As operators move from experimentation to execution, the opportunity is not just to adopt more AI, but to build systems that combine intelligence with trust across networks, data, and customer operations. TM Forum DTW Ignite 2026 focuses on how those capabilities come together to drive measurable business outcomes.

Composable IT and ecosystems

Complexity continues to slow progress across telecom. Tightly coupled systems, fragmented integration paths, and years of technical debt make it harder to launch new services, adapt quickly, and deliver consistent experiences across channels.

TM Forum continues to position Open Digital Architecture as both a practical migration path away from legacy complexity and the architectural foundation for AI-native operations, with tools, standards, Open APIs, and reusable components designed to support more modular, cloud-native, and interoperable platforms.

That is why the Composable IT and Ecosystems summit sits so centrally in this year’s event: it reflects a broader industry shift from digital transformation as a long-running aspiration to reinvention for the AI era, where openness, composability, and governance become prerequisites for scaling intelligent operations.

For operators, the value is practical. Modular environments make it easier to modernize in stages, improve interoperability across business and network domains, and create a stronger foundation for ecosystem plays such as CAMARA and Open Gateway. This is where solutions such as Infobip’s Network API offering become relevant—helping operators turn standardized capabilities like number verification, SIM swap detection, and device location into practical services that expand revenues, strengthen trust, reduce fraud, and reach more developers.

With Microsoft, teams can standardize platforms, simplify integration, and create an environment where new capabilities can be introduced with greater speed and confidence.

That conversation will continue in the panel discussion “The AI-Native ODA Roadmap.” The session will explore how operators can build AI-native operations on common foundations across IT and networks, with emphasis on interoperability, governance, reusable patterns, and business value. It is a timely example of how TM Forum DTW Ignite 2026 is connecting architectural change to the strategic and operational priorities telecom leaders are navigating now.

That same modernization path is also reshaping the business side of telecom through Agentic Business Support Systems (BSS). Instead of hard-coded workflows, operators can use AI agents to interpret intent, orchestrate actions across catalog, ordering, billing, and care, and accelerate the path from request to resolution.

With Microsoft, TM Forum Open APIs, and a composable architecture, BSS can evolve into a more adaptive, outcome-driven system that enables faster service creation, stronger customer experiences, and new monetization opportunities across the ecosystem.

This direction is reinforced by recent Microsoft Build 2026 announcements, where capabilities such as Work IQ and Agent 365 introduce a consistent way to ground AI agents in enterprise context, apply governance by design, and orchestrate actions across systems. Together, these capabilities make it easier for operators to move from isolated automation to agent-driven workflows that are composable, secure, and production-ready at scale.

This evolution also reflects the emergence of more persistent, context-aware agents—exemplified by experiences such as Microsoft Scout—that can operate continuously across tasks and systems, moving from reactive copilots to proactive digital coworkers that help coordinate work across the enterprise.

Autonomous networks

The industry is moving beyond manual processes toward systems that can interpret signals, recommend next actions, and automate response within clear controls. That shift sits at the heart of the Autonomous Networks summit at DTW Ignite 2026, where the focus is on how operators can make autonomy practical in day-to-day operations.

AT&T offers a strong example for incident management. By improving observability, creating better context across operational data, and accelerating the path from detection to action, operators can improve reliability and shorten the time between issue discovery and resolution. Microsoft supports this direction with cloud-scale data services, AI capabilities, and a platform approach that helps teams operationalize intelligence rather than isolate it in pilots.

 Microsoft’s Network Operations Agent (NOA) framework extends this vision by enabling operators to deploy coordinated AI agents across network operations—helping interpret signals, orchestrate actions, and drive closed-loop automation with greater consistency and control.

The broader direction is clear. Operators are moving toward more predictive operations, more intelligent assurance, and more trusted automation that improves resilience, experience, and efficiency.

AT&T will also bring this story to the Park stage at DTW Ignite 2026, where the discussion is expected to highlight how End-to-End Incident Management uses current context, observability, and AI to move faster from detection to action. It adds a timely, customer-led example of how operators are applying agentic decision-making to improve reliability, reduce disruption, and make autonomy more practical in live network operations.

By bringing more context and intelligence into incident management, we are improving how quickly teams can identify issues, coordinate response, and restore service with confidence. This type of advanced agentic technology is helping us keep our customers connected and provide a better experience for them.

—Mark Austin, Vice President Data Science, AT&T

Underpinning this shift is the emergence of unified data and AI platforms that can ground agents in real-time operational context. With Microsoft Foundry and Foundry IQ, its knowledge layer, operators can connect data across network, service, and customer domains, enabling agents to reason more effectively and support closed-loop decisioning that moves from insight to action with greater speed and consistency.

Microsoft’s recent work in Azure Networking operations adds an important operational lens to this shift. Rather than treating agents as simple assistants, the model is evolving toward more persistent digital coworkers that help coordinate the messy middle of operations across incidents, repairs, vendors, and validation steps. In large-scale environments, that can reduce manual effort, shorten mitigation time, and free engineers to focus more on judgment, oversight, and higher-value decisions while agents keep execution moving across systems and teams.

Trustworthy AI and data

AI creates value only when it is grounded in trusted data, strong governance, and a clear path to action. In telecom, that standard matters because operators work in highly regulated environments and depend on reliable decision-making across critical services.

That is why the Trustworthy AI and Data summit at DTW Ignite 2026 matters. The conversation is not only about model capability. It is about data readiness, governance, observability, and the controls required to scale AI responsibly across the business.

This is reinforced by Microsoft’s perspective on local AI, where operators extend the AI execution model closer to where data is generated—improving latency, resiliency, and control while keeping data private. Running inference locally or at the edge can also shift the cost profile, reducing dependency on centralized compute for time-sensitive or high-volume workloads while enabling new real-time scenarios.

SoftBank brings that point into focus through its AI-powered customer platform, where the value shows up in responsiveness, service quality, and workload reduction. In its work with Microsoft, SoftBank is applying Microsoft Foundry, Azure OpenAI in Foundry Models, Azure AI Search, and Semantic Kernel to help build a more intelligent call center experience that reduces wait times, improves response quality, and supports more scalable customer operations. The example reinforces that AI success depends on the right data foundation and a disciplined link to measurable outcomes.

Microsoft sees telecom ontologies as an important part of the foundation for trustworthy AI. By creating a shared semantic model across network, service, customer, and operations data, they help AI systems reason with more context, improve explainability, and support more consistent decisions across domains. Combined with Microsoft Fabric as the unified data foundation, Fabric IQ as the intelligence layer, and Microsoft’s broader data and AI platform, that structure can help operators reduce fragmentation and move with greater confidence from isolated use cases to governed, reusable intelligence.

That theme will also come through in Alberto Manuel Fernandes Dias’ panel, “Data products at scale—the blueprint for AI-native telcos.” The discussion reinforces that scaling AI in telecom depends on more than models alone. It requires well-designed data products, clear ownership, and disciplined governance to turn fragmented information into reusable, high-quality, and AI-ready assets. For operators, that blueprint matters because it creates the consistency, trust, and lifecycle discipline needed to support autonomy at speed and scale.

Accelerating transformation through partner innovation

Transformation in telecom does not happen in isolation. Across TM Forum DTW Ignite 2026, Microsoft and its partners are working together to help operators modernize networks, simplify operations, and bring AI into real business processes.

From composable IT and cloud-native BSS modernization to agentic marketplaces, digital twins, and voice AI pilots, these collaborations reflect how the industry is moving from experimentation to scalable, outcome-driven innovation.

