While adoption of AI technology is now widespread, impact is not. Many organizations are experimenting and running pilot programs, but far fewer have the operating discipline to become what we call Frontier Firms—companies that scale AI in ways that meaningfully reshape work, decisions, and value creation. According to IDC’s Business Opportunity of AI Survey (August 2025), 68% of all respondents use GenAI and only 22% of organizations worldwide are Frontier Firms.¹ These companies are seeing a return on investment in the technology that is several times greater than companies that are slow to adopt.

This gap is why Microsoft developed a newly revised 2026 edition of the AI Decision Brief, a handbook designed to help leaders and business decision-makers embrace the opportunities of Frontier Transformation. It addresses how AI can become a durable source of advantage: where to focus, how to measure value, how agents change workflows, and how trust, governance, and responsibility enable scale. “This is not simply the next stage of technology adoption,” writes Brad Smith, Microsoft Vice Chair and President. “Frontier Transformation is a leadership moment that asks organizations to fundamentally rethink how people, processes, and decisions work together.

We believe that this brief answers the questions many executives are asking about how to stay ahead of the curve. The questions below surface what we’re hearing from business leaders across industries as they plan investments, assess readiness, and look ahead. Each reflects a theme explored in depth in the AI Decision Brief and points to how organizations can begin turning AI execution into lasting impact. 

1. How can my company get the biggest impact from AI? 

The biggest impact comes when AI changes how the business operates—not just how fast someone answers an email. “Frontier Transformation is a holistic reimagining of business, aligning AI with human ambition to achieve an organization’s highest aspirations and growth potential,” writes Judson Althoff, CEO of Microsoft commercial business.

What does this mean in practice? Frontier Firms are leveraging AI to transform customer engagement, core processes, decision-making, and innovation. For them, AI isn’t confined to one team or one tool. Instead, it’s embedded across the enterprise in an average of seven business functions. That’s when the outcomes compound. These organizations are monetizing AI and outperforming slow adopters with roughly 3x higher returns.¹ Agents are accelerating that shift because they don’t just make recommendations; they can take action and complete tasks.

2. How do you graduate beyond early wins with AI adoption?

While AI can boost individual productivity—drafting documents, summarizing meetings, and automating the more tedious aspects of jobs—it can do so much more, according to Jaime Teevan, Chief Scientist and Technical Fellow at Microsoft. “The real opportunity is bigger: not just helping individuals work faster, but enabling teams and organizations to work better, together,” she writes. 

Most AI initiatives stall for the same reason most transformations stall: teams prove their value in specific use cases, but leaders don’t change the system around them. The model isn’t the bottleneck—processes, decision rights, and trust are. Frontier leaders, on the other hand, pick a small number of priority workflows and redesign them end to end. That’s how you move from “we got a nice pilot result” to “AI is embedded in how we run the business.”

3. How do I identify the priority workflows where AI can meaningfully change outcomes? 

“AI integration is often framed as a technical problem: which models to use, how to connect systems, how to mitigate risk,” writes Jared Spataro, Microsoft CMO of AI at Work. “But for most organizations, the real constraint on value is not technology, it’s how work is organized and governed. The bigger challenge is centered on management.”

Frontier organizations don’t ask, “Where can we plug in AI to automate a task?” They ask, “Which workflows most directly affect revenue, cost, risk, customer experience, or speed of decision-making?” Frontier leaders focus on embedding AI, agents, and data directly into those areas of high impact. 

4. As AI agents take more action on behalf of employees and teams, how does my role as a leader need to change?

Leadership has become even more important in the agentic era. “When AI systems can plan and execute over many steps, leadership and engineering rigor become the real bottlenecks,” writes Kevin Scott, CTO of Microsoft. “You need teams that are explicit about goals, careful about feedback and evaluation, and thoughtful about where autonomy is earned versus constrained.” 

The greatest risks are unclear intent, ownership, and accountability. Frontier leaders get ahead of this by redefining roles and decision rights early. Humans set outcomes, constraints, and success measures, while agents operate within clearly governed boundaries. That means treating agents like new employees or privileged service accounts—with named owners, least-privilege access, continuous monitoring, and regular review. 

5. How do you measure the success of AI when it’s embedded across workflows, decisions, and teams—not just individual tasks?

“Early productivity gains from AI are now expected,” writes Alysa Taylor, Microsoft CMO of Commercial Cloud and AI. “But Frontier leaders see beyond those short-term efficiency wins. They understand how AI can also help grow revenue, increase customer acquisitions, reshape processes, and improve operational efficiency.” 

Frontier leaders measure ROI the way they run the business: at the workflow and outcome level, not by counting isolated tasks. Yes, they track early productivity signals, but they don’t stop there—they tie AI to business metrics like faster cycle times, higher quality and consistency, better customer experience, lower risk, and faster decision-making.  

6. We’re under pressure to move fast with AI. Can we tackle security later on?

Great question! The answer is simple: absolutely not. “The AI opportunity is incredible, but speed without security, observability and governance opens the door to significant risk. By embedding these elements from the start, organizations can innovate rapidly while building and fostering trust,” writes Vasu Jakkal, CVP of Microsoft Security Business. 

The moment AI moves beyond pilots and starts touching real data, customers, and decisions, issues with security and accountability can offset gains in efficiency. According to Microsoft’s 2026 Data Security Index, less than half (47%) of companies have fully implemented data security controls for AI. Frontier leaders build observability, Zero Trust security, and clear ownership from day one, so teams can move faster with confidence instead of stopping to clean things up later.  

7. How do you scale AI across an organization without losing control or trust?

“Scaling AI is less about deploying tools and more about preparing people,” writes Nathalie D’Hers, Microsoft CVP of Employee Experience. “A workplace culture grounded in a growth mindset is more important than ever.” Frontier Firms embrace continuous learning and agility. This helps teams fundamentally reimagine processes and think bigger.  

Crucially, Frontier organizations also pair empowerment with guardrails. They give employees access to AI where work actually happens—through copilots, low-code tools, and approved platforms—so innovation isn’t bottlenecked by a small group of specialists. At the same time, they’re very clear about boundaries. That includes shared governance frameworks, approved data sources, identity and access controls, and observability at every layer. That’s what allows creation to scale safely.  

8. How do I balance Frontier Transformation with sustainability? 

“AI and sustainability are often treated as separate agenda items, but they are fundamentally connected,” writes Melanie Nakagawa, Chief Sustainability Officer at Microsoft. “Leaders should understand both sides of that equation: the resource footprint of AI as well as the opportunity it brings to help them operate more efficiently, build smarter, more resilient systems, and lower carbon emissions.”  

