The insurance industry stands at a pivotal moment in its digital transformation journey. With deep data reserves, a tradition of analytic decision-making, and a workforce skilled in actuarial and underwriting practices, insurers are uniquely positioned to benefit from the ongoing advances in AI.

However, despite early enthusiasm and pilot projects, only 7% of insurers have successfully scaled AI initiatives across their organizations.¹ The adoption of increasingly powerful AI agents—systems that can support autonomous tasks, help make decisions, and take action under human oversight—offers a promising path forward. By embedding intelligent agents into workflows, insurers can tackle legacy constraints, talent shortages, and operational inefficiencies to unlock transformative value.

Challenges in adopting agentic AI

The broad adoption of agentic AI in insurance is hindered by several entrenched challenges.

First, a persistent talent shortage affects specialized roles such as actuarial analysis and underwriting, which limits the industry’s ability to leverage data effectively. Adding to the challenge is legacy infrastructure, including outdated systems and fragmented data architectures, which can impede integration and scalability.

Financial strain across the insurance sector is another major factor, with catastrophe losses exceeding $100 billion annually for six consecutive years, making high-frequency property losses a structural issue.²

Organizational resistance also plays a significant role; siloed teams, unclear priorities, and a conservative corporate culture slow the pace of AI adoption.

Opportunities with agentic AI

Despite these hurdles, agentic AI presents transformative opportunities. Workforce augmentation is one of the most promising areas. For instance, Sedgwick’s Sidekick Agent, developed in collaboration with Microsoft, enhances claims processing efficiency by more than 30% through real-time guidance and decision support.³

AI also enables personalized customer experiences at scale, using embedded systems to tailor communications and support. Operational efficiency can be improved significantly in some implementations, with end-to-end redesigns yielding 30–40% gains in net efficiency.¹

Furthermore, agentic AI, under human guidance, can enhance quality assurance by improving consistency and helping insurers adhere to compliance processes, which is especially important as seasoned professionals retire and institutional knowledge can be lost.

With agentic AI, chatbots can also be improved to more effectively enhance customer experience. Instead of answering a question and handing a customer off to a queue, an agentic solution can help orchestrate a more end-to-end experience. Potentially, this can include everything from capturing first notice of loss, to requesting missing documentation, updating policy and billing systems, scheduling appraisals, and proactively notifying customers of next steps (all subject to insurer workflows and regulatory review, of course).

This “resolve, not route” approach is already showing measurable impact in claims operations: For example, according to McKinsey, one major insurer rolled out more than 80 AI models in its claims domain, cutting complex-case liability assessment time by 23 days, improving routing accuracy by 30%, and reducing customer complaints by 65%.⁴

For carriers, such outcomes translate into faster cycle times, higher customer satisfaction, and better loss-adjustment expense control—all while preserving necessary human oversight where judgment, empathy, and regulatory accountability are required.

Strategies for success with agentic AI

To successfully adopt agentic AI, insurers must align technology initiatives with customer needs and business goals.

Establishing an AI Center of Excellence (CoE) is a foundational step. A CoE provides governance, strategic direction, and technical expertise, helping organizations avoid fragmented AI adoption and scale responsibly.

Iterative testing is also essential, beginning with high-volume, repeatable tasks that help insurers refine models through feedback loops and production pilots.

Targeting scarce talent areas, such as fraud detection and underwriting, can maximize impact by augmenting roles that are difficult to fill.

Industry accelerators like Cognizant’s Agent Foundry offer prebuilt tools and frameworks that can help reduce implementation time and support compliance efforts. This platform-agnostic solution supports the full lifecycle of agent deployment, from discovery to scale, and integrates seamlessly with existing enterprise systems.

Finally, cultural transformation is critical. Since 70% of scaling challenges are organizational, insurers must foster a culture of change, accountability, and long-term thinking to fully realize AI’s potential.¹

Move to agentic AI with confidence

Agentic AI is not just a technological upgrade, it is a strategic imperative for insurers seeking to thrive in a rapidly evolving landscape. By addressing structural challenges and embracing AI as a catalyst for transformation, insurers can unlock new levels of efficiency, personalization, and resilience.

The path forward requires bold leadership, cross-functional collaboration, and a commitment to continuous learning. Those who invest in scalable frameworks, such as AI Centers of Excellence and industry accelerators, will be best positioned to lead the next era of insurance innovation.

Explore solutions for agentic AI in insurance

• Explore insurance solutions and resources on Microsoft for Insurance.
• To learn about how Cognizant and Microsoft are partnering to help insurance companies advance their cloud modernization journeys, see the Cognizant and Microsoft Partner Page.

¹ Insurance leads AI adoption. It’s time to scale

² 2025 marks sixth year insured natural catastrophe losses exceed USD 100 billion, finds Swiss Re Institute

³ Sedgwick optimizes claim workflows with AI application Sidekick and Microsoft integration

⁴ The future of AI in the insurance industry

The post Microsoft and Cognizant: Delivering on the promise of agentic AI adoption in insurance appeared first on Microsoft AI Blogs.

By using more intuitive, natural interfaces to knowledge and information, retailers can start addressing some of retail’s age-old challenges—like finding and retaining the best talent, getting them up to speed quickly, and simplifying store operations so associates can focus on delighting and assisting shoppers.

No matter the size of the retailer, choosing which AI technologies to prioritize and where to start can be challenging. However, there are many ways retailers are now using AI to deliver measurable value and real return on investment (ROI). Research shows that for every $1 a company invests in generative AI, the ROI is 3.7 times across industries and regions (compared to 3.5 times in 2024).¹ Top leaders using generative AI are realizing significantly higher returns, with an average ROI of $10.30—nearly three times more.¹

To build a foundation for AI success, focus on your business strategy—how AI supports your business goals. Start by identifying the business outcomes you’re aiming for and how AI can help you achieve them.

Here’s a glimpse into how you can start making gains with your AI investments today by focusing on store operations and the frontline.

The frontline is first in line with AI

As the face of retail, frontline workers play a crucial role in the shopper experience. According to recent research by McKinsey, there is a strong relationship between the employee and customer experience, as empowered employees are more likely to deliver superior customer service.² Yet many frontline workers spend too much time searching for information, and this is one of the top five reported obstacles to their productivity.³

Generative AI offers significant potential for enhancing frontline productivity and wellbeing, with evidence that most frontline workers think it could help, and they would be comfortable using AI for administrative tasks.³ Generative AI can automate routine tasks, allowing associates to engage more with customers. This shift can lead to a more stimulating work environment, which leads to higher job satisfaction and can help retailers combat ongoing challenges with employee turnover, seasonal hiring, and training.

At a more macro level, generative AI can also allow retailers to continuously learn and feed insights back into their business processes and to grow their products, services, and competitive differentiation. Retailers can do that by identifying patterns in recurring employee questions so they can get to the root cause of operational challenges and address key gaps in training and store processes.

Here are some other ways retailers are using generative AI today:

• Swedish retailer Lindex created Lindex Copilot to offer tailored support to store associates and better understand store needs. Generative AI facilitates this bidirectional learning.
• MediaMarktSaturn lets associates to have voice conversations with generative AI, accessing details for every product, service, and warranty while staying engaged with the in-store customer, maximizing conversion and increasing customer satisfaction—all while wearing an earbud.
• Store associates at gourmet chocolatier Venchi use detailed product knowledge and customer insights to address the diverse chocolate preferences of shoppers, achieving a customer satisfaction score of 4.9 out of 5.