• Amdocs is highlighting continued momentum in cloud-first modernization through its expanded work with Lumen, helping accelerate enterprise billing transformation on Microsoft Azure. Separately, Amdocs is also showcasing how its Entitlement Server on Azure is setting new performance benchmarks for digital service delivery, reinforcing the value of scalable, AI-ready cloud infrastructure for telecom providers.
• Beyond Now is also demonstrating how AI is reshaping telecom monetization through its work on agentic marketplace experiences. In collaboration with Microsoft, the company is highlighting how operators can use intelligent automation and AI-powered ecosystems to accelerate service innovation, streamline partner engagement, and unlock new digital revenue opportunities.
• Kenmei is advancing how operators can make network data more usable for AI-powered operations through its new Network Performance Data Product built on Microsoft Fabric. Running natively in Azure, the solution combines governed network KPIs with a telecom ontology layer, helping operators accelerate agent-ready use cases while keeping data secure, unified, and under their own control.
• By integrating Nokia Data Suite with Microsoft Fabric, operators can access on-demand telecom data products that simplify data integration across complex, multi-vendor environments. This unified data foundation enables faster adoption of AI, generative AI, and automation, supporting the journey toward autonomous networks.
• Norwood is demonstrating how voice AI is becoming more practical for telecom providers through its OpenSpan Voice platform. In collaboration with Microsoft, the company is piloting AI-powered small and mid-sized businesses (SMB) voice capabilities with a major United Kingdom and Australian telecommunications provider, demonstrating how operators can deliver more intelligent, responsive customer communication experiences at scale.
• Tech Mahindra and Microsoft are advancing telecom innovation with a 5G Network Digital Twin, an intelligent virtual replica that enables AI-powered optimization, proactive issue resolution, and new monetization opportunities. Built on Microsoft Azure and Fabric, the solution unifies data, simulates network scenarios, and drives measurable impact across cost efficiency, network slicing, service assurance, and autonomous operations, while maintaining enterprise-grade governance and data sovereignty.

Customer momentum: From blueprint to production

The strongest signal in telecom today is that customer stories are moving from blueprint to production. Leaders want to see where transformation is working in practice and where AI is delivering value beyond the pilot stage.

• MEO stands out because its modular AI factory connects strategy to execution, giving the company a more repeatable path to scale new use cases across the business. AT&T highlights the operational side of the story, with incident management illustrating how better data and more intelligent workflows can improve detection, triage, and resolution.
• TIM Brazil adds a security-focused example, showing how integrated signals and intelligent protection can strengthen operational resilience while reducing noise and improving response. Together, these examples show how operators are turning transformation into something more tangible, operational, and repeatable.

TM Forum also shows how quickly AI can move from experimentation to scaled impact. Using Microsoft 365 Copilot and Microsoft Copilot Studio, the organization moved rapidly from early pilots to production with internal and member-facing agents. Its cross-functional productivity agent, Buddy, is already delivering measurable ROI across multiple departments, while Navigator—launched in time for TM Forum DTW Ignite 2026—simplifies access to standards and articles for members. The result is a strong example of how AI can improve internal productivity, strengthen knowledge access, and create a foundation for broader support across the innovation cycle, from catalyst to production.

That momentum is visible across the telecom landscape. Recent public examples show operators using Copilot to strengthen leadership decision-making, workforce productivity, and sales execution—from Singtel and Ooredoo Qatar to KPN—while large-scale deployments across Accenture, Cognizant, Infosys, TCS, and Wipro reinforce how quickly the supporting ecosystem is scaling the skills, services, and implementation capacity needed to help enterprises and operators move from pilots to broader adoption. Together, they point to the same shift: AI is becoming part of day-to-day work, with measurable impact on speed, decision quality, and business outcomes.

That is why TM Forum DTW Ignite 2026 feels timely. Innovation matters, but adoption matters more. The next chapter of telecom will be shaped by operators that can turn transformation into repeatable outcomes.

Join us in Copenhagen

TM Forum DTW Ignite 2026 arrives at a pivotal moment for the telecom industry. TM Forum has structured the event around three mission summits all designed to help operators move from ambition to real change:

• Composable IT and Ecosystems
• Autonomous Networks
• Trustworthy AI and Data

We look forward to continuing these conversations in Copenhagen and sharing how Microsoft, together with customers and partners, is helping telecom organizations translate strategy into measurable progress. In the end, the next chapter of telecom will be shaped by operators that can pair intelligence with trust at scale.

Microsoft for telecommunications

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The post TM Forum DTW Ignite 2026: From strategy to execution in the AI era of telecom appeared first on The Microsoft Cloud Blog.

Across industries, CMOs are no longer asking whether AI will transform marketing but how fast they can move from experimentation to impact, and how to re‑architect work so AI shows up where decisions are actually made.

That question sat at the center of Microsoft’s CMO AI Innovation Forums, convened at CES and Cannes Lions, and designed for one purpose: helping marketing leaders navigate Frontier Transformation—the shift from tools and pilots to AI embedded in the flow of work, driving measurable business outcomes.

Frontier Transformation starts in the flow of work 

In the months between Cannes Lions last year and CES, it’s incredible to see how much things have changed. Six months ago, the question was “Where can we use AI?”Today, it’s “How do we make it deliver real business value—and prove it?” As we head toward Cannes again, the bar has moved even higher. The era of experimentation is over. Boards and CEOs are no longer interested in pilots—they’re expecting tangible outcomes: monetization, measurable growth, and a clear line from AI investment to business impact.

At the same time, most organizations aren’t set up to deliver that. At least not yet.

CMOs described teams juggling 25–30 disconnected applications, with AI pilots layered on top but rarely integrated end-to-end. The result is predictable: disconnected workflows, inconsistent insights, and limited scale. But the real challenge runs deeper than the tech.

What we’re hearing consistently from marketing leaders is this: AI initiatives fail when they are contained to a single function. You can succeed in marketing, but if your workflows aren’t connected to other functions in the enterprise, you will fail.

That’s why the next phase of transformation isn’t about deploying AI around the business it’s about embedding it through the business. Because ultimately, AI transformation is business transformation.

And let’s face it the stakes are rising fast:

• Monetization is mission-critical. AI investments must tie directly to revenue acceleration, margin expansion, or customer lifetime value not just productivity gains.

• Agentic commerce is reshaping the funnel. Discovery, consideration, and even purchase decisions are increasingly intermediated by AI agents disrupting traditional attribution models and forcing CMOs to rethink influence altogether.

• Trust is becoming a defining brand asset AND competitive advantage. As AI-generated interactions scale, consumer confidence in data usage, content authenticity, and brand integrity becomes a competitive differentiator.

• Measurement needs a reset. Legacy metrics can’t capture AI-driven, non-linear journeys. We need new protocols that reflect intent-based engagement, agent participation, and real-time orchestration.

CMO efforts are accelerating

So, as we think about how these shifts are impacting the role of CMOs, I wanted to bring you inside these CMO forums and share what leading CMOs are doing differently. These leaders aren’t hesitating. In fact, quite the opposite. They’re accelerating the integration and operationalization of AI in an effort to rewire processes and supercharge their people. Four patterns are emerging:

1. Measuring AI value is now non‑negotiable, but still unresolved

Efficiency and time savings are table stakes. CMOs are under pressure to tie AI directly to growth, effectiveness, and enterprise outcomes. To do this, they are moving beyond proxy metrics (time saved, content produced) toward value-based measurement frameworks, including:

• Linking AI-driven personalization to incremental revenue lift and conversion quality.
• Measuring speed-to-market as a competitive advantage, not just an operational KPI.
• Understanding how to measure attribution with agentic commerce increasingly mediating the buying journey.

CMOs are in agreement that measuring productivity and effectiveness end-to-end is a critical, unresolved issue.

2. Cross-functional workflows matter more than functional excellence

Marketing wins alone are no longer enough if sales, commerce, service, and supply chains are not connected. Leading organizations are:

• Embedding AI into end-to-end demand-to-fulfillment processes, not just campaign execution.
• Connecting marketing signals directly into sales prioritization, supply chain planning, and service resolution.
• Using AI to orchestrate real-time decisioning across functions, not just optimize within silos.

We have learned that you can knock it out of the park in marketing and still fail if the other organizations aren’t connected.

3. AI is changing who marketers serve—and how

It’s clear that we are no longer just marketing to consumers. This introduces a profound shift: 

• Brands must optimize not just for human attention, but for machine comprehension and recommendation.
• Content strategies must evolve toward structured, verifiable information that AI systems can trust.
• Influence changes as what the model believes about your brand becomes just as important as what the customer sees.

