The more time I spend working with AI, the more convinced I become that what matters most for her future isn’t how quickly she can answer. It’s whether she has the judgment to know when an answer can be trusted.

I’ve spent decades at Microsoft watching this tension play out: first building tools for other developers, then working across AI as models moved from research curiosities to systems deployed at scale. Now we’re building Microsoft IQ, where we’re exploring how an organization’s collective intelligence can become its greatest advantage. Through every one of those chapters, one thing has remained true: it’s never enough for a system to be powerful; it must also be trustworthy.

Trust is what turns assistance into delegation. When we can trust an agent to do what we intend, within the limits we set, we can hand off the work we never wanted to spend our lives on: the repetitive tasks that drain attention, the mundane work that fills a day without moving anything meaningful forward, the dangerous work humans should not have to do, the work too vast for any individual or team. Agents should take on that toil, extend our reach, and give us back our time for the work that calls for something only humans bring.

My daughter doesn’t know any of this yet. But by the time she’s grown, most of the work that rewards speed and repetition will be work we delegate. What will matter then is exactly what gave her teachers pause: the patience to stay with a hard problem, reason through it, and decide when she’s reached a conclusion she can trust. The very thing they feared might hold her back could be exactly what the next era prizes most.

So no, I’m not worried about the timed test. I hope she grows up in a world where software carries the toil and people are freed for the work that is unmistakably ours—to think, to judge, to create, to care for one another. That is the future I want agents to make real. But my hope is not evidence it will happen. The future I just described depends on a single question: can we trust agents to do the work? Trust is earned one task at a time. So, I went looking for evidence of where it’s been earned, and where it hasn’t.

We partnered with MIT Technology Review Insights on new research that draws directly from the technical leaders building this frontier: not the people talking about it, but the people doing it. We surveyed 300 technical experts across AI, data, and cloud domains, spanning 12 industries and 4 regions of the world, asking them to rank their confidence across 101 of the top tasks. What we got back is the 2026 Agent Confidence Index, an honest map of where agents are delivering real value, so our community can see what’s working and move forward together with conviction.

Learn from where confidence is highest

Across the 101 tasks measured, average confidence already lands at 64 out of 100, and thirty tasks clear 70. The highest scores cluster on work that is both predictable and draining: the late nights, the interruptions, the low-value repetition. Automated report generation leads at 83.5. Boilerplate code generation for new features sits at 82.5—the hours a developer no longer spends rewriting the same patterns, freed for the work that challenges them. Certificate expiration monitoring and renewal, at 81.5, ends the scramble that pulls engineers off high-stakes problems for something entirely routine. Real-time data stream monitoring follows at 80.5, and release note generation from commit history at 79.5—the manual end-of-sprint commit review, gone. This is where frontier teams are already delegating to agents, regularly.

The pattern holds across every discipline. In developer and AI workflows it extends to API client maintenance and code identification; in cloud operations, to ticket routing and cost optimization; in data, to anomaly detection. Wherever it sits in the stack, this is work technical teams now trust agents to own.

What matters most here isn’t what the data says about the tasks; it’s what it says about the people delegating them. When technical experts believe in something deeply enough to hand it real work, that belief ripples outward. It becomes the recommendation they make to their leadership, the solution they build for their customers, and the culture they create for their teams.

Even the toughest agent tasks are gaining traction

Here’s what strikes me most: the tasks ranked lower on the index are still high in absolute terms. Service mesh configuration and troubleshooting sits at 37.5, database schema migration scripting at 46.5, memory leak detection at 48.5. These sit at the very frontier, the interconnected, high-stakes work where investment and innovation are concentrated right now.

Consider what they demand. Service mesh configuration touches many systems at once. Database migration carries real stakes, requiring precision across data, application, and infrastructure layers at the same time. Memory leak detection means diving deep into a system’s behavior under load, accounting for conditions that shift from one deployment to the next. These are the challenges that have separated great engineers from exceptional ones—and even here, experts see agents helping. Not carrying the work alone, but contributing where it used to be unthinkable. That confidence is still climbing, and that’s telling.