While generative AI technologies are still relatively new, these examples offer a glimpse of what’s possible, and help retailers build an AI foundation for more powerful capabilities emerging with agentic AI.

Agents are revolutionizing retail operations

Investing in generative AI is crucial for retailers looking to reinvent customer engagement, empower store leadership and employees, and stay competitive—and now that opportunity has skyrocketed with agents.

Agents use AI to automate and execute business processes, working alongside or on behalf of a person, team, or organization. Now retailers can leverage agents to help their teams work more efficiently and effectively by giving them faster access to information so they can better support customers and be more productive.

Agents vary in levels of complexity and capabilities depending on the need. Agents can help frontline workers with a variety of time-saving tasks—from quickly surfacing real-time product information or details about store policies and procedures to support Q&A or troubleshooting. In addition to helping speed information retrieval, agents can help frontline workers with more advanced features like automated task creation or even advising and summarizing information—such as listing open tasks for a shift handover or flagging missed communications. Agents can also operate independently to dynamically plan, orchestrate other agents, and learn to improve over time. For example, an automated stock transfer agent might scan sales velocity across multiple stores and automatically transfer goods between locations if one store is oversupplied while another is understocked, minimizing manual intervention.

Find in-the-moment answers fast

One important way to get business value from agents is to help store associates find information about company policies or procedures when a customer is waiting for an answer.

SharePoint agents can help store associates find quick answers from internal company sources in seconds. Using the power of natural language, associates simply ask what they’re looking for on their tablet or mobile device and the agent responds in natural language with a link to the policy documentation for reference.

These agents go beyond information retrieval to also generate step-by-step instructions, synthesize product information, and support frontline managers to create and smart-assign shifts, and auto-validate task completion.

Agents can help associates reduce customer wait time, increase information accuracy, and possibly facilitate sales.

Simplify store processes

Complex business processes are another ongoing operational challenge and opportunity for custom agents to help improve productivity.

Custom-built agents can help retailers connect to external data sources and systems so store associates can find information such as product inventory availability in or near their store, shipping status, or how to initiate a return.

Frontline workers simply ask, “Help me initiate a return,” and the agent guides them through the process by clarifying the worker’s intent and providing them with next steps, all through a chat interface.

Custom agents are best suited to also streamline complex workflows like task management, that often involves multiple steps. Using custom agents built with Microsoft Copilot Studio, frontline workers can easily create a task and send it through a task management system that sends automatic alerts as needed, all from a single pane of glass.

Meeting you where you are on your AI journey

Microsoft offers AI solutions that you can customize to meet your unique needs and scale. There are several ways agents can be deployed, from no code to low code and pro code. Here are a couple options available today.

Microsoft 365 Copilot Chat is a new offering that adds pay-as-you-go agents to our existing free chat experience for Microsoft 365 commercial customers. Copilot Chat empowers retailers to get started on their AI journey today and includes querying the public web (such as a retailer’s website) for free. To enhance Copilot Chat, retailers can also build custom agents using Copilot Studio and SharePoint agents that enable access to retail systems such as enterprise resource planning (ERP), customer relationship management (CRM), and product information management (PIM), and to documents on SharePoint. These paid agents are available on a metered basis, so you only pay for what you use.

Store Operations Agent is a pre-built agent available on Copilot Studio enabling retailers to get started fast with a prebuilt solution that acts as an “associate” to your store associate. With this agent, retail employees can:

• Access data from LOB systems: Look up product inventory, check order status, find customer information and compare products.
• Access store policies and procedures: Quickly find answers to questions from knowledge bases such as SharePoint, websites, and across select internet portals.
• Raise incidents for quick resolution: Connect to incident management tools by using more than 1,000 connectors in Power Platform to raise incidents and alert store teams.

Using Store Operations Agent, employees at leading Nordic retailer Kappahl can quickly and securely surface product information, store policies and procedures, and more, increasing store associate productivity and upleveling the shopping experience for customers.

A new era of retail fueled by AI, powered by people

The range of potential gains with AI extends across retail operations—from people to processes to customers, helping make retail more human at every step of the way. From delighting shoppers to helping associates feel more supported and productive, AI can boost store operations efficiency, creating an environment where both shoppers and workers thrive.

Savings achieved using AI can be reinvested to create a better employee experience, fostering a work environment where employees are enthusiastic ambassadors of the brand, bringing the life of the store to customers every day.

Microsoft is the proven leader for AI transformation with the full technology stack and portfolio to help retail and consumer goods organizations power their business with AI. We can help you assess your agent environment, ideate on agent use cases, and establish success criteria for evaluating ROI so you can decide what agent is best for you.

Learn more

Learn more about how these forward-thinking companies are driving ROI with Microsoft 365 Copilot and agents—and illuminating the path ahead for every organization.

• Microsoft’s responsible AI principles
• How CMOs can personalize marketing and optimize spend with AI
• How merchants can drive velocity with AI
• Enhancing supply chain efficiency in the retail and consumer goods industry with agentic systems
• How unifying data improves shopper experiences

Microsoft Cloud for Retail

Connect your customers and your data

Explore solutions

¹ Generative AI delivering substantial ROI to businesses integrating the technology across operations: Microsoft-sponsored IDC report – Middle East & Africa News Center.

² How retailers can build and retain a strong frontline workforce in 2024.

³ Work Trend Index: Will AI Fix Work?

The post More human-centered retail with AI appeared first on Microsoft AI Blogs.

What are OSS and BSS?

Learn how to streamline processes and drive growth

Explore solutions

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 Microsoft AI Blogs.

Manufacturers face existential challenges around several key and often conflicting goals; the need to increase revenue whilst at the same time reducing costs across the value chain—spanning engineering, manufacturing, and supply chains, starting with product design and engineering. These challenges have impacted everything from product requirements and capabilities to product development all the way to sourcing and production. A recent IDC report highlighted how for product managers, investing more in engineering and research and development (R&D) correlates with lower cost of goods sold (COGS) and higher revenue growth for manufacturers, suggesting that investments in product engineering investments drive financial success.¹    

Benefits of generative AI in product engineering  

As product complexity and connectivity has continued to increase, engineers’ roles have become multi-disciplinary, requiring interaction with various data sources and tools, such as product lifecycle management (PLM), computer-aided design (CAD), computer-aided manufacturing (CAM), application lifecycle management (ALM) for software requirements, and computer-aided engineering (CAE). In addition to manufacturability, engineers need to incorporate aspects such as sustainability, regulatory compliance, quality, materials, and supplier and supply chain considerations much earlier in the product design process. The many lines of software code now prevalent in physical products and the growth in software requirements, also pressures traditional manufacturing information technology (IT) to support a proliferation of software tools, data, and infrastructure.      

Generative AI is transforming product engineering and R&D to enable manufacturers to realize these benefits:  

• Cost reduction: Optimizing product designs for cost, sustainability, and manufacturability can reduce product development and production costs.  
• Better decision-making: Facilitated through data analysis and scenario simulation, generative AI provides valuable insights for informed decisions that can enhance product development, improve product quality, and better meet customer demands.  
• Productivity and skills gap: Helps experienced designers automate tasks they do often, and inexperienced designers to get up to speed quickly and avoid errors with best practice guidance.  Assists with analysis and optimization of existing designs and can even generate new designs with user input.   
• Efficiency: Reduce the time taken by engineers to both search across, and interact with, product data from various sources across the product lifecycle.  
• Faster time-to-market: Shorter product development cycles mean products can reach the market faster to capitalize on new opportunities more quickly. 
• Innovation: Continuously analyzing product-related data from various sources, customer feedback, and learning from it with generative AI can suggest innovative solutions that might not be more readily apparent.   