As AI grows, it brings real resource and trust questions about environmental impact, supply chains, community impact, and whether the benefits of AI are broadly shared. The Frontier view is that designing for efficiency, responsibility, and equitable diffusion isn’t a nice-to-have; it’s how you unlock durable growth while avoiding backlash, constraints, and extra work later.

At Microsoft, we’re building out AI infrastructure with sustainability in mind while also using AI as a force multiplier for climate progress by optimizing systems, accelerating materials discovery, and improving resource efficiency.     

Next steps to lead in the era of Frontier Transformation

Read the full AI Decision Brief to understand what it takes to lead in the era of Frontier Transformation. The insights, leadership advice, and practical tips found within our brief will help prepare your company to properly utilize and scale a powerful AI strategy. Once you have that knowledge base, you’ll need a trusted, reliable set of AI tools to execute that strategy. 

Explore Microsoft AI tools and solutions for your Frontier Transformation. 

¹ IDC InfoBrief: sponsored by Microsoft, What Every Company Can Learn From Frontier Firms Leading the AI Revolution, IDC # US53838325, November 2025 

The post AI Decision Brief: How leaders can drive Frontier Transformation appeared first on The Microsoft Cloud Blog.

This is where the frontier is forming. While copilots help individuals be more effective, agents act on behalf of people. They carry out tasks, orchestrate multi-step workflows, and operate across systems continuously. And they’re moving quickly from experimentation to mainstream use. An IDC InfoBrief, sponsored by Microsoft, shows that 37% of organizations surveyed use agentic AI, another 25% are experimenting with it, and 24% are planning to use it the next 24 months.¹ Organizations that have already invested in people, skills, and responsible practices may be better prepared to operationalize agents at scale—and convert AI’s promise into real business performance.

Five strategic moves for introducing agents responsibly

The new Agents in the Workforce Handbook builds on those earlier foundations. Where the first blog in this series focused on empowering your people, and the second explored how to pair human judgment with AI systems, this third chapter looks ahead: How do you introduce agents into your workforce responsibly and intentionally? Below are five strategic moves leaders should consider. These are high-level guideposts; the Handbook goes much deeper with templates, examples, and decision frameworks to support implementation.

1. Start with your most persistent pain points

When organizations begin exploring agentic AI, a common challenge is prioritization. Imagining use cases is easy. Choosing where to start is harder. Successful organizations don’t begin with futuristic ideas—they begin with the familiar, recurring friction points that quietly drain time and introduce risk.

These are often the workflows teams have learned to “live with”: manual triage, routine follow-up, coordination across systems, repeated reporting steps, or tasks with high error potential. Leaders should observe how work truly happens—shadowing teams, reviewing process maps, and asking simple but revealing questions:

• Where do we lose time?
• What gets done manually that shouldn’t be?
• What feels broken—but no one owns?

These pain points typically offer the clearest path to early value. Addressing them not only frees capacity but also demonstrates to teams how agents can meaningfully improve the day-to-day. The Agents in the Workforce Handbook includes a readiness assessment and real-world patterns to help leaders identify and sequence the right opportunities.

2. Define your AI goal—and lead the change yourself

Introducing agents isn’t only a technical shift—it’s a leadership shift. Frontier Firms choose to align their early agent initiatives around bold, measurable goals: reducing manual work, accelerating cycle times, improving customer responsiveness, or expanding sales capacity. These goals create alignment and momentum, helping teams understand why agents matter and what success looks like.

But goals alone don’t change culture—leaders do. The organizations that move fastest are those whose executives personally model new ways of working. They use agents in their own workflows, talk openly about learnings, and recognize early adopters who demonstrate impact. They also acknowledge that change requires habit‑building. Experimenting with agents for even 20 to 30 minutes a day can materially improve adoption and confidence.

Skilling plays a central role. As Jeana Jorgensen, Corporate Vice President of Global Skilling, notes:

We’re hearing from many of our customers and partners that they expect employees across different roles to spend about 15 to 20% of their week learning and integrating AI into their daily work.

The Handbook offers guidance for identifying the roles, skills, and operating rhythms needed to support agent adoption.

3. Measure what works—and double down where it does

As with any transformative technology, early wins with agents need to be measurable and repeatable. Leaders should ensure visibility into how agents behave, how frequently they’re used, and the outcomes they produce. This isn’t about policing technology—it’s about giving teams the insights needed to improve and scale what’s working.

Effective organizations treat agent adoption like an operational discipline:

• They log and monitor agent activity.
• They measure time saved and business impact generated.
• They expand agents that demonstrate clear value.
• They refine or retire agents that don’t.

These data-driven insights help organizations move from experimentation to a consistent, enterprise-wide model for agent development—one where new ideas become shared services rather than isolated automations. The Handbook goes deeper into measurement strategies, including examples of what high-performing organizations track.

4. As agents become teammates, optimize continuously

Once an organization begins deploying agents across teams, a new challenge emerges: coordination. Agents that start out as individual productivity tools often become shared digital teammates—relied upon by multiple people, processes, and business functions. With that shift comes the need for thoughtful ownership, governance, and communication.

Successful organizations establish clear roles and responsibilities:

• Who owns each agent?
• Who can modify or update it?
• How are changes communicated to the people who rely on it?
• What happens when an agent’s behavior needs tuning?

Agents also require continuous improvement. As they’re used, they encounter edge cases, nuanced team preferences, and shifting processes. Over time, agents become more capable, and employees naturally evolve into “AI managers”—guiding digital apprentices the way they onboard and develop human teammates.

The Handbook provides deeper recommendations for governance models, centers of excellence, and cross-team alignment mechanisms that help organizations scale responsibly.

5. Reinvest the time saved—and push into innovation

While early value often shows up as efficiency, the long-term impact of agentic AI is much bigger: it creates renewed capacity for innovation. Frontier Firms understand that the goal isn’t to simply do the same work faster—it’s to free teams to pursue higher-value ideas, explore new business models, and elevate customer experiences.

Across industries, leading organizations are already demonstrating what this reinvestment looks like:

• L’Oréal is using AI agents to deliver personalized, at-scale beauty guidance.
• AT&T accelerated customer care resolution by 33%, saving millions while improving experience.

These examples highlight a crucial point: agents are not just workflow optimizers. They’re catalysts for reimagining how organizations deliver value. And the companies that begin investing now are positioning themselves for meaningful advantage.

Treat agents like teammates, not tools

The organizations achieving the strongest results view agents not as automations but as digital collaborators—systems that require feedback, tuning, and iteration. They integrate agents into team rhythms, treat them like growing contributors, and help their people evolve into confident AI managers.

This marks the natural third step in the Frontier journey: after empowering employees and strengthening the partnership between human expertise and AI (as explored in the first two blogs), organizations are now ready to bring digital teammates into the workflow in a structured, scalable way.