Customer and consumer engagement is not limited to human audiences, but LLMs and agents shaping discovery, consideration, and purchase in real time.

4. Agentic AI exposes operating model gaps

As teams experiment with agents, undocumented processes, tribal knowledge, and governance gaps surface immediately—forcing a rethinking of roles, incentives, and accountability. Leading companies are taking decisive action:

• Redesigning roles around human + agent collaboration, not task ownership
• Establishing clear governance models for AI decision-making and accountability.
• Creating shared data and process standards to enable agents to operate reliably.
• Investing in trust frameworks—including transparency, explainability, and responsible AI practices.

The fourth bullet is especially important, as this is where trust becomes critical not just externally with customers, but also internally. Can teams trust AI outputs enough to act at speed? And can leaders scale AI without introducing risk to their brand?

The takeaway

Across all of these conversations, one thing is clear: CMOs don’t just need more technology. They need clarity. They need connection. And they need confidence in how to scale. They’re looking for real patterns, proven approaches, and practical pathways from pilots to enterprise value. That’s because the next chapter isn’t about experimenting with AI. It’s about operationalizing it across the business to deliver real, measurable impact.

The post The CMO on the frontier: From AI experimentation to AI at work appeared first on The Microsoft Cloud Blog.

The answer isn’t more tools. It’s what people are enabled to do with them.

The friction we see is that many people are unsure how to use AI to their greatest benefit. Companies often struggle to measure the impact of their AI investments because they likely haven’t yet demonstrated return on investment for their employees.

Progress comes when employees actively adopt AI and see meaningful impact on their work—when they’re confident about questioning outputs, applying judgment, and integrating it into their real work.

But there’s another layer to that friction.

Alongside the industry’s excitement and expectations, there’s real hesitation. AI still feels uncertain: Where do I start? Am I already behind? What if I get this wrong?

That hesitation is a signal that access alone isn’t enough; people need to feel confident that AI will elevate their work, not detract from it, or worse, make them irrelevant.

You aren’t behind; you just need to get started. And you do that by learning one new skill at a time. Even skeptics can become strong advocates if they start by learning how to use AI to do the traditional task they dislike most. Once they feel the inevitable benefit, they’re highly likely to try the next task they don’t like doing. From there, we often see a path of continuous learning.

Here’s what too few people realize: technology alone isn’t going to elevate their performance. When everyone knows how to use the tools, the differentiator will be their uniquely human skills that no AI tool can replace.

Human skills aren’t “soft”—they’re foundational

In the New York Times bestselling book Open to Work: How to Get Ahead in the Age of AI, the authors describe five human capabilities that no machine can replace: curiosity, compassion, creativity, courage, and communication.

That same idea extends beyond the individual—organizations aren’t abstract systems; they’re made of people.

What we often call “organizational skills” are simply human skills, practiced consistently and scaled intentionally.

From human potential to organizational capability

A new IDC InfoBrief sponsored by Microsoft, Powering Up: Human Skills for the AI Era,¹ highlights a familiar gap: organizations are investing heavily in AI tools but far less in the capabilities needed to turn them into value.

These capabilities span cognitive, collaborative, leadership, ethical, and business domains.

How do these skills scale? They come together across three levels:

1. Individual. How people think, decide, take risks, and act—especially when working with AI.
2. Teams. How those capabilities show up in collaboration and workflows.
3. Organization. What leaders reinforce through culture, systems, and governance.

This is where personal capability becomes organizational advantage.

How human skills scale in the AI era

The human skills explored in Open to Work don’t disappear at the organizational level; they show up differently at scale.

1. Curiosity: Cognitive and collaborative capability

At the individual level, curiosity starts with a desire to explore and learn what’s possible. At scale, this shows up as:

• Asking better questions to challenge assumptions.
• Exploring different approaches beyond the first answer.
• Sharing learnings across teams.

2. Compassion: Ethical and leadership capability

Compassion is empathy and awareness of impact. At scale, this shows up as:

• Applying ethical judgment and accountability.
• Identifying and addressing bias.
• Practicing responsible data use.

3. Creativity: Cognitive and business capability

Creativity isn’t about aesthetics. It’s about imagining what doesn’t yet exist. At scale, this shows up as:

• Framing problems more effectively.
• Creating new sources of value.
• Driving innovation beyond efficiency.

AI can optimize what exists. Humans decide what’s worth building next.

4. Courage: Cognitive and leadership capability

Courage starts with acting even when outcomes aren’t certain. At scale, this shows up as:

• Applying critical thinking and judgment.
• Making decisions in complex environments.
• Leading change without guaranteed outcomes.

5. Communication: Leadership and business capability

Communication starts with clarity and listening. At scale, this shows up as:

• Setting a clear vision for AI transformation.
• Translating technical capability into business meaning.
• Aligning teams across functions.

What leaders should consider next

Taken together, these examples point to a clear pattern: personal strengths become organizational advantage when they’re built at scale.

If human skills are the differentiator, how do we design for them intentionally? Three mindset adjustments matter most—especially in a moment where excitement about AI is often matched by hesitation about where to begin:

1. Focus on the work, not just the training
   • Human skills develop through real decisions, real collaboration, and real accountability—not one-off courses.
2. Model the behaviors consistently
   • What leaders practice signals what’s safe. Judgment, curiosity, empathy, and learning must be seen, not just stated.
3. Measure what actually changes outcomes
   • Beyond adoption, organizations need to track decision quality, trust and confidence, and cross-functional outcomes.

The real opportunity of AI

AI won’t make organizations less human—but it will raise expectations for how people think, decide, and work.

The organizations that succeed won’t be the most automated. They’ll be the ones that invest in people as intentionally as they invest in technology.

That’s the opportunity—and the work—in front of us.

Continue your learning journey

The future of AI won’t be defined by technology alone—it will be shaped by people who continue to learn, adapt, and grow. Whether you’re just getting started or looking to deepen your expertise, AI Skills Navigator can help you discover learning experiences and credentials that build both AI capabilities and the human skills that help turn knowledge into impact.

¹IDC InfoBrief, sponsored by Microsoft, Powering Up: Human Skills for the AI Era, Doc. US54451326-IB, May 2026.

The post AI needs more than intelligence—it needs humanity appeared first on The Microsoft Cloud Blog.

For years, nurse leaders and frontline nurses have generously shared their time, experience, and candor with us—helping guide how we think about technology, set priorities, and show up as a partner to the nursing profession. That sustained collaboration underscores the importance of aligning technology with the realities of nursing today and continues to inform Microsoft’s approach to supporting the nursing practice.

Honoring nurses through partnership and progress

To nurses everywhere: thank you.

Thank you for the care you deliver across long shifts and constant transitions. Thank you for the judgment calls made between alarms, handoffs, and documentation. And thank you for the partnership you have offered—sharing insights about what works, what doesn’t, and where healthcare must go next.

Over the years, nurses have helped surface some of the most pressing challenges in healthcare today:

• Increasing complexity of care
• Persistent staffing pressures
• Growing documentation burden
• The cognitive load of coordinating across distributed workflows
• The emotional toll of balancing efficiency with compassion

Their voices, lived experience, and willingness to share candid feedback have helped bring clarity and urgency to these challenges.

Nurses have consistently pushed assumptions and raised the bar for what supportive technology should look like. Their perspective has reinforced a simple but powerful truth: technology must fit the realities of nursing practice, not the other way around. That’s why we are continuing to take action—working alongside nurses to design solutions that bring meaningful relief to the operational, cognitive, and emotional demands of day-to-day practice.

Turning insight into action has meant spending time alongside nurses during real shifts—observing handoffs, documentation workflows, and care coordination in practice—and using that input to shape support in the moments that matter most.

Built with nurses—guided by decades of clinical trust

Microsoft’s work to support nurses builds on decades of clinical innovation—supporting care teams through technologies that strengthen communication, coordination, and access to information across care settings. Through this work, we’ve developed a disciplined approach to designing technology that aligns with how care is delivered in practice. Over time, health systems challenged us to apply that same rigor to relieving administrative burden within nursing workflows—grounded not in physician‑oriented tools, but in purpose‑built solutions designed around the unique realities of nursing practice.