Microsoft partners play a pivotal role in transforming product engineering and R&D by building industry-specific solutions that integrate data unification and contextualization capabilities with Microsoft technologies which, combined with the Microsoft Cloud, are revolutionizing engineering functions.    

Establishing a secure engineering data foundation  

Product engineering and R&D involve handling many types and modalities of data, including CAD files, technical specifications, product data and configurations, requirements, and process data. Manufacturers commonly use a range of systems, including PLM, ALM, and enterprise resource planning (ERP) systems, to manage this complex data. These form a secure data foundation on which transformation of product engineering is built upon, and sensitive IP can be protected.     

The following are examples where generative AI is helping to deliver value in a secure, engineering data foundation with AI on the Microsoft Cloud.  

• Siemens has integrated Microsoft Teams, Microsoft Azure OpenAI Service, and Siemens’ Teamcenter PLM solution into an app to facilitate real-time communication and collaboration among frontline workers and engineers.
• Aras has introduced AI-assisted search and an intelligent copilot, using Azure OpenAI Service and Microsoft Copilot Studio on Azure, enhancing user interaction with PLM data, facilitating quicker access, analysis, and action on critical information through scalable search and conversational AI, user interaction with PLM data, facilitating quicker access, analysis, and action on critical information through scalable search and conversational AI.
• PTC Codebeamer Copilot focuses on requirements authoring and analysis for the flagship Codebeamer Application Lifecycle Management (ALM) solution. This AI-powered agent, being used by Volkswagen Group, improves the efficiency of the design phase, helping to ensure potential issues with system requirements are identified and addressed early in the process and a productivity boost as users manage complex hierarchies of requirements.
• Bluestar PLM are leveraging Microsoft Copilot for Dynamics 365 to automatically generate summaries for an engineering object based on data both from Dynamics 365 and Bluestar PLM, and automatically generating item descriptions in multiple languages to make it easier to generate quotes, bills-of-materials (BOMs), invoices, and other documents in different languages.  

Accelerating product engineering and R&D 

Engineers use a range of complex solutions in product engineering when producing product designs from CAD, CAM, and CAE applications. This also involves creating and using many different data types, from 3D CAD and CAM files, to CAE simulation datasets, documents, specifications, and various knowledge repositories.   

The following are examples where customers and generative AI-powered partner solutions are helping to deliver value in accelerating product engineering and R&D with AI on the Microsoft Cloud: 

• HARTING reduced design time from weeks to minutes by introducing an AI-powered assistant fueled by Azure OpenAI Service and Microsoft Cloud for Manufacturing, interoperating with Siemens NX CAD for rapid design. This solution reduced configuration time by 95%, a significant improvement in efficiency and the rapid creation of custom electrical connector prototypes that are speeding up time-to-market.
• Hexagon AI-powered automated CAM programming solution, ProPlanAI, reduces the time taken to program factory machine tools by 75%. This solution is part of Hexagon’s cloud-based Nexus connectivity and collaboration platform for discrete manufacturers, and is powered by Azure OpenAI Service, Microsoft Azure Cosmos DB, and Microsoft Azure Databricks.
• Siemens copilot for NX X software uses an adapted industry AI model to help users ask natural language questions, access technical insights, and streamline design tasks for faster product development. It provides CAD designers with AI-powered recommendations and best practices to optimize the design process within the CAD experience, aiding engineers in implementing best practices quickly, ensuring high-quality results from design to production.
• Rescale is transforming engineering innovation by integrating AI-powered tools with Microsoft technologies to enhance simulation data workflows with Rescale Automations, automating data processing for real-time insights, improving decision-making and collaboration with AI models including Phi-4 to reduce cycle times and costs while maximizing simulation insights.
• Siemens has announced an industrial foundational model (IFM) to enhance the productivity of engineering and automation tasks across the industrial sector. For example, it will help engineers automate CAM programming with context-aware recommendations, support Structured Control Code (SCL) generation and accelerate the creation of Process Flow Diagrams (PFDs) and Process and Instrumentation Diagrams (P&ID). The IFM is built on Microsoft’s Azure platform. 

The next step: Unlock innovation in product engineering with AI-powered digital threads 

The next stage in revolutionizing product engineering and R&D sees the addition of multi-agent AI systems that can orchestrate, collaborate, and scale across complex enterprise workloads, including product engineering solutions, supply chain, manufacturing execution systems, customer relationship management, field service, and enterprise resource planning.   

Microsoft, along with partners like PTC, Autodesk, and Aras, believe that digital threads are becoming a reality for industrial customers due to unified data foundations and generative AI. Unified data foundations make data usable by securely sourcing it from various systems and automating contextualization. Generative AI agents use this data to provide insights and take actions, unlocking numerous use cases across the manufacturing value chain, including product engineering, all through unified data foundations and generative AI.  

The following are several such examples of innovations that are fueling the emergence and promise of AI-powered digital threads: 

• Aras InnovatorEdge is a new low-code API management framework for extending product digital thread ecosystems, which will also integrate with Microsoft Fabric, Microsoft 365 Copilot, and Microsoft Cloud for Manufacturing, enabling seamless connectivity for advanced analytics and AI-powered insights.
• Autodesk Fusion connects people, data, and process through the product development lifecycle. Autodesk Data Solutions in Fusion Manage and Microsoft Fabric enable data management and process optimization. Additionally, Autodesk’s digital twin offerings through Tandem, factory simulation through FlexSIM, and factory operations management with Fusion Operation all benefit from this collaboration across the IT and operational technology (OT) ecosystem.
• PTC is collaborating with Microsoft on an enterprise data framework and agentic model for PLM scenarios in PTC Windchill within Microsoft Fabric to accelerate manufacturers digital thread strategies and unlock insights and workflows across the value chain using AI-powered agents.
• Toyota is deploying AI agents to harness the collective wisdom of engineers and innovate faster and more efficiently in a system named “O-Beya,” or “big room” in Japanese. The “O-Beya” system currently has nine AI agents—from a Vibration Agent to a Fuel Consumption Agent, bringing together numerous functional experts.  

By using Microsoft Cloud for Manufacturing and AI-powered solutions from our partner ecosystem, manufacturers can securely unlock new levels of impact. The integration of AI-powered solutions and AI agents unlocks innovation, reduces costs and improves operational efficiencies, meaning manufacturers are better equipped to navigate challenges and seize opportunities.    

Microsoft in manufacturing and mobility industries 

Learn more about Microsoft Cloud for Manufacturing and Microsoft for automotive, and how companies are using Microsoft AI capabilities in Microsoft AI in Action. 

Learn more about the unique use cases and solutions driving innovation in product engineering and R&D from our presence at Hannover Messe 2025.

Microsoft Cloud for Manufacturing

Drive innovation with an AI-powered digital thread

Explore solutions

¹ IDC Research, Investing in Product Engineering — Increase Revenue and Decrease Cost, Doc # US51892224, February 2025. 

The post Shaping the future of product engineering and research and development with generative AI appeared first on Microsoft AI Blogs.

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.

Microsoft Cloud for Retail

Explore solutions

Learn more

• 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 Microsoft AI Blogs.

Yet even with all this progress, for decades fragmented systems and heterogenous environments have kept digital threads within the industry largely aspirational, preventing most organizations from achieving synchronized operations. A persistent inability to connect modern technology solutions with aging infrastructure has also slowed the collaboration long promised to manufacturers. Together, unified data and AI are now enabling organizations of all sizes to break through these barriers, transforming digital threads from static, disconnected datasets to dynamic networks. With AI agents serving as the interface, every worker can surface the overall equipment effectiveness (OEE), total cost of ownership (TCO), and return on investment (ROI) insights necessary to drive decision-making.