If your organization is ready to move from experimentation to scaled impact, the Agents in the Workforce Handbook offers the detailed guidance, examples, and templates to support your next phase of Frontier Transformation.

¹ IDC InfoBrief: sponsored by Microsoft, What Every Company Can Learn From Frontier Firms Leading the AI Revolution, IDC # US53838325, November 2025.

The post How to introduce agents into your workforce: 5 actions leaders can take appeared first on The Microsoft Cloud Blog.

With the help of Microsoft partner SP Peru, María Almenara took the first step towards its digital transformation process. The bakery migrated to Azure, Microsoft’s cloud, leaving acquisition costs or digital infrastructure maintenance behind. “Thanks to the database, we can analyze customer buying frequency and average purchase amounts, optimizing our processes and reducing pressure on the shop and the manager. These steps directly affect the customer experience,” states Carlos Armando de la Flor, the bakery’s General Manager.

Integrating cloud functionality

When María Almenara decided to become a data-driven business, one goal was to reach a 90% fill rate. This indicator shows the ability to serve customers without running out of stock. Today, the bakery has reached a 99% fill rate, assuring an optimal experience for its customers.

Based on the work done with SP Peru, a system was also created with Azure Machine Learning. Its integration with the Enterprise Resource Planning System (ERP) and the development of a specific mathematical technique allows for daily and weekly predictions. This is how the bakery obtained sales estimates for each store and product, allowing for planning and adjustments to cover demand for each of the 8 locations, as well as the ability to ship precise orders.

Furthermore, with a goal of complete business transparency and real-time decision making, the bakery used different Human Resources survey systems like SAP, among others. With the help of Microsoft’s Power BI, management created a control panel to view 18 indicators in 3 areas: finances, expenses and budgets; human resources; and customer satisfaction.

The mathematical technique used for these predictions undoubtedly played an important role in this process. This technique was later replicated and tested by the Massachusetts Institute of Technology, where local partner SP’s technique performed better than that of the team from the prestigious academic institution.

Serving the person, not just the consumer

Thanks to integrating these changes and its technological foresight, the bakery was able to weather a year as challenging as 2020—and managed to reach a milestone for the industry. This also reflects a change in María Almenara’s ethos, which is made of three fundamental pillars: a) a scalable culture and business model with the single goal of making hearts happy; b) data as an essential asset for leading in the digital economy and c) focus on the person, that is, on partners and customers.

With each step of the digital transformation process, María Almenara realized that its partners had to grow with the company. This is reflected in its turnover rate, which is less than 1%. The industry’s turnover rate is usually 25%. Without a doubt, incorporating technology has created business growth and satisfaction for its 223 partners.

Carlos Armando de la Flor concludes: “Here at María Almenara, we see technology as a helpful tool, not just something to solve things. Thanks to the omnichannel retailing platform our business uses, we’ve been able to establish a way to work that allows pregnant women or women with young kids to serve customers from home, prioritizing their health and comfort, and reducing turnover rates.”

COMPANY INFORMATION

• Customer: María Almenara
• Partner: SP Peru
• Products and Services: Microsoft Azure
• Industry: Other
• Organization Size: Medium (50 – 999 employees)
• Country: Peru
• To contact this Partner, click here
• Click here to learn more about this company
• Tags: Customer Stories, María Almenara, Microsoft Azure, Perú

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Over the past several years, we have seen customer concerns evolve materially. Early conversations focused primarily on privacy and lawful data handling. Today, those concerns have expanded. Leaders are now asking how they maintain operational continuity during disruption, how they adopt AI responsibly without losing control, and how they protect national, organizational, and customer interests in an increasingly volatile global environment.

These questions are not abstract. They surface in boardrooms, procurement decisions, architecture reviews, and crisis simulations. They reflect a broader shift in how trust is evaluated in digital systems. Today in Brussels we brought together attendees from around the world—policy makers, IT leaders, and enterprises—to approach these questions from the multiplicity of perspectives to move the conversation from headlines to action.

From privacy to resilience and beyond

Privacy remains foundational. But it is no longer the sole lens through which sovereignty is assessed.

Customers are increasingly concerned about business continuity in the face of cyber incidents, geopolitical tension, supply chain disruption, and network instability. They want to understand how critical workloads operate if connectivity is constrained, if dependencies fail, or if policy conditions change with little warning.

At the same time, innovation pressures have intensified. AI is becoming central to public service delivery, national competitiveness, and economic growth. Organizations cannot afford to pause progress while sovereignty questions are debated in isolation. They need approaches that allow them to move forward responsibly, balancing opportunity with control.

What we hear consistently is this: sovereignty concerns will continue to evolve. Any approach that treats them as static is already behind.

For four decades, Microsoft has operated under some of the world’s most demanding data protection, competition, and digital governance frameworks. Working closely with European institutions, regulators, and customers has shaped how we think about sovereignty—not as a regional exception, but as a discipline that must function at scale, under scrutiny, and over time. That experience matters because many of the sovereignty questions now emerging globally were first tested in Europe, long before they became mainstream elsewhere.

A consultative approach to risk management

This is why we believe digital sovereignty must be approached as consultative risk management, not a checkbox or a predefined deployment model.

Every organization faces a unique mix of regulatory obligations, cyber risk, operational exposure, and innovation goals. Even within a single institution, sovereignty requirements differ by workload. Some demand strict isolation and local control. Others require global scale, advanced security capabilities, and rapid innovation.

Our role is to help customers navigate these tradeoffs deliberately. That means working with them to assess risk, align architecture to policy realities, and design environments that reflect both today’s constraints and tomorrow’s unknowns.

This work sits at the intersection of cybersecurity, compliance, resilience, and frontier transformation. It requires ongoing engagement, transparency, and the willingness to adapt as conditions change.

Digital sovereignty posture in practice

A digital sovereignty posture that is flexible recognizes that no single approach can address every requirement. Instead, it focuses on giving organizations options, visibility, and control across a continuum of environments.

Customers operating in public cloud environments expect clear data residency options, strong encryption and access controls, and visible operational discipline. Just as important, they look for transparency into how cloud systems are governed and how exceptional situations are managed, particularly as regulatory scrutiny increases.

Those expectations do not disappear when workloads move closer to the edge. In fact, they intensify. For workloads that require greater isolation, local processing, or operation in constrained environments, hybrid and disconnected solutions become essential. In February, Microsoft announced the expansion of disconnected operations, enabling customers to run critical workloads in air-gapped environments while retaining consistent governance and operational control. This capability extends cloud-based practices into disconnected settings, supporting operational continuity without abandoning security and innovation. 