That focus intensified through hands‑on co‑innovation with healthcare systems, where nursing leaders were unequivocal: workforce strain and administrative burden require urgent action—not observation. Instead of starting with a predefined solution, we worked side-by-side with nurses—designing in real care environments, testing during live workflows, and learning quickly. That sustained collaboration established nursing as a long‑term focus for digital and AI innovation, grounded in trust, relevance, and real clinical impact.

That momentum carried forward into deeper engagements with nurse leaders across the country, including industry forums and collaborative sessions where nurses identified practical opportunities to better support care coordination, communication, and wellbeing. These insights continue to inform how solutions evolve to support the full scope of nursing work.

Continuous feedback mechanisms have helped nurse voices remain central. The result is progress shaped not by a single program or moment, but by sustained partnership, iteration, and trust—reflected in solutions that increasingly align to how nursing work actually happens.

These stories reinforce why listening matters. They highlight the humanity of nursing work and the importance of building tools that support nurses without adding friction or complexity.

What’s new for nurses

Nurses deserve technology that works as hard as they do—respecting their expertise, valuing their time, and fitting naturally into care delivery. Progress isn’t just incremental improvement; it shows up when nurses can stay focused on patients, move more seamlessly across tasks, and leave a shift with less unfinished work and mental fatigue.

Purpose‑built with direct input from nurses, recent advancements to Microsoft Dragon Copilot represent a meaningful shift in how technology supports nurses. These innovations are designed to reduce friction across the full scope of a shift—extending well beyond documentation and aligning to how care is delivered across settings, teams, and shift-based responsibilities.

Recent advancements include:

• Smart room and wearable device integrations, powered through partners including Artisight, Caregility, hellocare.ai, and Stryker, help capture key information passively—reducing interruptions and freeing up time to stay focused on patient care.
• In-workflow access to organizational content such as policies, procedures, schedules, and communications, giving nurses access to even more information without breaking focus.
• Expanded service line support, including emergency departments and intermediate/stepdown units—meeting nurses where they practice.
• Dragon Copilot mobile app, extending support beyond in-EHR documentation to match how nurses work—reducing friction as they move between rooms, stations, and tasks.

Together, these enhancements reflect continued progress shaped by close collaboration with nurses—expanding where and how Dragon Copilot can be used and reinforcing a commitment to evolve alongside nursing practice.

A partnership that continues

Looking ahead, Microsoft remains committed to continued innovation in partnership with nurses—focusing on the most challenging aspects of nursing and applying technology where it can make a real difference. That commitment goes beyond listening; it means investing, building, and evolving solutions that support nurses across the full scope of their work.

This Nurses Week 2026 is both a moment of gratitude and a reaffirmation of how progress happens—together. By continuing to build with nurses and for nurses, we can help advance nursing in ways that honor the profession and support the future of care.

To nurses everywhere: thank you for all that you do every day, and for continuing to partner with us on this journey.

• Watch the Microsoft Dragon Copilot demo.
• Continue the conversation—The Nurse’s POV podcast explores how AI can support nurses, while keeping people at the center of change.
• As a thank you, LinkedIn Learning is providing access to CEU-eligible courses for nurses through the end of July 2026. 

Microsoft Dragon Copilot

Bring documentation, clinical context, and knowledge into one workflow.

Watch the demo

The post Built with nurses, shaped by trust: Honoring the humanity at the heart of care appeared first on The Microsoft Cloud Blog.

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

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

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

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

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

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

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

1. Redefine product lifecycle intelligence

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

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

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

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

2. Run AI-powered factories 

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

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

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

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

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

3. Build trust across human–agentic teams

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

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

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

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

4. Orchestrate supply chains with AI agents

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

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

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

—Andre Scheepers, Chief Digital Officer, Farmlands Cooperative

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

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

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

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

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

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

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

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

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

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

As the world navigates a critical phase for energy, the recent CERAWeek 2026 event showcased how leaders are addressing an era defined by convergence and competition—where technology and energy markets are deeply intertwined, and resilience must align with sustainability. The theme of CERAWeek 2026—“Convergence and Competition: Energy, Technology and Geopolitics”—proved to be remarkably relevant as discussions unfolded throughout the week.

It was evident that energy markets have become inseparable from digital infrastructure. AI is rapidly reshaping power demand, while supply chains remain vulnerable to geopolitical pressures. Throughout the conference, energy leaders confronted the simultaneous demands of security, affordability, and decarbonization.

Microsoft’s perspective was clear: we are entering the new Energy Frontier, where data, AI, and cloud computing serve as essential enablers for trust, resilience, and growth throughout the energy value chain.

AI emerged as a central topic in creating a more responsive and robust energy system. In this landscape of convergence and competition, energy executives are being challenged to identify disruptions earlier, pivot strategies rapidly, and make informed decisions amid global uncertainty, market fragmentation, and ongoing climate challenges. AI is no longer just a productivity booster—it’s now foundational to secure, real-time, and adaptive energy operations. The consensus at CERAWeek was that the decade’s leading organizations will be those that leverage AI to transition from static systems to intelligent, adaptive solutions.

From physical infrastructures to smart systems: Lessons from the event

This transformation was highlighted across the energy chain:

• Oil and gas companies are striving to balance investment with emissions reduction, safety, and operational resilience.
• Power and utilities are contending with surging electricity demand from electrification and data centers, while modernizing grids and preparing for extreme weather.
• Natural gas and liquefied natural gas (LNG) are more global and sensitive to geopolitical change than ever before.
• Mining and materials are recognized as essential to clean energy and electrification efforts.
• Policy, permitting, and regulation were frequently cited as critical to the pace of new projects.

At the heart of the discussions was AI—driving higher electricity consumption, transforming asset management, and unlocking new opportunities for analysis, prediction, and system optimization. The lines between energy and technology have all but disappeared.

Rising competition in a fragmented world: What CERAWeek revealed

The conference underscored how competition is intensifying. Geopolitical tensions, trade barriers, and supply chain disruptions are now permanent features of the marketplace. Energy leaders spoke candidly about the ongoing need to operate in environments marked by uncertainty—managing regional conflicts, cyber risks, volatile weather, and price swings.

Resilience, once seen as a defensive posture, is now a source of competitive strength. The organizations best able to anticipate disruptions, respond dynamically, and maintain secure operations in complex conditions will continue to lead. But as participants agreed, this requires more than incremental change—it calls for innovative operating models grounded in trusted data, intelligent platforms, and secure cloud infrastructures.

Microsoft at CERAWeek: Advancing on the Energy Frontier

At CERAWeek 2026, Microsoft reaffirmed its commitment to empowering energy and resource companies to seize the opportunities created by convergence and competition.

The Microsoft Agora House hosted sessions and live demonstrations illustrating how cloud, data, and AI technologies are addressing industry-wide challenges—not in isolation, but across the entire energy ecosystem.

Our collaboration with clients and partners around the world continues to focus on four key priorities:

1. Developing an AI‑ready energy workforce

The complexity of energy systems is rising as workforce dynamics shift. Companies struggle with talent shortages, aging employees, and the urgent need for large-scale reskilling—while keeping operations safe, dependable, and efficient.

AI stands out as a catalyst for equipping the next generation workforce. With Microsoft tools, organizations can:

• Automate tasks, both routine and knowledge-based, across engineering, operations, and business functions.
• Deliver AI-powered training and reskilling tailored to technical and frontline jobs.
• Foster collaboration among IT, operational technology (OT), and field teams using secure, integrated platforms.

Our aim isn’t to replace people but to enhance expertise, streamline processes, and let teams concentrate on high-impact work—whether they’re managing intricate assets, tackling emergencies, or speeding up innovation.

2. Strengthening and optimizing operations amid volatility

Operational reliability is more important than ever in a divided world.

With increasing digitization, energy infrastructures are more exposed to cyber, physical, and geopolitical threats. Meanwhile, profitability relies on maximizing uptime, performance, and safety.