At Hannover Messe 2025, Microsoft is showcasing how new AI agents and partnerships with leading software vendors can help manufacturers deliver secure, scalable innovation from the shopfloor to the boardroom. Attendees will experience firsthand how data-driven intelligence and AI-enabled solutions will reshape manufacturing.

AI agents supporting the development of frontline workers 

Manufacturing transformation is reaching into every aspect of operations. Frontline workers now have access to AI agents providing them with enhanced guidance needed to make informed decisions. To expand this modern toolbox, we announced back at Ignite 2024 the public preview of Factory Operations Agent in Azure AI Foundry. An AI-powered assistant, Factory Operations Agent streamlines operations—enabling operators, production, and leaders to quickly access insights and optimize manufacturing processes through natural language querying. In doing so, the agent accelerates issue resolution and root cause analysis to improve productivity within day-to-day manufacturing operations.

As the industry struggles with turnover, worker skilling is an ever-present challenge. The World Economic Forum found that 63% of industry leaders believe skilling to be a significant barrier to growth.¹ Manufacturers need no-code and low-code options that democratize the power of AI without the need for extensive coding. With this in mind, we are announcing the same Factory Operations Agent now available in Copilot Studio in public preview, where with one-click it can be easily integrated into products like Microsoft Teams.

Finally, we’re announcing the public preview of Factory Safety Agent in Copilot Studio. This low-code, customizable solution provides workers with answers to occupational health and safety (OHS) questions and guidelines. It can also streamline safety inspections and personalize workforce training. 

Also, at Hannover Messe 2025, we will be showcasing state of the art technologies that will enhance the future of frontline work, like with our customer Sanctuary AI.

Sanctuary AI is shaping the future of frontline work, ushering in the era of autonomous labor with the power of Microsoft Azure. As frontline labor shortages intensify, manufacturers can explore deploying advanced general-purpose robots with dexterity-driven physical AI to automate repetitive, complex, and unsafe tasks to enhance operational efficiency. With Azure’s high-performance graphics processing units (GPUs), Sanctuary AI can train machine learning models at scale, pushing the boundaries of dexterous intelligence. 

Advancing innovation in digital engineering with generative AI 

Manufacturers shape their market leadership through digital engineering and design. By accelerating development and prototyping, and reducing time-to-market, AI-powered generative design is empowering manufacturers to create new high-performing, customer-centric products.

GenAI use cases to modernize manufacturing

Explore the value generative AI creates across the organization

Learn how

Aras is introducing Aras InnovatorEdge, a low-code application programming interface (API) management framework embedded in the Aras Innovator® platform. This solution simplifies API creation and integration, enabling secure, scalable data connectivity and enhancing collaboration, operational efficiency, and decision-making across enterprises. It integrates seamlessly with Microsoft Fabric, unlocking deeper insights and optimizing decision-making across the digital engineering landscape. 

Autodesk and Microsoft collaborate to create an AI-powered digital thread to help manufacturers gain efficiencies, reduce costs, and compete smarter. Autodesk® Fusion, the industry cloud for manufacturing, connects people, data, and process through the product development lifecycle. Autodesk Data solutions in Fusion Manage and Microsoft Fabric will enable efficient data management and process optimization. Additionally, Autodesk’s digital twin offerings with Tandem, factory simulation through FlexSIM, and factory operations management with Fusion Operations all benefit from this collaboration, ensuring that these tools work seamlessly across the IT and OT ecosystem. 

Windchill by PTC is a crucial platform for engineering and manufacturing teams globally. To support manufacturers aiming to integrate AI across their value chains, PTC and Microsoft are partnering to develop an enterprise data framework and multi-agentic model within Microsoft Fabric. This collaboration extends digital thread capabilities beyond traditional product lifecycle management (PLM), integrating data from enterprise resource planning (ERP) and manufacturing execution system (MES) systems, and enabling AI-powered insights and workflows. 

Preparing the factory edge for AI  

AI is redefining factory operations, but to fully capitalize on shop floor investments, manufacturers need to integrate their on-premises industrial edge solutions with the cloud. 

A core component of the Azure adaptive cloud approach, Azure IoT Operations is built on industry standards. Capturing data from industrial equipment assets and devices, Azure IoT Operations normalizes it at the edge—sending operational insights to the cloud and back.

Husqvarna is leveraging Azure IoT Operations and AI tools to digitally transform its factory floors. Their AI Vision Companion enhances visual quality control for chainsaw production, while AI chatbots assist night workers with troubleshooting, improving efficiency, and reducing downtime. With these new capabilities, Husqvarna expects to double their in-market connected devices and boost robotic lawn mower sales, expanding Azure IoT Operations from two to 40 factories globally by summer 2025. 

Siemens and Microsoft have expanded their partnership, Siemens Industrial Edge works seamlessly with Microsoft Azure IoT Operations, making OT and IT data planes fully interoperable for manufacturing. This joint effort streamlines data flow between edge and cloud, enhancing machine performance, product quality, and maintenance efficiency, and enabling manufacturers to adopt AI and digital twin technologies for more adaptive, optimized production.

Making AI-powered digital threads a reality for manufacturers 

The nervous system of industrial operations, digital threads weave together critical information, processes, and people across manufacturing segments. Grounded in unified operational (OT), information (IT), and engineering (ET) data, the electronic frameworks can empower individuals with relevant, timely insights. From initial concept to customer support, this continuous flow of data connects and enriches every aspect of manufacturing.

For over a century, Rolls-Royce has been a force for progress; powering, protecting, and connecting people everywhere. Today, with digital transformation at the forefront, the company is redefining how its world-class products are designed, built, and maintained. Hannover Messe 2025 visitors will see firsthand how AI and cloud technologies are shaping the future of aerospace. With the help of Siemens and Microsoft, Rolls-Royce is leveraging AI to streamline production, boost engine efficiency, and predict maintenance needs before issues arise. Rolls-Royce is also helping provide more efficient, reliable, and low-emissions energy solutions, powering everything from critical infrastructure to data centers. Rolls-Royce isn’t just keeping up with the digital revolution—it’s driving it.

Without AI, manufacturing data is difficult to navigate. Data quality, standardization, and integration have been unreliable. Microsoft is helping manufacturers make sense of their data to unlock the AI opportunity. With Microsoft Fabric, manufacturers can integrate data across different departments and teams. Traditionally, this data is trapped within separate systems. Parsec and Tulip integrations mark another major step in our ability to drive operational intelligence, enhancing shop floor and frontline execution. 

Parsec, developer of the industry-leading MES, TrakSYS™, today announced an upcoming integration with Microsoft Fabric and the factory operations agent in Azure AI Foundry solution to help deliver generative AI to manufacturing organizations. Dubbed TrakSYS IQ, this industry-defining functionality will enable users to retrieve and analyze factory data through a conversational user interface, bolstering productivity and data-based decision-making. 

Tulip, a leader in frontline operations solutions, announces its integration with Microsoft Fabric. This integration enables the Tulip Frontline Operations Platform to deliver scalable analytics across multiple factories, leveraging rich datasets for machine learning to provide real-time feedback and alerts to supervisors and operators. 

See Industrial AI in action at Hannover Messe 2025

The future of manufacturing is powered by AI. This year, at Hannover Messe 2025, attendees will have the opportunity to experience how Microsoft and its partners are supporting the industry transformation—from digital engineering, on factory floors, with frontline workers, and through digital thread. Join us at Hall 17, Stand G06. 