That commitment shows up in concrete safeguards that customers can independently evaluate and apply. The EU Data Boundary is one example, supporting data storage and processing within the EU and European Free Trade Association (EFTA) regions for cloud services, alongside longstanding investments in encryption, access controls, auditability, and operational transparency. These measures provide practical mechanisms for aligning cloud operations with regulatory and risk requirements, rather than relying on abstract assurances. 

At the same time, we are expanding options across hybrid and private cloud environments to support continuity, resilience, and local control where required. These investments reflect a simple reality: customer needs are not converging toward one model. They are diversifying.

Underpinning all of this are Microsoft’s digital commitments, which frame how we approach privacy, security, transparency, and responsible AI. These commitments are not marketing statements. They guide how systems are built, operated, and governed, and they provide a foundation for long-term accountability.

Practical guidance for leaders navigating sovereignty

As digital sovereignty becomes embedded in policy and procurement decisions, leaders benefit from a practical lens. Based on what we hear from customers and stakeholders, there are a few consistent themes shaping successful approaches:

• Sovereignty requirements will continue to expand beyond privacy to include continuity, resilience, and AI governance.
• Risk management is now inseparable from digital transformation strategy.
• Flexibility and optionality matter more than rigid architectures.
• Transparency and accountability are as important as technical capability.
• Sovereignty posture must consider protections against cyberthreats.

Addressing these realities requires partners who understand the full scope of the challenge and are willing to engage over the long term. It requires platforms and collaboration designed with sovereignty in mind from the start.

So what does this mean for you?

Digital sovereignty is not a destination. It is an ongoing discipline shaped by changing technology, regulation, and global conditions.

At Microsoft, we approach this work with humility and responsibility. We recognize that customer concerns will continue to evolve, and that our own platforms and practices must evolve with them. We remain committed to expanding our sovereign cloud continuum, strengthening our cloud capabilities, and delivering solutions that balance innovation with control.

Most importantly, we remain focused on delivery. Because in moments of uncertainty, what matters most is not what technology promises, but what it allows organizations to do with confidence.

Where does digital sovereignty go from here?

The future of digital sovereignty will be defined by implementation, not rhetoric. Success will depend on collaboration between governments, industry, and civil society, as well as a shared commitment to transparency and continuous improvement.

As we look ahead, our focus remains on helping organizations turn sovereignty principles into durable, scalable outcomes. That means continuing to invest in capabilities that support trust, engaging constructively with policymakers, and listening closely to the evolving needs of our customers.

Digital trust is built over time, through consistent action and openness, and that trust is one of the most important foundations we can help create.

The post Navigating digital sovereignty at the frontier of transformation appeared first on The Microsoft Cloud Blog.

Deepfakes threaten trust in news, elections, brands and everyday interactions, leading us to question what’s real. Determining what’s authentic or manipulated is the subject of Microsoft’s “Media Integrity and Authentication: Status, Directions, and Futures” report, published today. The study evaluates today’s authentication methods to better understand their limitations, explore potential ways to strengthen them and help people make informed decisions about the online content they consume.

The authors conclude that no single solution can prevent digital deception on its own. Methods such as provenance, watermarking and digital fingerprinting can offer useful information like who created the content, what tools were used and whether it has been altered.

People can be deceived by media if they lack information like its origin and history, or if its information is low-quality or misleading. The goal of the report is to provide a roadmap to deliver more high-assurance provenance information the public can rely on, according to Jessica Young, director of science and technology policy in the Office of the Chief Scientific Officer at Microsoft.

Helping people recognize higher-quality content indicators is increasingly important as deepfakes become more disruptive and provenance legislation in various countries, including the U.S., introduce even more ways to help people authenticate content later this year.

Media provenance has been evolving for years, with Microsoft pioneering the technology in 2019 and cofounding the Coalition for Content Provenance and Authenticity (C2PA) in 2021 to standardize media authenticity.

Young, co-chair of the study, explains more about what it all means:

What prompted the study?

“The motivation was two-fold,” Young says. “The first is the recognition of the moment we’re in right now. We know generative AI capabilities are becoming increasingly powerful. It’s becoming more challenging to distinguish between authentic content — like content that was captured by a camera versus sophisticated deepfakes — and as a result, there’s a huge uptick right now in interests and requirements to use those technologies that exist to disclose and verify if content was generated or manipulated by AI.

“The moment has been building, and we have a desire to help ensure that these technologies ultimately drive more benefit than harm, based on how they’re used and understood.”

Young adds that the paper is meant to inform the greater media integrity and authentication ecosystem, including creators, technologists, policymakers and others to understand what is and isn’t possible currently and how we can build on it for the future.

What did the study accomplish, and what did you learn?

The report outlines a path to increase confidence in the authenticity of media. The authors propose a direction they refer to as “high-confidence authentication” to mitigate the weaknesses of various media integrity methods.

Linking C2PA provenance to an imperceptible watermark can bring relatively high confidence about media’s provenance, she says.

She notes the report has a lot of caveats too, such as how provenance from traditional offline devices like cameras, which often lack critical security features, can be less trustworthy because it’s easier to alter.

It isn’t possible to prevent every attack or stop certain platforms from stripping provenance signals, so the challenge, Young says, “is figuring out how to surface the most reliable indicators with strong security built in — and, when necessary, reinforce them with additional methods that allow recovery or support manual digital-forensics work.”

How is this study different from others?

Young says their study investigated two “underexplored” lines of thought for the three methods of verification. They define the first as sociotechnical attacks, where provenance information or the media itself could be manipulated to make authentic content appear synthetic or fake content seem real during the validation process.

“Imagine you see an authentic image of a global sporting event with 80% of the crowd cheering for the home team,” she says. “The away team engages in an online argument claiming, ‘Hey, no, that’s all a fake crowd.’ Someone could make one small, insignificant edit to a person in the corner of the picture and current methods would deem it AI generated — even if the crowd size was real. These methods that are supposed to support authenticity are now reinforcing a fake narrative, instead of the real one.

“So, knowing how different validators work, even through really subtle modifications, you could manipulate the results the public would see to try to deceive them about content,” she says. The second key topic builds on the C2PA’s work to make content credentials more durable, while also addressing reliability. This is where the research is especially novel, Young says. “We looked at how provenance information can be added and maintained across different environments — from high-security systems to less secure, offline devices — and what that means for reliability.”

Why is verifying digital media so difficult?

Authenticating media is complex because there’s not a one-size-fits-all solution, Young says.

“You have different formats that have different limitations or trade-offs for the signals they can contain,” she explains. “Whether it’s images, audio, video — not to mention text, which has a whole different array of challenges — and how strong the solutions can be applied there.”