Microsoft assists energy firms to:

• Integrate IT and OT data for comprehensive operational insights.
• Leverage AI and analytics for improved asset reliability and predictive maintenance.
• Bolster cybersecurity across critical and industrial infrastructures.

These advancements help leaders shift from merely reacting to events toward predicting and modeling scenarios—a necessity as disruptions grow more frequent and less predictable.

3. Driving net‑zero progress through data and AI

Net-zero commitments are now about action, not theory.

Tackling methane emissions, scaling carbon capture, updating power grids, and bringing renewables online all require accurate data, transparent tracking, and sophisticated systems operating at scale.

Microsoft enables customers to:

• Track and manage emissions with dependable, verifiable data.
• Utilize AI for methane detection, carbon accounting, and climate risk assessments.
• Modernize grid infrastructure to support electrification and renewable integration.

Success in sustainability now goes hand-in-hand with competitiveness. Organizations that transform climate ambition into actionable results will attract investment, secure approvals, and build public trust.

4. Becoming the Energy Frontier with agentic AI

A transformative development shaping the Energy Frontier is the advent of agentic AI—intelligent systems capable of reasoning, acting, and adapting in complex contexts.

At CERAWeek, we presented agentic AI solutions that:

• Streamline approval and regulatory workflows.
• Refine energy trading, logistics, and supply chain management.
• Support scenario planning involving weather, geopolitics, and changing demand.

These are not isolated fixes—they represent a new class of systems built for navigating uncertainty, helping leaders evaluate trade-offs, anticipate impacts, and accelerate decision-making confidently.

A call for leadership and collaboration

CERAWeek 2026 reaffirmed its role as a crucible for shaping the future of energy. Technological convergence is dissolving traditional industry boundaries, while competition is redefining how value is created and protected. As the event concluded, the message was clear: those who invest early in intelligent platforms, credible AI, and flexible operating models will define the coming era.

Microsoft remains committed to working closely with energy and resource organizations, building secure, sustainable, and adaptive systems that fulfill the promise of the Energy Frontier. We look forward to ongoing collaboration with industry, government, and technology leaders to continue shaping the future together—well beyond CERAWeek 2026.

Thank you to everyone who joined us at the Microsoft Agora House. The conversations, forums, and real-world stories shared have set a new pace for innovation—demonstrating how data, AI, and cloud are truly revolutionizing the global energy system.

The post CERAWeek 2026: Reflections on convergence, competition, and the new Energy Frontier appeared first on The Microsoft Cloud Blog.

At the same time, leaders face unprecedented complexity: fragmented regulations, rising cyber threats, geopolitical volatility, and accelerating AI adoption are reshaping where data can live, how AI can be trained, and how organizations can balance innovation with control.

Against this backdrop, Microsoft convened global policymakers, CIOs, partners, regulators, and industry leaders in Brussels—and online—for the 2026 Microsoft Digital Sovereignty Summit. The summit brought forward a shared message: Digital sovereignty is not a fixed destination; it is a continuous risk management discipline that underpins resilience, security, and innovation.

Below, we’ll dive into our top five insights from the event and what they mean for organizations both across Europe and globally.

5 key insights from the 2026 Microsoft Digital Sovereignty Summit

1. Digital sovereignty is fundamentally about risk management

One of the clearest themes from the summit was a shift in how leaders define digital sovereignty: not as an abstract policy concept, but as a practical exercise in risk management.

Leaders emphasized that sovereignty today means understanding and managing a complex risk landscape spanning cybersecurity threats, geopolitical disruption, regulatory requirements, and business continuity. The objective is not to eliminate risk entirely, but to assess it clearly and manage it proportionally.

A key takeaway from discussions was that there is no one-size-fits-all approach. Every organization—and every workload—has a unique risk profile, legal obligation, and level of criticality. As a result, sovereignty decisions must be made deliberately, workload by workload, rather than through a single architectural choice or a “universal sovereign cloud” model. This view reflects a broader industry trend away from location‑based assurances and toward enforceable, auditable control across data, operations, and AI.

This reframing marks an important shift: digital sovereignty is no longer about rigid control or ideology but about enabling organizations to operate confidently in uncertainty.

2. Cybersecurity is the foundation of digital sovereignty

A central message throughout the summit was clear: sovereignty without cybersecurity is a non-starter.

Cyber risk has become the most immediate and pervasive threat across sectors, from government and defense to finance, healthcare, and critical infrastructure. Leaders emphasized that cyber threats are persistent, adaptive, and increasingly linked to geopolitical dynamics.

Importantly, discussions challenged the common misconception that isolation equals security. Disconnecting systems or building digital “walls” can create blind spots by limiting access to shared threat intelligence, coordinated response capabilities, and real-time threat detection. As highlighted during the event, modern cyber defense depends on scale, collaboration, and integrated visibility across identity, endpoints, cloud infrastructure, applications, and data.

This reinforces a critical point: sovereignty cannot be achieved without cybersecurity. Without continuous access to global threat intelligence, modern cyber defenses, and interoperable security platforms, organizations cannot maintain real control, resilience, or continuity, regardless of where data resides.

3. Sovereignty and innovation are not tradeoffs; they are mutually reinforcing

Summit speakers shared a strong consensus that organizations do not need to choose between innovation and control. When grounded in strong security and governance, sovereignty creates the conditions necessary for innovation to thrive.

From legal and contractual commitments to purpose-built technical capabilities, discussions highlighted how sovereign frameworks can reduce uncertainty to allow teams to adopt cloud and AI with greater confidence, enabling organizations to move faster, not slower.

This perspective reframes digital sovereignty from a perceived constraint into a strategic enabler that supports competitiveness, resilience, and growth across Europe’s digital economy.

4. Sovereign and powerful AI requires responsible data processing and transparent control

Another major insight from the summit was the growing expectation that sovereign AI must be built on responsible data processing and transparent control. Leaders emphasized that as AI becomes more deeply embedded in core operations, organizations need systems that not only meet today’s regulatory and security obligations, but remain trustworthy, auditable, and resilient as requirements continue to evolve.

Sovereignty in the age of AI extends well beyond data residency. It requires clear, enforceable boundaries around where data is processed, how it is used, and how AI models are trained and executed, combined with full visibility into how AI systems operate across their lifecycle. Assumptions of trust are no longer sufficient—organizations increasingly expect verifiable control, including customer-managed encryption, protections for data while in use, restrictions on operator access, and auditable governance mechanisms that demonstrate compliance in practice.

Critically, sovereignty must be designed end-to-end—spanning infrastructure, platforms, security, data governance, and AI workloads. It is not a single architectural choice or off-the-shelf solution, but a workload-dependent approach aligned to risk, criticality, and mission needs. The summit highlighted how new capabilities are being built across the stack to support sovereign requirements at scale.

5. Digital sovereignty succeeds through collaboration, not isolation

A final and critical insight from the Summit was that digital sovereignty succeeds through collaboration, not isolation.

Across panels and discussions, leaders reinforced that sovereignty depends on ecosystems, where governments, enterprises, and technology providers work together to translate policy into operational reality. Attempts to isolate systems or fragment digital infrastructure can increase risk rather than reduce it, limiting access to innovation, intelligence, and coordinated defense.

Real world examples from customers across Europe, including organizations running regulated workloads on Azure Local, demonstrated how collaboration enables sovereignty at scale. Combining local expertise with global platforms helps organizations maintain control, meet regulatory requirements, and drive innovation simultaneously.

The message was clear: sovereignty is not the responsibility of any single institution. It is a shared commitment, strengthened through cooperation across public and private sectors, and reinforced by partners who align with local priorities.

Digital sovereignty posture in practice

A strong digital sovereignty posture gives organizations choice, visibility, and control across diverse environments. As emphasized throughout the summit, the objective is to align capabilities with risk exposure, regulatory expectations, and the specific needs of different workloads, applying proportionate controls rather than forcing a single model across the entire estate.

In public cloud settings, this means transparency, strong encryption, clear access controls, and accountable operations. For workloads that need greater isolation or local control, hybrid and sovereign solutions provide essential options. Earlier this year, Microsoft expanded its sovereign cloud continuum, enabling critical workloads to run in constrained or disconnected environments while still benefiting from innovation and advanced security practices. This enables critical workloads to run in constrained or disconnected environments while still benefiting from innovation and advanced security practices.