Thanks to all partners and customers joining Microsoft at Hannover Messe 2025: ABB, Accenture Avanade, Autodesk, AVEVA, AVL, Bayer, Blue Yonder, Bosch, Bühler Group, C3.ai, Capgemini, Cognite, Databricks, EPLAN, Hexagon, Husqvarna, Kongsberg Digital, Litmus, MTEK, NVIDIA, NTT Data, o9, Parsec, PTC, PWC, Rescale, Rockwell Automation, Rolls-Royce, Sanctuary AI, Sandvik, Schneider Electric, Siemens, Sight Machine, Symphony AI, TeamViewer, TCS, and Tulip. 

¹WEF: Skill Gaps are the Biggest Barrier to Transformation, Skillsoft.

The post Industrial AI in action: How AI agents and digital threads will transform the manufacturing industries appeared first on Microsoft AI Blogs.

Fifty years ago, Microsoft started with a bold idea: the belief that technology could change the world. Thanks to the largest partner ecosystem in the industry, numbering 500,000 and growing, that vision became a reality, and I know we are just getting started. From the early days of distributing Windows PCs and Office to now delivering AI transformation strategies that solve the most complex customer challenges, our ability to stay at the forefront of innovation as technology evolves is a testament to our culture of continuous reinvention.

According to IDC, for every $1 of Microsoft revenue, services partners earn $8.45, and software partners earn $10.93. This underscores the immense opportunity available to partners of all types. As we look ahead to the future, we know that generative AI (GenAI) is forecast to grow exponentially faster than the overall IT market. Partners generating at least 25% of their Microsoft-related revenue from AI can expect higher margins and revenue growth, unlocking even more potential for transformation and success.*

Microsoft has always been a partner-led company. Our partners are core to our heritage and our future. Their innovation and collaboration have driven real transformation and customer success and will continue to shape the future of industries around the world. As we commemorate this historic moment, I want to take the opportunity to say Thank You to our partners for being on this incredible journey with us.

Here are just a few ways you can join us to celebrate this milestone:

• Watch this video from Judson Althoff, Executive Vice President and Chief Commercial Officer, Microsoft.
• Join the Microsoft AI Skills Fest for 50 days of learning and discovery starting April 8! Gain skills that will empower you and your team to build innovative AI solutions with Microsoft’s apps and services.

“For decades, Intel’s partnership with Microsoft has sparked innovation and delivered value to our customers. Together, we’ve revolutionized industries and established new benchmarks for excellence. We look forward to collaborating for the next 50 years — and beyond.”

— Jim Johnson, Senior Vice President, Client Computing Group, Intel

Preparing for the future with the Microsoft AI Cloud Partner Program (MAICPP)

Microsoft succeeds when our partners succeed. MAICPP has evolved to enable partners worldwide to deliver customer outcomes across every industry, from small businesses to the largest enterprises. Our program is designed to provide our partners with the most relevant tools and resources they need to thrive in a rapidly changing market, and it serves as the home for all partner types.

“As a proud Microsoft alum, I’ve seen firsthand how our collaboration has evolved to drive meaningful change for businesses across industries. From strategy through engineering and implementation, PwC and Microsoft drive innovation and deliver real business outcomes for clients worldwide.”

— Stephanie Mosticchio, Principal, US and Global Microsoft Alliance Leader, PwC

Through MAICPP, all partners can access updated benefits packages designed to accelerate growth and meet specific business needs. Software development companies are encouraged to explore ISV Success, a pathway offering additional benefits to expand development capabilities and shorten time to market. Whether building, publishing or growing sales, partners can leverage targeted offers to get the support they need.

“As someone who has led global partnerships at several of the world’s leading technology companies, I am impressed by how Microsoft has leaned in with their partner ecosystem and taken a leadership position in cloud computing and AI. We, at Snowflake, are excited to continue to strengthen our partnership in the years to come, and we look forward to jointly driving customer success in the age of enterprise AI. Congratulations!

— Tyler Prince, Senior Vice President of Worldwide Alliances & Channels, Snowflake

Depending on business goals, partners may pursue a Solutions Partner designation or specialization, both of which provide tailored benefits to help differentiate their business in a competitive market. Achieving a designation unlocks valuable go-to-market resources, sales support, new incentives and product benefits to help expand customer reach, sharpen skills and drive growth. For software development companies, becoming a Solutions Partner** with certified software*** further enhances market presence by validating software capabilities in high-demand areas.

“Having worked alongside every CEO of Microsoft in my career, I would like to personally congratulate Microsoft for its 50 extraordinary years of driving relentless innovation.”

“Lenovo is proud to be a major part of this amazing journey with Microsoft and we are committed to this partnership for many more decades to come.”

— Yuanqing Yang, Chairman and Chief Executive Officer, Lenovo

For partners holding an Azure designation or Azure specialization, additional incentives are available through Azure Migrate and Modernize and Azure Innovate — both underpinned by Azure Essentials. With comprehensive resources, extensive coverage across scenarios and tailored incentives in one easy-to-navigate hub, Azure partners can better support customers from migration to innovation. Learn more in What’s new for Azure partner-led offerings: ISV Success and specialization updates.

Our program offers benefits for partners aligned to their growth stage and across all customer segments. We have recently made the process of obtaining an Azure Solutions Partner designation more aligned to our partners who specialize in working with small and midsize customers. We are also expanding access to Azure Migrate and Modernize and Azure Innovate incentives for SMB pathways. Read more about the SMB path to Azure Solutions Partner designations.

Cloud Solution Provider is our partner hero motion for small and medium enterprises

In November at Microsoft Ignite, we highlighted the $661 billion total addressable market (TAM) opportunity for SME&C in FY25 and beyond. Cloud Solution Provider (CSP) partners are the trusted advisors who serve these customers and accelerate their AI transformation with the value-added services and solutions that create real business impact. CSP is our hero motion that enables those partners to drive this business transformation.

“Our Microsoft partnership has evolved to meet the needs of our business and our partners. Together we’ve been able to support our partners to deliver true solution and value selling, leveraging the robust resources available through Microsoft AI Cloud Partner Program and benefitting from the rich incentives. It has enabled us to drive innovation and deliver exceptional experiences for our partners through our ArrowSphere platform and broader enablement programs to ensure they’re empowered to deliver real customer outcomes. Together, we’re enabling the channel to deliver solutions that deliver real impact for customers around the world.”

— Brendan Murphy, Global Director, Public Cloud, Arrow Electronics

We strive to provide CSP partners with the skilling, capabilities and investments to make this opportunity a reality. So far in FY25, we have:

• focused our incentives to clearly align to our five strategic priorities — Copilot on every device across every role, AI design wins with every customer, securing the cyber foundation of every customer, a focus on migrations and Microsoft 365 execution
• dedicated 70% of our total incentive spend to partners that serve the Small and Medium Enterprise Channel (SME&C) segment
• introduced a series of new promos, including a new-to-Microsoft 365 E5 offer to enable CSP partners to win new customers

Expanding our portfolio of CSP offers and capabilities is an ongoing priority. We share updates as they become available.

Capturing the marketplace opportunity

As customers increasingly centralize their solution procurement, marketplaces have become the preferred buying platform. For software companies, adopting cloud marketplaces accelerates deal closure and increases deal sizes. Serving as a global B2B commerce engine, our marketplace empowers Microsoft partners to provide solutions to customers worldwide. It offers various sales models: digital direct, through partners or with Microsoft — providing flexibility to align with how customers want to buy and how partners want to sell. Learn more in this recent blog.