Young says there are different requirements and opinions about what level of transparency is appropriate as well. In some cases, users might not want any of their personal information included in the digital provenance of a piece of media, while in others, creators or artists might want attribution and to opt-in for having their information included.

“So, you have different requirements or even considerations about what goes into that provenance information,” she says. “And then, similar to the field of security, no solution is foolproof. So, all the methods are complementary, but each has inherent limitations.”

Where do we go from here?

Young says that as AI-made or edited content becomes more commonplace, the use of secure provenance of authentic content is becoming increasingly important. Publishers, public figures, governments and businesses have good reason to certify the authenticity of the content they share. If a news outlet shoots photos of an event, for example, tying secure provenance information to those images can help show their audience the content is reliable.

“Government bodies also have an interest in the public knowing that their formal documents or media are reliable information about public interest matters,” Young says.

She adds that as AI modifications to media become “increasingly common” for legitimate purposes, secure provenance can provide important context to help prevent an average reader or viewer from simply dismissing that content as fake or deceptive.

“For the industry and for regulators, we note how important continued user research in this area is to drive towards more consistent and helpful display of this information to the public — to make sure it’s actually meaningful and useful in practice,” Young says.

“We have a limited set of technologies that can assist us, and we don’t want them to backfire from being misunderstood or improperly used.”

Learn more on the Microsoft Research Blog.

The post A new study explores how AI shapes what you can trust online appeared first on The Microsoft Cloud Blog.

• Wave 3 of Microsoft 365 Copilot
• Expanded model diversity with Claude and next-gen OpenAI models available today
• General availability of Agent 365 on May 1 for $15 per user
• General availability of the new Microsoft 365 E7: The Frontier Suite on May 1 for $99 per user

Frontier Transformation is a holistic reimagining of business, aligning AI with human ambition to achieve an organization’s highest aspirations. It is the next evolution of AI Transformation — not only do we need to deliver efficiency and productivity, but we need to democratize intelligence and do more for humanity. Companies do not want or need more AI experimentation. They need AI that delivers real business outcomes and growth.

In my daily conversations with customers and partners, they typically question what the most important components of an AI solution are. Is it the model? Is it silicon? At Microsoft, we believe the two most essential elements of Frontier Transformation are Intelligence + Trust. Organizations need to harness their own unique work intelligence as they build agents and solutions; and all AI artifacts across their technology stack must be observed, managed and secured to ensure they are delivering value responsibly. 

Intelligence that shows up in real work 

I often say that zero-shot artifact creation is nothing more than a parlor trick. Models can reason over data, produce draft documents, presentations and spreadsheets, but they do not understand work. Real differentiation comes from intelligence — deep work context, embedded in the tools people already use. AI should amplify your intelligence but do so in a manner that protects your differentiation and unique value.

Work IQ amplifies an individual’s IQ by tapping into your organization’s IQ. It is the intelligence layer that enables Microsoft 365 Copilot and agents to know how you work, with whom you work, and the content upon which you collaborate. That is why Copilot is faster, more accurate and more trusted than solutions built on models and connectors alone.

This month, we are unleashing Work IQ with our next generation of agentic experiences in Wave 3 of Microsoft 365 Copilot in Word, Excel, PowerPoint and Outlook. Employees will have an enhanced chat experience in Copilot with the ability to create and augment artifacts, and the power to build their own agents within the canvas they work in every day.

Microsoft 365 Copilot is model diverse by design. Rather than betting on a single model, we built a system that makes every model useful at work. Customers get the choice, performance and flexibility in an open, heterogenous environment.  Copilot leverages leading models from OpenAI and Anthropic, operating openly across clouds and data services without locking customers in. Claude is now available in mainline chat in Copilot via the Frontier program, alongside the latest generation of OpenAI models.

Microsoft 365 Copilot Wave 3 is not just a singular release of new capabilities but rather a commitment to continuous innovation. We will bring frontier capabilities with enterprise promises for our customers in an open and model diverse manner. Another great example of this is Copilot Cowork, which is in research preview. Built in close collaboration with Anthropic, we are bringing the technology that powers Claude Cowork into Microsoft 365 Copilot to enable long-running, multi-step work that unfolds over time.  Click here to learn about our Wave 3 news in more detail.

These announcements come as our customers across industries are already seeing the value of Microsoft 365 Copilot. Microsoft recently delivered its strongest quarter yet with Copilot, with paid seats growing more than 160% year over year and daily active usage up ten times, as customers increasingly make Copilot a core part of everyday work. Expansion is also accelerating as the number of customers deploying Copilot at significant scale — more than 35,000 seats — tripled year over year. Just last week, Mercedes Benz announced a global rollout of Microsoft 365 Copilot, following recent investments from NASA, Fiserv, ING, the University of Kentucky, the University of Manchester, the U.S. Department of the Interior and Westpac. This is in addition to the 90 percent of the Fortune 500 who now use Copilot.

Trust: from agent experimentation and sprawl to enterprise control 

The speed of agent development and proliferation tells us customers see value, but without guardrails the pace of adoption turns into blind spots, diminished ROI and real security risk. As AI agents become more capable and autonomous, trust is nonnegotiable. IDC predicts 1.3B agents in circulation by 2028, and 80% of the Fortune 500 are already using Microsoft agents, led by operationally complex industries like manufacturing, financial services and retail.

That is why I am excited to announce the May 1 general availability of Microsoft Agent 365, the control-plane for AI agents. Priced at $15 per user, Agent 365 gives IT and security leaders a single place to observe, govern, manage and secure agents across the organization — using the same infrastructure, applications and protections they rely on to manage people today.

We are seeing tremendous momentum with our preview customers. In just two months, tens of millions of agents have appeared in the Agent 365 Registry. We have tens of thousands of customers that are already adopting Agent 365 to securely govern and scale AI agents across enterprise workflows.

At Microsoft, we are also using Agent 365 as Customer Zero and the early signals are clear. We now have visibility into more than 500,000 agents across the company with the most widely used focused on research, coding, sales intelligence, customer triage and HR self-service. That adoption is translating into real work. Over the past 28 days alone, agents have been generating more than 65,000 responses every day for employees. This is evidence that we are not simply experimenting, we are embedding agents in the flow of everyday work and empowering human ambition.

Introducing the Frontier Suite

To meet this demand, I am thrilled to announce we are bringing Intelligence + Trust together with Microsoft 365 E7: The Frontier Suite. Microsoft 365 E7 unifies Microsoft 365 E5, Microsoft 365 Copilot and Agent 365 into a single solution powered by Work IQ and integrated with the apps and security stack customers already rely on. It includes Microsoft Entra Suite and advanced Defender, Intune and Purview security capabilities, delivering comprehensive protection across agents and employees.