Organizations must focus on flexibility, working to meet today’s requirements while preparing for tomorrow. Features like the EU Data Boundary, long-standing encryption and access safeguards, and operational transparency give customers concrete ways to align with regulations and manage risk.

Across public, hybrid, and private clouds, Microsoft’s approach combines operational discipline with commitments to privacy, security, and responsible AI, creating a foundation for trust, resilience, and sustainable digital sovereignty.

Rooted in risk management

Across every session and conversation throughout the summit, one theme was unmistakable: digital sovereignty is now a continuous, organization-wide discipline rooted in risk management.

Leaders must balance security, compliance, resilience, and innovation—making deliberate, workload-specific decisions in an environment where risks are constantly evolving. Organizations that succeed will be those that treat sovereignty not as a fixed state, but as an adaptive capability built on strong cybersecurity, flexible architectures, and trusted collaboration.

The 2026 Microsoft Digital Sovereignty Summit made this clearer than ever: a sovereign, secure, and innovative digital future is possible, and it’s already taking shape.

Learn more about Microsoft’s approach to Sovereign Cloud and Sovereign AI

• Microsoft Sovereign Cloud website
  
• Build sovereign AI at the edge with Azure Local
  
• Microsoft Sovereign Cloud adds governance, productivity and support for large AI models securely running even when completely disconnected
  
• Navigating digital sovereignty at the frontier of transformation
  
• IDC InfoBrief: Digital Sovereignty Reconsidered: From Location-Based Assurance to Enforceable Control
  
• Sovereignty designed in Europe: Microsoft opens its first studio for resilient cloud and AI architectures in Munich, Brussels and Amsterdam
  
• Microsoft Sovereign Cloud in Europe white paper
  
• Discover Microsoft Sovereign Cloud videos
  

The post 5 takeaways from the 2026 Microsoft Digital Sovereignty Summit appeared first on The Microsoft Cloud Blog.

New capabilities include the ability to surface relevant work-related information alongside patient data for customers using Microsoft 365 Copilot; partner-built AI apps and agents available through Microsoft Marketplace that extend intelligence across revenue cycle, clinical insights, and decision support; and expanded role-based experiences for physicians, nurses, and radiologists designed to scale securely across settings and geographies.

Today, more than 100,000 clinicians rely on Dragon Copilot as part of their daily practice—supporting care for millions of patients every month. That kind of adoption doesn’t happen by accident; it happens when technology earns trust, fits naturally into clinical workflows, and proves its value day after day. As healthcare continues to accelerate, the question facing organizations is no longer if AI will be part of care delivery, but how quickly they can equip their teams with tools that scale safely, work across roles, and keep clinicians focused on patients. The new Dragon Copilot capabilities we’re introducing at HIMSS 2026 build on this proven foundation—extending trusted clinical support beyond documentation to meet the growing demands of modern care.

Clinicians need more than access to data—they need an AI assistant that works alongside them, understands context, and supports action across systems and settings. Built on Microsoft Azure, Dragon Copilot delivers this capability with enterprise‑grade security, responsible AI, and cloud scale—giving organizations the confidence to deploy broadly and grow with care teams wherever they work.

“We ultimately went with Microsoft because of the security, the compliance, the scalability, and the fact that they’ve delivered reliable solutions for years.”

—Snehal Gandhi, MD, Vice President and Chief Medical Information Officer, Cooper University Health Care

See what Dragon Copilot has to offer:

Unifying the disparate—so care teams can move faster, with confidence

By unifying information from across systems and sources, Dragon Copilot reduces fragmentation and unnecessary searching—bringing patient data, trusted clinical content, and partner powered AI insights into a single, contextual experience within the clinical workflow.

What makes this approach different is not just access to information, but how intelligence is delivered and applied. Clinicians can naturally query, summarize, create, and act using voice or text—without toggling between tools. Insights are surfaced instantly in one place, enabling care teams to move fluidly from understanding to action while spending less time navigating systems and more time with patients.

That intelligence is grounded in a broad set of trusted sources, including:

• Prebuilt trusted clinical content with citations
• Patient data like diagnoses, labs, medications, and allergies
• Organizational content such as policies, procedures, schedules, and communications

When needed, reliable web information can also be accessed through a safety‑first pathway—ensuring responses remain appropriate for clinical use.

Care delivery depends on more than clinical facts—it also depends on fast access to the work context around care. With Microsoft 365 Copilot, powered by Work IQ and accessible inside Dragon Copilot, clinicians can pull in relevant work-related information from connected apps and enterprise data, right where they’re already working. Work IQ is the intelligence layer that helps Copilot understand how people collaborate across emails, files, meetings, and chats—so responses are grounded in the right context. The result is a more unified experience that reduces time spent searching across tools and keeps momentum inside the clinical workflow.

Dragon Copilot extends clinical intelligence beyond any single system or screen. Instead of being locked into one interface, clinicians can invoke powerful AI capabilities wherever they’re already working—across applications, EHRs, and web pages. By simply clicking or highlighting text, Dragon Copilot can read, understand, and apply its intelligence directly in context, without forcing clinicians to switch tools or reenter information.

For example, a clinician reviewing a note can place their cursor over a sentence and say, “Add more detail about what the patient shared regarding their cardiac history.” Dragon Copilot immediately expands the documentation using the surrounding clinical context—no copying, no pasting, and no workflow disruption—helping clinicians move faster while keeping their focus on the patient, not the screen.

Building on this foundation, Dragon Copilot further unifies innovation through AI apps and agents available in Microsoft Marketplace. Developed by partners such as Canary Speech, Humata Health, Optum, and Regard, these solutions deliver capabilities across clinical insights, revenue cycle management, prior authorization, and clinical decision support. Organizations can easily purchase, deploy, and scale partner innovation—while clinicians experience those insights directly within their existing workflows.

“Sentara Health is integrating Regard’s diagnosis and documentation technology within Dragon Copilot to save time, improve revenue integrity, and most importantly improve care.

By combining Dragon’s ambient conversation capture with Regard’s ability to surface key insights from data, we expect to help our clinicians identify comorbidities and relevant diagnoses in real time without adding steps to their workflow. Our goal is straightforward: strengthen the clinical picture, reduce documentation burden, and support more informed decision-making at the point of care.”

—Dr. Joseph Evans, Vice President, Chief Health Information Officer at Sentara Health

Simplifying the complex—so care teams can be present with patients

Dragon Copilot streamlines clinical documentation and routine tasks, so clinicians spend less time navigating systems and more time focused on patient care. By simplifying physician and nursing charting, notes, flowsheets, and radiology reporting, it reduces rework and cognitive burden—helping care teams work more efficiently and confidently across the day.

This simplification is powered by healthcare-grade AI models built for clinical accuracy, with clinical note quality evaluated using the Provider Document Summarization Quality Instrument (PDSQI9)—an industry standard developed with leading academic and healthcare institutions to ensure clear, consistent, and clinically appropriate outputs.

Beyond documentation, Dragon Copilot automates high friction tasks across the workflow. Persona specific note types, automated referral letters and after‑visit summaries, summaries of prior radiology reports, and proactive coding guidance reduce manual effort and unnecessary toggling—allowing care teams to focus on decisions, not data entry.

New and expanded capabilities include:

• Proactive ICD‑10 specificity suggestions, delivered during note review to support timely, accurate reimbursement.
• Reusable custom clinical documents, created from prompts or examples and managed as templates, allowing clinicians to get additional unique content created automatically, such as custom letters.
• Pull-forward workflow support to jump-start new documentation from prior notes.
• Multilingual conversation capture, connecting with patients in their language. Captures the conversation in 58 languages and automatically converts the encounter into a note written in the primary language used in each country.
• Seamless migration from Dragon Medical One, preserving existing commands, vocabularies, profiles, templates, and AutoTexts.