Unlocking success through skilling and events

The speed of technology innovation requires continuous learning. To support this, we offer our partners a variety of skilling opportunities, such as our popular in-person Microsoft AI Partner Training Days, designed to help partners develop both technical and sales capabilities.

We are also streamlining and simplifying our skilling portals through initiatives like Microsoft Sales Titan (currently in private preview for CSP Accelerate partners and available for all partners in summer 2025), a program tailored to equip sales professionals with in-depth knowledge of Microsoft Threat Protection SKUs, empowering them to position themselves as industry leaders. Discover these and other skilling opportunities.

Looking ahead, we invite our partners to join us at Microsoft Build, taking place May 19–22, 2025. This flagship event offers an exclusive opportunity to explore the latest advancements in AI, learn how to work smarter and elevate your projects. Connect with peers, industry experts and Microsoft leadership while diving into the code and innovations that will shape the future.

“Schneider Electric and Microsoft have been driven by a shared vision of a world that is more electric and digital. We’re thrilled to celebrate Microsoft’s 50th anniversary and excited to continue pioneering innovative solutions together, harnessing the transformative power of AI, pushing the boundaries of what’s possible for our customers and shaping a sustainable future for generations to come.”

— Frédéric Godemel, Executive Vice President, Energy Management, Schneider Electric

Looking forward – the next 50 years

As we celebrate this remarkable milestone, we remain focused on and optimistic for the future. We continue to innovate, collaborate and empower our partners to thrive in the era of AI and beyond. The past 50 years have been defined by shared success, and this will continue for our future. Together, we will unlock new opportunities, drive transformation and shape the future of technology.

Throughout this journey, stories of innovation have inspired us. A few examples of how partners are celebrating our 50th anniversary are included in this blog. See the full list of partner quotes on the Microsoft 50^th Anniversary celebration site.

Thank you for being an integral part of our story. We can’t wait to see what we’ll accomplish together next!

*IDC: Microsoft Partners: Driving Economic Value and AI Maturity

 **“Solutions Partner” refers to a company that is a member of the Microsoft AI Cloud Partner Program and may offer software, services, and/or solutions to customers. Reference to “Solutions Partner” in any content, materials, resources, web properties, etc. and any associated designation should be not interpreted as an offer, endorsement, guarantee, proof of effectiveness or functionality, a commitment or any other type of representation or warranty on the part of Microsoft. All decisions pertaining to and related to your business needs including but not limited to strategies, solutions, partner selection, implementation, etc. rest solely with your business. 

 ***A certification is (A) specific to the solution’s interoperability with Microsoft products and (B) based on self-attestation by the solution owner. Solutions are only certified as of the date the solution is reviewed. Solution functionality and capability are controlled by the solution owner and may be subject to change. The inclusion of a solution in marketplace and any such designations should not be interpreted as an offer, endorsement, guarantee, proof of effectiveness or functionality, a commitment or any other type of representation or warranty on the part of Microsoft. All decisions pertaining and related to your business needs including but not limited to strategies, solutions, partner selection, implementation, etc. rest solely with your business.

The post Microsoft at 50: The journey and future of the partner ecosystem appeared first on Microsoft AI Blogs.

For over two decades, we have consistently delivered front-end speech capabilities that have helped clinicians document billions of patient records and that have become a cornerstone of clinical documentation. Five years ago, we took a significant leap forward by pioneering the ambient AI category in healthcare. Today, we announce the integration of these proven technologies with fine-tuned generative AI, healthcare-adapted safeguards, and new capabilities on a scalable platform. This powerful combination brings unprecedented levels of efficiency and care, offering wide-reaching benefits for all.

Our robust voice solutions have consistently delivered outcomes for clinicians, patients, and healthcare organizations. Outcomes like 5 minutes of time-savings per encounter on average that have enabled 13 additional appointment slots per provider, per month.¹ A 70% improvement in clinician work-life balance and reduction of feelings of burnout and fatigue.¹ And the delivery of better patient experiences, where 93% of patients say their physician is more personable and conversational due to our technology.²

Dragon Copilot builds on this evolution to streamline documentation, surface information, and automate tasks across care settings. It’s an AI extensible workspace that offers a unified experience, integrates with electronic health records (EHRs) such as Epic, and supports clinicians across all stages of their workflow. Part of Microsoft Cloud for Healthcare, it’s built on a secure, modern architecture and can take clinical productivity to new heights while helping boost clinician wellbeing and the patient experience, increasing efficiency, and improving financial impact.

Streamline documentation with new levels of customization

Dragon Copilot uses the latest AI models to help produce accurate documentation efficiently and consistently.

• Create clinical documentation automatically: Captures multiparty, multilingual patient-clinician conversations and orders ambiently during the visit and converts them into high quality, comprehensive, specialty-specific notes allowing clinicians to connect with patients rather than screens.
• No internet? No problem: Recordings are captured and processed once users are reconnected. 
• Produce high quality, customizable documentation: Allows clinicians to customize documentation, save templates, AI prompts, and frequently used text.
• Talk naturally: Provides natural language speech capabilities, dictation at the cursor, custom vocabularies, and intuitive voice correction capabilities across devices.

Surface information without leaving your workflow

From querying notes and getting medical information to receiving encounter recording suggestions, Dragon Copilot gives users access to pertinent information when they need it.

• Query notes: Provides details and answers questions like whether a patient is taking a certain medication, has a relevant family history, or mentioned something specific during the conversation. Copilot uses conversation transcripts and notes to address your requests.
• Get credible medical information: Clinicians can access a broad range of medical information and clinical topics, allowing them to check the latest protocols for managing a condition or check drug interactions, for example. Dragon Copilot uses grounded AI with citations to ensure trust in its responses.
• Receive suggestions: Create more complete notes. Dragon Copilot analyzes the transcript and makes suggestions to help clinicians capture specific information, such as temperature, BMI, and family history.
• Put conversational data to good use: Get insights at scale with Microsoft Fabric and Dragon Copilot. Tap into point-of-care data to better analyze usage and adoption and help improve research, patient care, engagement, outreach, and more.

“Using all these tools together is going to be a great in-room, in-office assistant for taking care of the patient. It’s just remarkable.”

Dr. Lance Owens, Chief Medical Information Officer, University of Michigan Health-West

Automate tasks with a single click

Dragon Copilot helps clinicians automate clinical and non-clinical tasks. From summarizing notes and evidence, to prepping orders and drafting referral letters and after visit summaries, it saves time and increases clinician productivity and efficiency.

• Make orders easy: Automatically capture over a dozen order types during clinician-patient conversations. With supported EHRs, orders are directly entered into the EHR order module. 
• Summarize notes: Get an instant synopsis of each encounter, including key facts and details, streamlining workflow and reducing cognitive load. Dragon Copilot makes it easy to get a quick refresher on the patient before finalizing a note.
• Summarize evidence: Receive more than just linked notes to transcripts. Dragon Copilot curates diagnosis evidence from subjective elements such as symptoms, objective elements such as labs and imaging, and other relevant information shared during the encounter.
• Create referral letters: Have Dragon Copilot quickly draft a referral letter from clinical notes by using the information gathered during an encounter. It automatically extracts key details—including medical history, requested services, and pertinent test or imaging results—and repurposes them for the letter.
• Generate after visit summaries: Dragon Copilot converts clinical documentation from encounter visits into written patient-friendly after-visit summaries, providing an easy reference for key clinical highlights and important directions.