Customers have told us E5 alone is no longer enough; they do not want multiple tools stitched together, they want one trusted solution. At $99 per user, E7 is priced below purchasing these capabilities à la carte, giving customers a simpler, more cost-effective way to deploy enterprise AI at scale.

With the general availability of Agent 365 and the latest agentic experiences in Microsoft 365 Copilot offered as one Frontier suite, AI moves from experimentation to durable, enterprise-wide value, built on a foundation of Intelligence + Trust. This is how we make Frontier Transformation real. Microsoft is not just imagining the future of AI, we are empowering organizations across industries and around the world to build it.

The post Introducing the First Frontier Suite built on Intelligence + Trust 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.

Transform the way care teams work with Dragon Copilot

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:

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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.

Dragon Copilot/Marketplace video placeholder

“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.

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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

Connect with a Dragon Copilot product specialist

• 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.

The post Unify. Simplify. Scale: Microsoft Dragon Copilot meets the moment at HIMSS 2026 appeared first on The Microsoft Cloud Blog.

Microsoft Global Skilling helps people and organizations build the skills they need to thrive in an AI‑powered world. Within Global Skilling, the Learning Lab is the innovation engine—a team focused on designing, testing, and evolving modern learning experiences to continuously improve how skills are developed, validated, and applied in the flow of work. 

AI is reshaping how organizations work. Teams aren’t just adopting new tools—they’re also figuring out how those tools fit into existing workflows, roles, and expectations, all while trying to keep pace with business demands in a rapidly changing landscape. It’s a heavy lift. As the leader of the Learning Lab team, I’m navigating these same pressures, along with my team members, as we balance day-to-day delivery with the need to evolve our processes in real time. That’s why we’re embedding AI assistants and agentic workflows into internal processes—using them not only to work differently but also to learn differently. Through experimentation, we’re uncovering new ways to streamline operations and improve the learner experience for our global audience.  

This blog highlights three of our team’s most impactful AI initiatives that could also benefit your organization. Inspired by these projects, we developed A Practical Guide for Bringing AI into Your Business Processes, featuring real-world examples and actionable ideas for integrating AI and human expertise across your organization. 

A Practical Guide for Bringing AI into Your Business Processes

Download the guide

3 impactful AI initiatives leading the way

1. Reducing time-intensive coordination to optimize research 

The challenge of coordinating teams for research  

Before any learning materials can be built, our team conducts extensive research to understand new technologies, identify required skills, and validate what learners need. This early-stage analysis requires input from multiple stakeholders and a deep review of internal documentation, product roadmaps, and existing training materials.  

How AI is helping accelerate our research tasks and optimize cross-team input 

One of the biggest bottlenecks for our research workflows has been the time it takes to synthesize information and align teams around what a course should achieve. To improve this, we began experimenting with Researcher in Microsoft 365 Copilot and persona-based agents to support our research and planning stages. Our new process looks like this: 

• Researcher synthesizes internal documentation, product roadmaps, and existing training materials to surface emerging themes and identify knowledge gaps. With the ability to process thousands of pages in minutes, it flags potential course objectives the team might have missed.
• In parallel, persona-based agents simulate the perspectives of stakeholders from varying teams to help validate ideas before bringing them to the key decision-makers.
• Throughout this process, our team members guide these AI tools through every step—providing the business context, analyzing AI outputs to identify gaps or inconsistencies, refining direction, and ensuring consideration of broader business objectives.  

In our experience with AI handling synthesis and early-stage validation, we’ve reduced the time required for core research processes from two weeks to just one day. This significant time savings extends to every course developed with this method, enabling us to redirect focus toward shaping stronger strategies, aligning content with business impact, and accelerating decision-making across teams.

Applying this approach in your organization 

AI-supported research and planning can help you make sense of complex information faster and build alignment earlier in your decision cycles. By using AI to synthesize documents, surface patterns, and validate assumptions, you can reduce the effort required to get teams on the same page. Your team members can then focus on refining strategy, confirming business priorities, and shaping higher-impact decisions. This combination improves speed and clarity throughout cross-functional work.  

Explore A Practical Guide for Bringing AI into Your Business Processes to learn more about how you can apply this in processes like: 

• Drafting onboarding plans that human resources (HR) leaders can tailor to company culture.
• Developing quarterly sales plays informed by shifting buyer behavior and competitor activity.
• Creating campaign briefs rooted in audience insights, market trends, and performance data.
• Developing forecasting assumptions by synthesizing inputs from sales, operations, and historical data. 

2. Transitioning from manual maintenance to continuous quality improvements 

The challenge of shorter content lifecycles  

We maintain thousands of courses and lab environments as part of our skilling initiatives for Microsoft technologies. With the fast pace of product evolution, it can be challenging to keep learning content accurate and functional.  

How GitHub Copilot became the maintenance partner for the team 

We recognized that the demands for maintaining learning content were increasing beyond our capacity to manage effectively. So we integrated GitHub Copilot into the content maintenance workflow like this: 

• GitHub Copilot tools analyze content repositories—flagging inconsistencies, identifying outdated examples, and recommending updates based on current documentation.
• Throughout this process, our team reviews and refines the AI-generated recommendations. When GitHub Copilot flags an issue, we evaluate how those changes might apply to other training courses. We also ensure that all revisions align with learning objectives and verify that security and accessibility standards are met.
• Then GitHub Copilot helps implement some of the suggested updates, like generating new code samples or suggesting environmental configurations that align with the latest product releases. 

As a result, our team has reduced the time we spend on routine content maintenance by up to 25%. And with these time savings, team members can shift from reactive updates to proactive innovation—evaluating emerging skills, shaping next-generation modules, and exploring how agents, simulations, and personalized learning could improve outcomes. 

Applying this approach in your organization 

AI-assisted maintenance can help you keep large, fast-changing content ecosystems accurate and up to date without overwhelming your teams. By using AI to surface inconsistencies, flag outdated material, and recommend updates, you can dramatically reduce time spent on routine fixes. Your experts can then focus on reviewing changes for accuracy, regulatory needs, and strategic intent. This balance enables you to maintain quality at scale while freeing your teams to invest in higher-value innovation.  

Explore A Practical Guide for Bringing AI into Your Business Processes to learn more about how you can apply this in processes like: 

• Maintaining and updating sales enablement content as product and service offerings evolve.
• Keeping product messaging frameworks and campaign assets consistent and up to date.
• Updating help center articles and support workflows after feature releases.
• Updating contract templates and clause libraries to align with new regulatory guidance.

