure OpenAI Service.
• Microsoft introduces new capabilities that help retailers bring AI to the shopper journey and enhance store associate experiences.
• New era of value realization is here—put your data to work with AI.

The post Unlock the full potential of your next-generation supply chain with Microsoft and Blue Yonder appeared first on The Microsoft Cloud Blog.

From startups to global enterprises, Microsoft is helping organizations of all sizes unlock the power of data and AI to accelerate the energy transition and create a data driven digital foundation for a sustainable future. Microsoft, our partners, and customers, are deploying innovative solutions that enable energy transformation in ways that weren’t possible before—to empower employees, increase operational efficiency, achieve net-zero commitments, and grow sustainable businesses.

Microsoft for Energy and Resources

Transform the energy and resources industry

Explore solutions

CERAWeek always brings new ideas and people together, and we are thrilled once again to participate in this important exchange of ideas, insights, and innovation. We need a diversity of voices to tackle the multidimensional energy transition, and we’re committed to working with customers and partners to accelerate digital transformation and our journey to a sustainable future.

At CERAWeek 2024 from March 18 to 22, 2024 in Houston, Texas, Microsoft will address the complexities of the multidimensional energy transition—markets, climate, technology, and geopolitics. We hope to see you at this annual gathering of energy executives, policymakers, and thought leaders from around the world. This year, attendees will explore strategies for a multidimensional, multispeed, and multifuel energy transition. Look for us throughout the week on the main stage, in leadership circles, Innovation Agora sessions, and at the Microsoft Agora House, where we’ll showcase new technologies, solutions, and perspectives together with our customers and partners.

Accelerate the energy transition with AI 

Themes at CERAWeek 2024 include energy markets, climate and sustainability, new supply chains for net-zero, technology and innovation, and power markets in transition. Microsoft’s leaders from energy, sustainability, cloud and AI, and security will be addressing these topics and speaking about the impact of AI and other technologies at the following sessions:  

• Scott Guthrie, Executive Vice President, Cloud + AI: “The Multidimensional Energy Transition: A world of choices.”
• Matt Kerner, Corporate Vice President, Microsoft Cloud for Industry: “AI: How will it impact the energy business?“
• Kelly Bissell, Corporate Vice President, Microsoft Security: “AI Enhancing Cybersecurity across the Energy Sector.”
• Bobby Hollis, Vice President Energy: “Future Forward: Harnessing the power of Gen-AI in climate solutions.”
• Christoph Schittko, Principal Software Engineer and Kadri Umay, Principal Program Manager, Microsoft: “Empowering the Energy Industry to Achieve Net-Zero Carbon Emissions with Data and A.”
• Conor Kelly, Principal Program Manager and Dag Boye, Industry Advisor, Microsoft: “Accelerating Business Transformation and the Energy Transition with Real-World AI.”
• Hanna Grene, Global Leader Go-to-Market and Operations, Energy and Resources Industry: “Effectively Decarbonizing the Electricity Grid.”
• Hany Soliman, Americas Business Leader Energy and Resources Industry: “Hydrogen and Power: Keeping the lights on in a zero carbon system.”
• Hema Prapoo, Worldwide Oil and Gas Leader: “Unveiling the latest breakthroughs in climate change mitigation.”
• Sverre Brandsberg-Dahl, Partner Chief Technology Officer, Energy Industry: “Accelerating CO2 transportation and storage solutions.”

I am pleased to participate alongside my Microsoft colleagues as a speaker on the topic, “Will AI accelerate the energy transition” and in an interactive “Next Gen” session featuring rapid-fire insights by leading minds on energy innovation along with CERAWeek 2024 future energy leaders.  

Showcasing innovation with customers and partners

At the Microsoft Agora House, we’ll join our customers and partners in showcasing some of the latest innovations driving safety, productivity, efficiency, and sustainability. Visitors to our Agora House can learn about:

• Microsoft Copilot for Dynamic 365 Guides: Transform frontline operations with AI and mixed reality
  AI, automation, and mixed reality solutions are poised to reshape industries everywhere. While industrial organizations worldwide overhaul their operations, frontline workers are still awaiting their digital renaissance. Within the energy industry, a focus on safety and the desire to accelerate skilling has Chevron looking to better equip its workers for the future. Copilot in Dynamics 365 Guides offers Chevron the opportunity to optimize its operations, empower workers, and infuse informed decisions throughout its value chain. Together, AI and mixed reality enable Chevron to define energy in human terms.​
• Microsoft Copilot for Security: Protect critical infrastructure at the speed and scale of AI
  Discover how Copilot for Security helps a broader set of security and IT professionals protect both their IT systems and industrial assets at the speed and scale of AI. Witness the power of Copilot synthesizing data from new sources, adding context and enrichment, and delivering new levels of effectiveness and efficiency, all in natural language, powered by generative AI.
• Microsoft Azure Data Manager for Energy: Accelerate your journey to energy data modernization
  Azure Data Manager for Energy helps energy companies gain actionable insights, improve operational efficiency, and accelerate time to market on the enterprise-grade, cloud-based OSDU® Data Platform service. The Microsoft partner ecosystem plays a crucial role in Azure Data Manager for Energy. For example, SLB’s Enterprise Data Solution seamlessly integrates with Azure Data Manager for Energy and simplifies data handling and discovery for domain-specific applications. Customers like Equinor are targeting data efficiency and a low-carbon future with Azure Data Manager for Energy and Aker BP is leveraging the platform to transform its data and operations.
• Microsoft Cloud for Sustainability​: Unlock the power of AI to meet your sustainability goals​
  Discover how AI in Microsoft Cloud for Sustainability helps unlock data insights to accelerate sustainability progress, business growth, and climate innovation. Now in preview, Sustainability data solutions in Microsoft Fabric allows organizations to accelerate their time to insights and sustainability progress by providing out-of-the-box environmental, social, and governance (ESG) data model, connectors, and reporting. By connecting your ESG data with Fabric you can turn volumes of sustainability data into meaningful insights and progress.