“This is a complete transformation… it’s going to make it easier, more efficient, and help us take better quality care of patients.”

Dr. Anthony Mazzarelli, Co-President and Chief Executive Officer, Cooper University Health Care

True anywhere access

From a full-featured web app with no client installation, to dedicated mobile and desktop apps with added functionality, Dragon Copilot goes wherever you go. And for even greater workflow efficiency, Dragon Copilot is natively embedded in supported EHRs.

Access in-app training and support—whenever and wherever it’s most convenient

Dragon Copilot offers some of the best product support and insights to help healthcare organizations get the most out of their AI investment.

• On-demand training: In-app training videos and on-demand content provide access to training content.
• Integrated live chat and virtual support room: Need help? Dragon Copilot comes with immediate support without leaving the app and a virtual support room staffed by experts.
• Product and AI feedback: In-app feedback and dedicated channels enables clinicians to rate Dragon Copilot and provide feedback that helps improve the product experience, note quality and AI responses.

Our expansive partner ecosystem

Dragon Copilot is bolstered by our collaboration with healthcare industry experts across our global ecosystem of trusted partners. We work with leading independent software vendors (ISVs), system integrators (SIs), and cloud service providers (CSPs) so our customers in every region can access the healthcare solutions and offerings they need.

Dragon Copilot is coming to you

Dragon Copilot is generally available in the United States and will be generally available June 1, 2025 in Canada, except for the province of Quebec. General availability in the Canadian province of Quebec, will follow later this year with international market expansion to the United Kingdom, Germany, France, and the Netherlands.

Built on a foundation of trust

We are dedicated to helping customers use and build AI that is trustworthy, secure, safe, and private. By using the Microsoft Secure Future Initiative, we support the highest standards of security, privacy, and compliance. Our AI aligns with Microsoft’s responsible AI practices and incorporates healthcare-specific clinical, chat, and compliance safeguards to ensure accurate and safe outputs. Additionally, our data is grounded in privacy principles, backed by transparent policies, and protected by rigorous safeguards.

“Microsoft has invested a lot in security. It gives me peace of mind that Dragon Copilot is part of the whole Microsoft suite.”

Novlet Mattis, Senior Vice President, Chief Digital and Information Officer, Orlando Health

Ready to take the next step?

• Visit us at HIMSS Booth #2221.
• Not attending HIMSS 2025? Join us for our livestream event.
• Learn more on Dragon Copilot.
• Explore the latest with our new healthcare AI models.

Dragon Copilot

A new groundbreaking solution that transforms the way clinicians work

Discover more

¹ Microsoft survey of 879 clinicians across 340 healthcare organizations using DAX Copilot; July 2024.

² Survey of 413 patients conducted by multiple healthcare organizations whose clinicians use DAX Copilot; June 2024.

The post Meet Microsoft Dragon Copilot: Your new AI assistant for clinical workflow appeared first on Microsoft AI Blogs.

Epic® on Azure

Get started

Azure for mission-critical workloads

Migrating EHR systems to Microsoft Azure provides healthcare organizations with a robust platform for mission-critical workloads, ensuring optimized performance, fast data access, built-in disaster recovery, and enhanced security features, such as AI-powered threat detection and automated compliance monitoring. On top of that, Azure maximizes cloud investments, offering new possibilities to harness data to springboard AI innovations.

Data is at the heart of healthcare. Hospitals produce more than 50 petabytes of data across more than 10 siloed systems every year. As the healthcare industry faces the dual challenges of managing vast amounts of unstructured data and a shortage of workforce, up to 97% of healthcare data goes unused, highlighting a significant missed opportunity for operational excellence and better patient insights.¹ One of the biggest benefits for healthcare customers on Azure is the ability to unify their multi-modal healthcare data for analytics and AI with healthcare data solutions in Microsoft Fabric that lets them ingest, store, and analyze data from various sources and modalities. While Fabric unifies your data, Microsoft Purview delivers the data governance service that helps you classify the data across your data estate, including identification for sensitive data. Integrating Microsoft Purview with healthcare data solutions in Fabric not only strengthens security but also help you ensure compliance, enabling healthcare organizations to govern their data with confidence. We are acutely aware of the industry expectations in which our technology is utilized, and this is one of the many reasons why our healthcare customers trust Azure for mission-critical workloads.

As we continue to deliver data innovations, we see our customers use their connected data on a wide spectrum of AI capabilities. With Azure AI, healthcare organizations can accelerate innovation through predictive analytics, automate clinical tasks, and improve patient interactions with the help of ambient AI solutions like DAX Copilot (directly embedded in EHR systems), as well as take advantage of Microsoft healthcare AI models in Azure AI Foundry and GitHub, a collection of cutting-edge multi-modal generative AI models that benefit imaging and radiology workflows.

Enhanced support for mission-critical

Mission-critical workloads demand comprehensive support. In 2024, Microsoft Unified enhanced its support for mission-critical workloads in healthcare through its Mission Critical Offerings. This initiative provides proactive support to improve the health, resiliency, and performance of healthcare systems via regular assessments, guidance, and optimization recommendations, ensuring business continuity and addressing unique healthcare challenges.

Collaborating for technology excellence: A strategic partnership that stands out

Our commitment to mission-critical is reflected in our collaborations with leading EHR providers such as Epic®. This long-standing relationship of more than 20 years has yielded an optimized solution for Epic® on Azure, offering a robust, purpose-built platform backed by joint-reference architecture. Recently, Microsoft announced expanded scalability on Azure for healthcare organizations, specifically for running Epic®’s Chronicles* Operational Database (ODB), increasing its capacity to 65 million global references per second (GRefs/s), a 171% enhancement from 2023 on the new Mbv3 VM series.

The collaboration with Epic® extends well beyond the cloud infrastructure—to several products and capabilities part of Microsoft Cloud for Healthcare. Epic® and Microsoft have expanded their collaboration to integrate advanced AI technologies such as Microsoft Azure OpenAI Service and the DAX Copilot into Epic®’s EHR system. The integration helps provide AI-powered clinical insights, streamline administrative processes, and improve clinician productivity through features like note summarization and automated coding suggestions.

Delivering value beyond infrastructure: The Microsoft Cloud for Healthcare promise

Microsoft’s well-rounded partnership with Epic® is one of the many reasons why Azure is the cloud of choice for many of our healthcare customers.

The decision to move mission-critical workloads to the cloud is often not just about infrastructure. Customers like Mercy chose Azure to not only modernize their infrastructure but also extract value from sizeable data archives. Mercy’s digital transformation on Azure enabled it to connect previously siloed data and use several Microsoft services such as Azure Data Lake to result in positive business outcomes. For example, by empowering care teams with smart dashboards and insights into factors that determine patient discharge, Mercy has been able to reduce patient stay durations significantly. Mercy employs Azure AI Document Intelligence to scan and recognize information on patient’s insurance cards which then gets updated on their EHR records automatically.

We recognize our customer’s desire to have a complete digital transformation in the cloud that transcends every layer of the stack, and Microsoft Cloud for Healthcare lets us deliver to that promise. It encapsulates a broad spectrum of innovative data and AI innovations from Microsoft, purpose-built for the healthcare industry, enabling our customers to achieve their cloud-first goals faster and easier. Recently, Microsoft announced several innovations as part of the portfolio, including new healthcare AI models in Azure AI Foundry, capabilities for healthcare data solutions in Microsoft Fabric, the healthcare agent service in Copilot Studio, and an AI-powered nursing workflow solution.