3. Delivering inclusive learning at scale through diverse content formats 

The challenge of content relevance and engagement  

Our learners span every continent, speak dozens of languages, and have their own preferred learning methods. Creating multimodal, accessible, and inclusive learning experiences while managing constant content updates was stretching the team thin.  

How AI helps scale and translate content for global learners  

To support different learning styles and languages, we’re piloting how to create immersive, inclusive learning through two experiments with AI: 

1. We’re using AI tools to turn a single source of training content, like a session transcript or recording, into multiple formats, such as videos, podcasts, and recap summaries. This multimodal output lets us update learning materials at the pace required by our global audience and helps ensure that we’re reaching learners in their preferred formats.
2. We’re piloting an AI-powered tool that not only translates content but also generates avatars that deliver multilingual voiceovers with more natural lip-sync, eliminating one of the most distracting elements of dubbed content. 

Early results show that we can now recover up to 15 hours per course we develop—time our team can spend on more nuanced work that AI can’t do, like adapting cultural references, verifying that tone and pacing match learning objectives, and maintaining brand voice. 

Applying this approach in your organization 

AI-powered localization can help you deliver content that feels native to every audience you service, no matter the language or market. By pairing AI’s speed in translation, voiceover, and prompt generation with your team’s expertise in cultural nuance and brand standards, you can scale global engagement without diluting quality. This combination lets you reach more learners, customers, and employees while keeping your message consistent and relevant across regions.  

Explore A Practical Guide for Bringing AI into Your Business Processes to learn more about how you can apply this in processes like: 

• Localizing campaign assets for regional markets across languages and cultural norms.
• Tailoring pitch decks and demos for industry-specific or region-specific buyers.
• Creating multilingual chatbot responses and support scripts for global customers.
• Adapting standard operating procedure and process documentation for different facilities or regional regulations. 

Building skills and strengthening our AI strategy

As AI becomes an extension to the Learning Lab, we’ve discovered that it’s much more than just implementing new tools—it’s also a journey of building technical and human skills across the team. Our experiments require every team member to stretch into new capabilities, from process optimization and innovation to strengthening collaboration and creative problem-solving. As a result, we’ve been able to spend less time on repetitive tasks and to dedicate more energy to the kind of creative, relationship-driven work that leads to exceptional learning experiences. 

Looking to build skills for you and your teams? Explore AI Skills Navigator, the agentic learning space that brings together AI-powered skilling experiences and credentials that help individuals build career skills and organizations worldwide accelerate their business.

The post How to bring human expertise and AI together: 3 impactful initiatives appeared first on The Microsoft Cloud Blog.

To support these confidential environments, Microsoft offers full stack capabilities that support customers across connected, intermittently connected, and fully disconnected modes. Today’s expansion of capabilities includes three major updates:

• Azure Local disconnected operations (now available) – Organizations can now run mission-critical infrastructure with Azure governance and policy control, with no cloud connectivity, optimizing continuity for sovereign, classified or isolated environments.
• Microsoft 365 Local disconnected (now available) – Core productivity workloads, Exchange Server, SharePoint Server, and Skype for Business Server, can run fully inside the customer’s sovereign operational boundary on Azure Local, keeping teams productive even when disconnected from the cloud.
• Foundry Local adds large model and modern infrastructure capabilities – Organizations can now bring large AI models into fully disconnected, sovereign environments with Foundry Local. Using modern infrastructure from partners like NVIDIA, customers with sovereign needs will now be able to run multimodal models locally on their own hardware, inside strict sovereign boundaries enabling powerful, local AI inferencing in fully disconnected environments.

This delivers a truly localized full stack experience built on Azure Local infrastructure and Microsoft 365 Local workloads, designed to stay resilient across any connectivity condition, with large models being part of Foundry Local extending the stack to run advanced multimodal models locally, securely, even when fully disconnected. Customers can now help maintain uninterrupted operations, keep mission critical workloads protected, and apply consistent governance and policy enforcement, while keeping data, identities, and operations within their sovereign boundaries.

Azure Local runs critical infrastructure locally, even when disconnected

For workloads with specialized requirements, Azure Local provides the on-premises foundation with consistent Azure governance and policy controls. With Azure Local disconnected operations, management, policy, and workload execution stay within the customer-operated environments, so services continue running securely even when environments must be isolated or connectivity is not available. Using familiar Azure experiences and consistent policies, organizations can deploy and govern workloads locally without depending on continuous connection to public cloud services. Azure Local is designed to scale with mission-critical needs from smaller deployments to larger footprints that support data-intensive and AI-driven workloads. Customers can start fast, expand over time, and maintain a unified operational model, all within their sovereign boundary.

Operating in disconnected environments surfaces constraints that go beyond traditional cloud assumptions: external dependencies may be unacceptable, connectivity may be intentionally restricted, and operational continuity is a business imperative.

“The availability of Azure Local disconnected operations represents a breakthrough for organizations that need control over their data without sacrificing the power of the Microsoft Cloud. For Luxembourg, where digital sovereignty is not just a principle but a strategic necessity, this model offers the resilience, autonomy, and trust our market expects. By combining Microsoft’s technological leadership with Proximus NXT’s sovereign cloud expertise, we are enabling our customers to innovate confidently – even in fully disconnected mode,”said Gerard Hoffmann, CEO Proximus Luxembourg.

Microsoft 365 Local keeps productivity and collaboration available in fully disconnected environments

As sovereign environments move into disconnected environments, keeping people productive becomes just as critical as keeping infrastructure online. Building on more than a decade of delivering and supporting these services, Microsoft 365 Local disconnected brings that continuity to the productivity layer, delivering Microsoft’s core server workloads—Exchange Server, SharePoint Server,and Skype for Business Server supported through at least 2035—directly into the customer’s sovereign private cloud.

With Microsoft 365 Local, teams can communicate, share information, and collaborate securely within the same controlled boundary as their infrastructure and AI workloads. Everything runs locally, under customer-owned policies, with full control of data resiliency, access, and compliance. By operating with Azure-consistent management and governance, customers get the productivity experience they rely on, designed to stay resilient and secure even when offline.

Bringing large models and modern infrastructure to Foundry Local

With the availability of larger models and modern infrastructure as part of the Foundry Local portfolio, Microsoft is enabling customers with highly secure environments the ability to run multimodal, large models directly inside their sovereign private cloud environments. This brings the richness of Microsoft’s enterprise AI capabilities to on-premises systems, complete with local inferencing and APIs that operate completely within customer-controlled data boundaries.

Expanding beyond small models, the integration of Foundry Local with Azure Local is specifically designed to support large-scale models utilizing the latest GPUs from partners such as NVIDIA. Microsoft will provide comprehensive support for deployments, updates, and operational health. Even as inferencing demands increase overtime, customers retain complete control over their data and hardware.