Scaling across roles, geographies, and devices

Dragon Copilot is designed with role-based experiences that deliver the right capabilities to each clinician, when and where they’re needed. Physicians, nurses, radiologists, and other care team members benefit from workflows tailored to their unique responsibilities—from documentation and care coordination to image interpretation—while organizations maintain consistency, security, and compliance at scale. With a single solution spanning multiple roles, including the only experience built for radiologists and demonstrated outcomes for nurses, healthcare organizations can simplify their technology footprint and drive greater return on investment.

Physicians

Dragon Copilot supports physicians across care settings through EHR‑integrated workflows and a dedicated app available on mobile (iOS and Android), web, and desktop. Physicians can document more efficiently, access timely clinical information, and reduce cognitive load—whether at the point of care or on the go.

Together with partners, Dragon Copilot continues to scale globally and is now available in U.S., Canada, the UK, Ireland, France, Germany, Austria, Belgium, and the Netherlands.

Nurses

Dragon Copilot enhances nursing workflows by ambiently capturing documentation at the point of care and transforming conversations into structured flowsheet entries. With expanded support for all med-surg flowsheet templates and lines, drains, and airways (LDAWs) additions and removals—nurses can document more completely without disrupting care.

Through a dedicated app available on mobile (such as iOS and Android), web, and desktop, nurses can also access information from trusted medical sources, query transcripts to surface key patient details, and create concise summaries—without leaving their workflow—reducing clicks, and keeping focus on patient care.

“Dragon Copilot gives power back to nurses to spend time at the bedside with face-to-face interactions.”

—Stephanie Whitaker, MSN, Registered Nurse, Chief Nursing Officer, Mercy

Nurses using Dragon Copilot have reported reduced cognitive load, faster documentation, and improved patient experience, reinforcing the value of role‑specific AI designed for frontline care. The Dragon Copilot nursing experience is available in the United States.

“I can say that without a doubt, using Dragon Copilot has significantly reduced the time that I’m focused and worrying about sitting down and getting my charting done behind the computer.”

—Christine Dupire, Registered Nurse, Mercy

Radiologists

Paired with PowerScribe One, Dragon Copilot helps minimize repetitive tasks such as reviewing prior reports and automates routine steps in report creation. It surfaces relevant clinical context, integrates customizable AI experiences, and provides intelligent access to credible information—helping radiologists stay focused and deliver high‑quality reports with confidence. The Dragon Copilot radiology experience is currently in preview in the United States.

“As we embrace the next frontier of AI, we know that having cloud-based solutions that work seamlessly with our existing products and systems is paramount. Having Dragon Copilot as a companion for PowerScribe One gives me confidence that I can test and benefit from the latest AI advancements with minimal disruptions and distractions.”

—Sean Cleary, MD, Vice Chair of Informatics for Imaging Sciences University of Rochester Medical Center

Restoring humanity to healthcare through AI

AI will only transform healthcare if it truly serves the people delivering care. Dragon Copilot is built for that purpose—bringing role‑based experiences, hands‑free workflows, and proactive clinical intelligence together in a way that fits naturally into how clinicians work. By unifying information, reducing friction, and extending trusted intelligence across the workflow, Dragon Copilot helps clinicians spend less time managing tasks and more time connecting with patients—restoring focus, confidence, and humanity to the practice of medicine.

Join the more than 100,000 clinicians already using Dragon Copilot

• Visit us at the HIMSS 2026 Booth #2812.
• Get the playbook to learn how clinicians utilize AI to work smarter.
• Download the white paper to explore AI use cases transforming healthcare.

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This year, Microsoft had a clear focus at DTECH 2026: help utilities move from pilots to production by unifying IT and OT data, applying AI where it measurably improves reliability, affordability, and productivity and do so with the security and governance necessary for critical infrastructure.

Microsoft-led sessions explored moving beyond experimentation to focus on how utilities are turning unified data and AI into repeatable, operational outcomes. The takeaways from DTECH this year point to the next chapter of grid modernization—one defined by execution at scale, not pilots. 

What utility leaders reinforced: Keeping pace with change

Utility leaders consistently pointed to the increasing speed of change across the grid. Planning and operations are being pushed to respond faster as load growth becomes larger, more concentrated, and more volatile. Electrification is reshaping peak demand profiles, while capital programs are under pressure to deliver measurable value earlier—even as timelines continue to compress. 

At the distribution level, operational complexity is increasing. Distributed energy resources, electric vehicles, flexible demand, and new market programs are turning distribution systems into highly dynamic environments that demand better visibility, orchestration, and cybersecurity. Utilities are managing bidirectional power flows, evolving protection schemes, and the reality that smaller, distributed assets can have outsized system-level impacts—raising the bar for visibility, orchestration, and cybersecurity.

As a result, resilience is no longer episodic; it is a daily operating requirement. Fragmented data and manual coordination continue to limit situational awareness and slow response during major events.

Industry leaders were realistic about these constraints. Equipment lead times, workforce availability, and regulatory requirements mean that near-term reliability gains often come from improving how existing assets and systems are planned and operated. As a result, progress is increasingly measured by how effectively insights are translated into operational decisions, supported by secure and scalable platforms.

Trusted data as the foundation for AI in operations

Utilities generate vast amounts of data across assets, outages, telemetry, imagery, work management systems, and customer platforms. In many organizations, this data remains distributed across systems with inconsistent definitions, varying latency, and uneven governance.

These conditions slow analysis, create conflicting views of performance, and limit the ability to move from insight to action. Without a consistent and trusted data foundation, AI initiatives struggle to scale beyond isolated use cases. 

Microsoft is focused on helping utilities establish governed data foundations that support analytics and AI across planning, operations, field work, and customer engagement. By enabling scale across use cases—rather than building one‑off pipelines—utilities can align around shared definitions, apply consistent security controls, and collaborate without duplicative effort. 

This matters because the highest value use cases are inherently cross domain. Outage performance, capacity planning, and major event readiness all depend on data that spans systems and organizations. A unified data foundation allows AI to support these decisions with clarity, traceability, and operational relevance. 

From siloed AI solutions to agentic operations

Another notable theme at DTECH 2026 was the growing interest in agent-enabled workflows. Utilities are looking beyond standalone AI tools toward systems that can support multi-step workflows across planning, operations, and field execution, while maintaining appropriate oversight by subject matter experts across the workforce.

The focus is squarely on practical outcomes. Earlier risk identification, clearer paths from signal to action, and stronger coordination across teams are driving interest in these approaches, as utilities seek to move faster.

Human oversight remains foundational. Operators and engineers expect AI systems that surface options, explain their rationale, and reference trusted data—while operating within clearly defined governance boundaries. In regulated, safety‑critical environments, this human‑in‑the‑loop model must align with role‑based access, operational constraints, and established safeguards.

Partner innovation making modernization deployable

Grid modernization depends on strong ecosystem collaboration. No single entity can deliver it alone. What matters is interoperability—how solutions work together across planning, operations, outage restoration, field productivity, and major event response.

That focus was clear in the announcements from Microsoft and our partners at DTECH 2026:

• Dragos—Microsoft and Dragos announced an expanded partnership focused on helping organizations modernize and secure their cyber-physical operations. By combining Dragos’ OT threat intelligence and detection capabilities with Microsoft’s cloud, AI, and security platforms, utilities can strengthen the safety, reliability, and resilience of the critical systems that power businesses and communities. 
• GE Vernova on Azure—GridOS Data Fabric and DDLR are now on Microsoft Azure, combining GE Vernova’s operational expertise with Microsoft’s cloud, AI, and analytics.
• Hitachi—Hitachi Energy’s Ellipse EAM is being combined with Microsoft Dynamics 365, Microsoft Fabric, Copilot, and Microsoft Foundry to create a unified solution that manages data, analytics, and business operations, supports asset operations, and provides visibility of equipment across entire networks for more reliable services, safer operations, and fewer emergency repairs.  
• Itron—The new Itron Intelligent Edge Operating System (IEOS) Connector for Microsoft 365 Copilot uses trusted grid-edge data to redefine grid edge intelligence by applying AI at scale to optimize operations, enhance predictive insights, and enrich customer experiences.
• Schneider Electric—Microsoft’s AI, cloud, and data capabilities are integrated in the One Digital Grid Platform, enabling operations to move from prediction to execution in minutes.