Partnerships for energy industry transformation  

Complex climate challenges require deep collaboration and innovation across industries and geographies. Microsoft values its partnerships and the industry-specific solutions partners provide, and we’re honored to highlight many of these change-makers at CERAWeek 2024. Microsoft partners in our Agora House are at the forefront of accelerating data modernization and leveraging generative AI so companies can achieve their safety, efficiency, productivity, and decarbonization goals. Featured partners and their solutions include: 

• Accenture is reinventing business and workforce productivity with generative AI. 
• Cognite is partnering with Microsoft to unlock real-time industrial insights with AI and to bring enterprise data operations to the generative AI era.  
• Schneider Electric is advancing decarbonization by integrating more distributed energy resources into the power grid. Microsoft and Schneider Electric are collaborating to leverage copilots and generative AI to transform outage management and control center operations.¹  
• SLB is accelerating the energy transition with speed and scale through data, AI, innovation, and partnerships with digital solutions enabling carbon capture utilization and storage (CCUS).  

Other partners we are highlighting and presenting at the Microsoft Agora House include:

Customers leading the way with AI and Microsoft Copilot for Microsoft 365

Microsoft customers are at the forefront of digital transformation with AI. For example, Petronas, Cegal, and Microsoft have teamed up to drive innovation with an innovative platform based on Microsoft Azure high-performance computing (HPC) and AI technologies.² This initiative, which involves moving HPC workloads to the cloud, is anticipated to benefit energy operations for Petronas. 

More energy companies have announced commitments to implementing copilot to empower their workforce and advance their digital transformation journeys. Pacific Gas & Electric is leveraging Microsoft Power Platform, including AI and copilot features to address up to 40% of help desk demands to save more than $1 million annually. Global energy firm TotalEnergies is using Copilot for Microsoft 365 and Power Platform to improve operational efficiency, and this year all 100,000 employees will be trained to use these AI tools.³ Bp will also roll out Copilot for Microsoft 365 to its global workforce and empower them to improve workflows and enhance productivity.⁴

Startups speeding the energy transition 

The climate crisis impacts everyone, and diversity in the startup ecosystem helps to ensure that solutions also apply to everyone. People of color are disproportionately affected by climate change, yet Black and Latino founders receive less than 1.5% of total United States venture capital funding, women-founded organizations received 1.9% of those funds, and Black and Latino women founders less than 0.1%.⁵ 

Transformation starts with people, not technology, and Microsoft is proud to support underrepresented climate tech startups. At CERAWeek 2024, we are honored to feature nine startup pitch sessions with underrepresented founders and chief executive officers who are driving the future of clean energy and climate tech innovation at our Experience Zone. The Microsoft Agora House presents a unique opportunity to meet these startup leaders and learn about their innovations. The lineup includes: 

Other startup presenting in our Experience Zone include FlexDAO, Line Vision, and Utilidata from the Microsoft Energy Transition Studio for Startups, a new program designed to empower energy transition startups worldwide. By providing technical expertise, commercial support, and access to capital, the Microsoft Energy Transition Studio for Startups aims to accelerate the deployment of renewable energy, carbon capture, carbon management, and geothermal, to help the world get closer to and achieve net-zero. If your organization is developing energy transition or climate tech solutions, or to nominate a company, apply to the first cohort of Microsoft Energy Transition Studio for Startups.

See you in Houston

We hope you’ll join us in person at the conference and in the Microsoft Agora House, where we can connect and share more on transformational technologies like generative AI and their impact on the energy ecosystem. See you in Houston, Texas from March 18 to 22, 2024.

Learn more about Energy and Resources solutions with Microsoft

• CERAWeek 2024 
• Transformative AI solutions powering the energy and resources industry 
• Microsoft for Energy and Resources 

¹Schneider Electric drives Generative AI productivity and sustainability solutions by integrating Microsoft Azure OpenAI, PR Newswire.

²Petronas, Microsoft, Cegal join forces for upstream digital innovation, Gas Pathways.

³TotalEnergies unlocks the potential of generative artificial intelligence for its employees, TotalEnergies.

⁴bp looks to leverage power of generative AI with Copilot for Microsoft 365, bp.

⁵McKinsey and Company, Underrepresented start-up founders: The untapped opportunity, June 2023.

The post Microsoft at CERAWeek 2024: Enable energy transformation with data and AI appeared first on The Microsoft Cloud Blog.