As customers realize the value of consolidating their IT investments around a single vendor, Azure is increasingly being adopted for mission-critical workloads. By seamlessly connecting and delivering value across all layers of the stack, Azure for mission-critical extends a customer’s return on cloud investments. Customers like St. Luke’s University Health System are reaping the benefits of their Epic® on Azure migration by taking advantage of several synergies in the Microsoft portfolio, like the interoperability of Microsoft Teams with Epic®. Security is of paramount importance when dealing with patient records, and customers like Jefferson Health migrate their Epic® environments to Azure with high confidence with Microsoft Defender for end-point detection and response.

Next steps

As we continue to transform mission-critical workloads in the cloud, we are making it easier for our partners and customers to create connected experiences at every point of care, empower their healthcare workforce, and unlock the value from their data, all with uncompromised privacy and security. Microsoft Cloud for Healthcare is supporting healthcare organizations on every step of their journey toward shaping a healthier future.

• Explore Epic® on Azure.
• Learn more about the Mbv3 VM series.
• Learn more about Microsoft Cloud for Healthcare.

*Epic® and Chronicles are trademarks of Epic Systems Corporation.

¹ World Economic Forum, 4 ways data is improving healthcare, December 2019.

The post Azure for mission-critical workloads in healthcare: EHR and beyond appeared first on Microsoft AI Blogs.

Microsoft, in collaboration with its partners like Sight Machine, is at the forefront of addressing this challenge. Advanced AI technologies and solutions integrated into platforms like Microsoft Fabric are transforming the way manufacturers handle plant floor data. These initiatives aim not only to assist manufacturers in managing data more efficiently but also to fully use industrial data to enhance productivity, improve efficiency, and achieve cost savings.

Microsoft Cloud for Manufacturing

Design, build, and operate with AI

Explore solutions

Tailoring small language models for manufacturing

In AI, small language models and large language models serve distinct purposes, each offering unique advantages. Small language models are specialized and efficient, focusing on specific tasks or domains. This specialization allows small language models to provide highly accurate and relevant insights tailored to industries such as manufacturing. Due to the smaller size, small language models require fewer computational resources, making them more cost-effective and faster to deploy. This efficiency is crucial in manufacturing environments where real-time data processing and decision-making are essential. 

Large language models, on the other hand, are general-purpose models trained on vast amounts of data, making them versatile but also resource intensive. While large language models excel in scenarios requiring broad language understanding, they can be less precise for specialized tasks. 

Fine-tuning small language models can enhance their performance for specific tasks by customizing pre-trained models with additional training on targeted datasets. This approach allows small language models to achieve higher accuracy and relevance in their designated areas, making them more effective for specialized applications like manufacturing. Fine-tuning is also more cost-effective and efficient compared to training large language models from scratch, as it requires fewer computational resources and reduces operational costs. One of the key advantages of fine-tuning is the ability to control the model’s responses. Fine-tuned models are optimized for specific tasks, ensuring consistent and predictable behavior. This is crucial for applications where precise and reliable outputs are necessary.  

For example, in manufacturing, fine-tuned models can be tailored to understand and respond accurately to industry-specific terminology and requirements. Fine-tuning also allows for better implementation of responsible AI practices, preventing unintended behaviors and ensuring models adhere to ethical guidelines. Using Microsoft Azure OpenAI Service, manufacturers can fine-tune small language models to address unique challenges. 

Factory Namespace Manager: A cost-effective, efficient AI solution 

Microsoft partner, Sight Machine, has developed Factory Namespace Manager, a small language model specifically for manufacturing, using a fine-tuned version of Phi-3.5 SLM. Factory Namespace Manager is among the first partner-enabled adapted AI models for manufacturing available in the Microsoft Azure AI Foundry model catalog. It addresses a critical data governance challenge in the manufacturing industry: the standardization of factory data naming conventions. In many manufacturing environments, data is generated from a wide variety of sensors, machines, and systems, each with its own naming schema. This lack of standardization can lead to significant difficulties in managing and integrating data across different sources.  

Factory Namespace Manager solves this problem by using AI to map the multitude of factory data naming schemas into unified corporate-standard namespaces or data dictionaries. This process enables manufacturers to integrate factory data with enterprise data systems, facilitating end-to-end optimization and improving overall operational efficiency. By creating a unified namespace, the tool helps ensure that data from different sources can be easily understood, analyzed, and utilized for decision-making. 

“Our solution addresses a widespread challenge in the manufacturing industry, converting decentralized naming systems into a single corporate standard. This has become an acute problem as more clients push factory plant floor data to the cloud, removing data from its original context, and making the management of that data increasingly difficult.”

Kurt DeMaagd, Sight Machine Chief AI Officer and Co-Founder

This solution is particularly valuable for companies with extensive and diverse data sources from multiple generations of machinery, which often lack standardized labeling. Factory Namespace Manager makes it easier to manage and leverage this data, ultimately enhancing productivity and reducing the complexity of data management. By using AI, this tool bridges a significant gap in technology, enabling the mapping between original data field names and corporate standards. This capability allows manufacturers to seamlessly integrate factory data with enterprise data systems, facilitating end-to-end optimization. 

The additional fine-tuning of AI models within Factory Namespace Manager helps affirm the tool can adapt to specific manufacturing environments and data sets, enhancing its accuracy and effectiveness. By adhering to principles of responsible AI, such as fairness, transparency, and accountability, the tool not only improves operational efficiency but also ensures ethical and trustworthy AI deployment in manufacturing. 

“We really came to appreciate the importance of responsibly trained models. Even when dealing with seemingly mundane manufacturing data, it was essential to apply responsible AI principles correctly to prevent models from misbehaving. Support and guidance from Microsoft helped us improve the efficiency of fine-tuning and helped ensure the models developed were robust and reliable.”

Kurt DeMaagd, Sight Machine Chief AI Officer and Co-Founder

More innovative tools  

Sight Machine and Microsoft have developed additional innovative tools aimed at enhancing manufacturing productivity and efficiency.  

• Sight Machine Manufacturing Data Platform (MDP): This platform integrates easily with various Microsoft products, capturing the entire manufacturing process in a single, secure industrial data foundation. It contextualizes all plant data and incorporates data from all sensors, machines, lines, and plants operated by a company. The MDP provides a single source of truth on production, enabling continuous system-wide analysis and insights. By integrating with Microsoft Fabric, Sight Machine enables manufacturers to combine and analyze contextualized production data with financial, supply chain, enterprise resource planning (ERP), and manufacturing execution system (MES) data. This comprehensive approach allows for unprecedented levels of knowledge and enterprise-wide insight. 
• Factory CoPilot: This tool democratizes industrial data through the power of generative AI. By integrating Sight Machine’s Manufacturing Data Platform with Azure OpenAI Service, Factory CoPilot offers an intuitive “ask the expert” experience for all manufacturing stakeholders. It provides real-time insights, root cause analysis, and user-friendly reports—helping to diagnose issues and improve manufacturing processes. 
• Sight Machine Blueprint: Developed in collaboration with NVIDIA and Microsoft, this tool uses AI for high-speed, automated data labeling. It enables manufacturers to analyze up to 100 times more data, providing deeper insights and improving decision-making. Microsoft Cloud for Manufacturing is at the forefront of this evolution, offering a suite of tools and services designed to address the unique challenges that manufacturers face.  

Learn more 

• Discover more about Microsoft Cloud for Manufacturing. 
• Learn more about Factory Namespace Manager.  

The post The future of manufacturing: AI for data standardization appeared first on Microsoft AI Blogs.