Choice and control without added complexity

Customers facing strict sovereignty and regulatory requirements are clear that a fully disconnected sovereign private cloud is a key business need. Microsoft Sovereign Private Cloud is designed to meet these needs head-on, enabling secure, compliant operations even in environments with no external connectivity. At the same time, we recognize that disconnected environments are not one-size-fits-all; some customers operate across connected, hybrid, and disconnected modes based on mission, risk, and regulation. Our approach helps customers to meet strict sovereign requirements in fully disconnected scenarios without compromising simplicity, while retaining flexibility where connectivity is possible. Together, Azure Local disconnected operations, Microsoft 365 Local, and Foundry Local help organizations choose where workloads run and how environments are managed, while standardizing governance and operational practices across connected and disconnected deployments.

Next steps

Get started

• Azure Local disconnected operations and Microsoft 365 Local disconnected are now available worldwide, and large models on Foundry Local are available to qualified customers.
• Explore the Microsoft Sovereign Cloud
• Learn more about Azure Local disconnected operations

The post Microsoft Sovereign Cloud adds governance, productivity, and support for large AI models securely running even when completely disconnected appeared first on The Microsoft Cloud Blog.

That’s why I’m excited to share that Microsoft Azure has completed an independent, industry‑led GxP supplier audit conducted through the Joint Audit Group managed by Ingelheimer Kreis (IK).

GxP refers to regulations that ensure quality, safety, and data integrity in highly regulated environments, particularly in life sciences. This milestone provides independent validation that Azure’s systems and processes meet the standards required to support regulated workloads in the cloud, giving organizations greater confidence to accelerate their AI transformation and scale innovation responsibly.

“Overall, the audit observed strong organizational maturity, robust processes, and effective governance structures. Microsoft demonstrated a high degree of transparency, collaboration, and readiness to address regulatory expectations. Furthermore, Microsoft demonstrated strong maturity in quality, security, compliance, engineering, and operational processes. The organization showed strong commitment from leadership and robust operational controls.”

As quoted by the Joint Audit Group managed by Ingelheimer Kreis

This milestone builds on Azure’s longstanding commitment to compliance, reinforcing trust across life sciences and other highly regulated industries while helping accelerate broader cloud and AI adoption.

Raising the bar for cloud trust in life sciences and beyond

IK conducted a GxP-aligned supplier audit of selected aspects of Microsoft’s cloud service operations within an agreed scope. The sessions provided insight into governance, security and software engineering practices, and operational processes that may impact regulated GxP use of Microsoft Azure and related services. The audit was performed using a spot-check approach and reflects the information presented by Microsoft during the sessions. The IK audit results provide IK members with assurance regarding the Azure controls environment, enabling members to work to remove compliance blockers, accelerate their adoption of Azure services, and obtain confidence and trust in the security and sovereignty controls of Azure.

The joint GxP audit provides pharmaceutical and life sciences organizations with a higher level of confidence that Azure’s operational, security, and compliance practices meet industry expectations for validated GxP workloads. By having a coalition of major pharmaceutical manufacturers audit Microsoft’s cloud controls, customers gain assurance that Azure’s change management processes, evergreen update model, and underlying operational rigor align with the standards historically required in on-premises validated environments. This independent industry assessment reduces longstanding adoption barriers for regulated workloads and gives customers a basis for trusting Azure as a compliant, reliable platform for GxP relevant applications.

Microsoft Azure is designed to meet stringent requirements for data residency, privacy, and compliance. With Microsoft, organizations can keep sensitive data within defined geographic boundaries and under local jurisdictional control.

Microsoft offers a comprehensive set of compliance offerings to help organizations comply with national, regional, and industry-specific requirements. Backed by more than 100 compliance certifications—including ISO, HIPAA, and HITRUST, Azure meets rigorous security and privacy requirements across global and industry frameworks.

Securing the future: a collaborative approach

Security and compliance in the cloud is a shared responsibility, and the division of those responsibilities between the cloud service provider and customer depends on the cloud offering utilized. Microsoft works to ensure that we are compliant with industry and international standards, and customers are responsible for ensuring their data within the Microsoft Cloud is protected in a manner that is compliant with the standards and regulations imposed on the customer.

Azure integrates with services such as Microsoft Purview Compliance Manager and Defender for Cloud to provide organizations with visibility into their compliance posture and enable proactive governance across cloud environments.

We also provide clear guidance and detailed, auditable evidence through the Microsoft Trust Center and the Service Trust Portal. These tools exist to give customers transparency and confidence, pairing high‑level trust principles with concrete proof customers can use to meet their own regulatory and assurance needs.

With independently audited controls now recognized by leading multinational pharmaceutical companies, Azure gives life sciences organizations the confidence to run their regulated workloads in the cloud—so they can focus on what truly drives value: discovering new therapies, accelerating R&D, scaling clinical operations, and manufacturing medicines reliably at global scale. Instead of diverting resources toward duplicative cloud platform audits, customers can trust that Azure’s underlying operational rigor, change management processes, and security practices meet GxP expectations.

The audit strengthens the foundation that lets life sciences innovators move faster, modernize safely, and keep their focus on bringing breakthrough medicines and devices to patients. For more information on the audit, contact the team.

Empowering our customers

Microsoft remains committed to meeting today’s compliance, security, and regulatory standards. Across our cloud platforms and services, we maintain rigorous and independently validated controls, adhere to applicable laws and industry requirements, and continually strengthen our frameworks to protect the confidentiality, integrity, and availability of customer data. This commitment is reinforced by foundational company policies, a robust global compliance program, and active oversight from senior leadership—ensuring that every Microsoft offering is built on trust, transparency, and responsible innovation.

By working with industry leaders and regulators to shape compliance frameworks and advance sovereign cloud capabilities, Azure supports the next era of regulated AI innovation. By upholding these standards, we empower organizations in regulated industries to operate confidently, knowing their workloads run on a platform designed to meet stringent expectations today and evolve alongside emerging regulatory guidance, validated by independent experts and experienced by customers every day.

More on our approach to trust and compliance

• Dive deeper into how leading life sciences organizations are building readiness and resilience with trusted cloud platforms. Explore the e-book, Reshaping Manufacturing and Supply Chain in Pharma and MedTech, to discover actionable strategies for compliance, innovation, and operational excellence in regulated manufacturing.
• Explore From Vision to Value: AI Use Cases Transforming Healthcare to learn how healthcare and life sciences organizations are applying AI today on trusted cloud platforms.
• To learn more about Microsoft’s approach to trust and compliance, explore resources at the Microsoft Trust Center.

Connect with us at upcoming industry events to see how Azure can help your organization achieve more with confidence.

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