These developments reflect continued progress toward reference architectures and reusable patterns that reduce bespoke integration and support broader adoption across utility environments.

Security and resilience built into modernization

Security remains a core consideration as IT and OT environments converge and connectivity at the edge increases. Utility leaders emphasized the importance of approaches that function across hybrid architectures and reflect operational realities.

Identity, access management, monitoring, and governance must be consistently applied across cloud, edge, and on‑premises systems. Resilience improves when operators have timely visibility, clear decision paths, and automation that supports established operating practices.

What comes next

DTECH 2026 highlighted a clear direction for grid modernization; utilities are prioritizing:

• Trusted data foundations spanning IT and OT.
• AI and agent-enabled capabilities embedded in operational workflows.
• Secure architectures designed to support reliability, governance, and resilience.

Microsoft will continue to work alongside utilities and industry partners to advance these priorities and support grid operations that can adapt to increasing complexity while delivering reliable outcomes for customers and communities. 

Turn insight into action

• Explore the possibilities of AI transformation with Microsoft
• Read the latest International Energy Agency’s World Energy Outlook
• Learn how to achieve more in the energy and resources industry with trusted data and AI solutions from Microsoft
• Explore the Reinventing the Utility Playbook: AI Agents for Grid Growth, Storm Response, and the Workforce 2.0 DTECH 2026 session
• Learn more about the AI-Powered Utilities: The Next Wave of Innovation DTECH 2026 session

The post DTECH 2026: How Microsoft and our partners are accelerating AI innovation for utilities appeared first on The Microsoft Cloud Blog.

At Microsoft, we see this shift clearly in our conversations with customers globally. Leaders are moving quickly to scale AI, while remaining accountable for sustainability commitments to customers, investors, regulators, and employees. Too often, these goals are positioned as tradeoffs. In practice, they are reinforcing. When AI transformation is approached with intent and discipline, it can drive stronger business performance while advancing sustainability outcomes.

That belief is the foundation of our new Strategic Guide: Aligning AI Transformation with Sustainability Goals.

Why AI transformation and sustainability belong together

The most meaningful impact from AI comes not from isolated pilots, but from transformation—when intelligence is embedded across strategy, operating model, and culture. That’s the premise of Microsoft’s Frontier transformation AI vision, where organizations are enriching employee experiences, reinventing customer engagement, reengineering core business processes, and bending the curve on innovation.

What’s often overlooked is that these same shifts deliver sustainability gains. More efficient processes require less energy and fewer resources, better data reduces waste and overproduction, and modern cloud and AI architectures—when designed intentionally—can shrink digital footprints while increasing speed and resilience.

Five practices for sustainable AI transformation

Our new Strategic Guide: Aligning AI Transformation with Sustainability Goals makes this connection explicit and practical, offering five essential practices leaders can apply today to turn AI ambition into measurable business and sustainability outcomes.

1. Adopt a modern cloud strategy.
   Moving workloads to efficient, hyperscale cloud environments is often the single biggest step organizations can take to reduce energy use while improving performance. Modern cloud platforms enable organizations to scale AI intelligently—optimizing compute, storage, and cooling in ways that are difficult to achieve on‑premises.
2. Assess your cloud provider’s sustainability and trust goals.
   An organization’s environmental footprint increasingly extends beyond its own walls. Transparency, renewable energy commitments, and responsible datacenter operations matter because your partners’ practices become part of your sustainability equation.
3. Manage data responsibly for efficient and accurate AI.
   Efficient data pipelines, strong governance, and thoughtful lifecycle management do more than reduce risk. They also reduce unnecessary compute and storage, helping AI systems become more accurate, scalable, and sustainable.
4. Optimize cloud workloads.
   As AI moves from pilots to production, sustainability outcomes increasingly depend on how workloads are designed and run in the cloud. Right‑sizing compute, reducing idle resources, and streamlining data movement lowers energy use while improving performance and cost control.
5. Fit the model to the mission.
   With efficient cloud foundations in place, leaders can focus on selecting the right AI models for the right jobs. Aligning model choice with business objectives, performance requirements, and sustainability goals enables organizations to scale AI responsibly—maximizing impact without unnecessary complexity or resource use.

Together, these practices help leaders move beyond aspiration to execution—delivering what the guide describes as a dual return: stronger business performance alongside reduced environmental impact.

What the research shows

AI can deliver better results—faster and more sustainably

In a simple experiment highlighted in the Strategic Guide: Aligning AI Transformation with Sustainability Goals, Microsoft set out to understand how efficiently AI could perform a common knowledge work task.

Five professionals were asked to summarize a 3,000-word technical report into 200 words. Completing the task took a median of 41 minutes and consumed an estimated 13.7 watthours of laptop energy.

Using a single prompt, Microsoft Copilot completed the same task in under a minute—using just 0.29 watthours of datacenter energy. That’s roughly 55 times faster and 47 times more energy efficient. Independent reviewers also rated the AI-generated summary higher for clarity, accuracy, completeness, and overall quality.

The takeaway is clear: when AI is applied thoughtfully, it can reduce time, energy consumption, and friction—while delivering stronger outcomes.

What this looks like in practice

Across industries, organizations are already demonstrating how AI transformation and sustainability reinforce one another.

ABB, a global leader in electrification and automation, is using AI to help energy and asset intensive industries operate more efficiently while meeting increasingly ambitious sustainability goals. The Genix Industrial AI Platform helps ABB customers deliver from 25% efficiency gains in data centers to 18% energy savings in cement production.

In the construction sector, Giatec is tackling one of the world’s most carbon intensive materials: concrete. Built on Microsoft Azure, Azure IoT Hub, and Azure OpenAI in Foundry Models, Giatec’s intelligent platform optimizes mix designs, reduced 2.5 million tons of carbon emissions, and increased profit margins for concrete producers by up to 100%.

Space Intelligence uses AI to turn vast amounts of satellite data into trusted, actionable insights for global climate and conservation efforts. The company moved to Microsoft Foundry and the Planetary Computer ecosystem to reduce the time required to map the world’s forests by 75%, completing coverage of more than 50 countries in just one year, something that would’ve taken six years—delaying the ability to drive and verify real world climate impact.

Becoming a Frontier organization—responsibly

These examples point to a broader trend: the organizations leading in AI are also redefining what responsible innovation looks like. Frontier organizations don’t treat sustainability as a separate initiative or reporting exercise. They design it into their transformation from the start.

Solving systemic challenges like climate change requires collaboration—across value chains, ecosystems, and sectors. It also requires leaders who are willing to ask better questions about how technology is deployed, measured, and governed.

This perspective is demonstrated by Microsoft’s recent announcement on community-first AI infrastructure. As we scale AI, we have a responsibility to consider not only what these systems can do, but how and where they are built. That means investing in infrastructure that supports local communities, prioritizes renewable energy, manages water responsibly, and is designed with transparency and long-term partnership in mind. Building AI responsibly isn’t just about reducing risk—it’s about earning trust and ensuring that the benefits of innovation are shared broadly—from the datacenter outward.

Used thoughtfully, AI can help us make smarter decisions, operate more efficiently, and unlock entirely new ways of creating value—while staying within planetary boundaries. Used carelessly, it risks accelerating the very challenges we’re trying to solve.

That’s why clarity matters. Frameworks matter. And practical guidance matters.

What leaders can do next

If you are responsible for shaping your organization’s AI strategy, sustainability agenda, or both, I encourage you to explore the Strategic Guide: Aligning AI Transformation with Sustainability Goals. It is designed to help you cut through complexity, identify where to start, and move forward with clear actionable strategies.

At Microsoft, we’re committed to helping our customers become Frontier organizations that lead with innovation, responsibility, and impact.

The challenges we face are complex. But with the right strategy, the right technology, and a shared commitment to progress, AI can help us build a more sustainable and prosperous future—for everyone.

Strategic Guide: Aligning AI Transformation with Sustainability Goals

Read the guide

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