We’re shipping new capabilities constantly to support this momentum. Database migration tooling in GitHub Copilot now covers not just scripts but the full application and infrastructure migration story. The Azure Site Reliability Engineering (SRE) Agent brings decades of experience operating Azure at scale and deep profiling capabilities directly into memory analysis and performance diagnosis.

Why human judgment remains paramount

When we asked technical experts how they’re navigating agent adoption, 59% named “keeping humans in the loop” as their top priority—ahead of better observability, ahead of governance documentation, and ahead of everything else. That’s a mark of maturity. Teams moving forward with clarity treat agent oversight as non-negotiable, regardless of how capabilities evolve.

The boundary itself is straightforward. Agents excel at well-specified, high-volume, reversible work: they synthesize data, automate known workflows, and surface anomalies at a speed and scale no human team could match. The moment a decision becomes high-stakes, context-dependent, or hard to undo, a human signs off. That isn’t a limitation of the technology; it’s the architecture of a trustworthy system.

What’s changing, and what remains underappreciated, is the skill it takes to draw that boundary well: the discipline of full-lifecycle evaluations and guardrails. Success means measuring agent output against intent and keeping behavior inside your business strategy. It’s new territory for most engineering teams, and it’s becoming table stakes for modern software faster than most organizations realize. The good news: the same tools generating the work can help you build the harness. Ask GitHub Copilot to write the evals and it will. Frontier teams are already doing this, and it’s why they’re pulling ahead.

Agents are opening career doors for engineering

Across system reliability and site operations, evaluations and quality assurance, and data pipeline management, 80% or more of respondents see meaningful career opportunity ahead. We believe this is one of the most significant moments in the history of building software, not because agents replace what technical people do, but because what’s left when they take on the toil is the work that defines a career: the judgment calls, the architectural vision, the reasoning to navigate complexity under pressure. That fluency will define the next generation of technical leadership.

We’re living this shift at Microsoft, right alongside our customers. Junior developers are using agents to explore codebases on their own and arriving at mentoring conversations with sharper, more sophisticated questions. Senior engineers are covering more ground because the repetitive work that used to fill their days is now delegated, and the work that’s left is harder, interesting, and consequential. Both are growing into more capable versions of themselves. For me, that’s the outcome I’ve always believed technology could deliver.

An integrated approach to intelligence and trust

Designing more sophisticated agent systems has made one thing clear: agents thrive in well-integrated environments, working best when your whole stack draws on a single source of truth. The high-confidence tasks are the ones we’ve already figured out; the meaningful frontier is the harder, interconnected work, and that’s exactly where observability, governance, security, and unified intelligence have to operate as one.

Microsoft IQ brings your enterprise context into a single, continuous intelligence layer. Within it, Work IQ builds semantic understanding of how your business operates across email, calendar, meetings, chats, files, people, and collaboration patterns. Such depth of knowledge is the reason technical teams choose us, and it’s what drives my focus and passion in learning how people actually work so their agents get them. My colleague Kim Manis, CVP of Product for Microsoft Fabric, has written specifically about what this means for data professionals, and the integral role of Fabric IQ.

It’s all part of the Microsoft Agent Platform, which is becoming the operating system for enterprise AI at scale. From building in GitHub and contextualizing with Microsoft IQ, to running in Microsoft Foundry and governing in Microsoft Agent 365, Microsoft is uniquely positioned to help customers bring together data, models, agents, and human judgment into a continuously improving and secure system.

Frontier transformation is being led by builders like you.

Next steps:

• Download The 2026 Agent Confidence Index from our partners at MIT Technology Review Insights. It is a free, ungated deep dive into all 101 tasks, broken out by role and workflow, with the patterns and reasoning behind where confidence is strongest and the frontier is expanding.

• Join us at the AI Engineering World’s Fair (June 29-July 2) where our very own Pablo Castro will keynote, and our teams will offer 16 breakout sessions and 4 labs. Swing by the Microsoft booth as well to explore an interactive 3D visualization of the Index data. We want to hear what’s working for you.

• Learn more about Microsoft IQ and how it connects across Work IQ, Fabric IQ, Foundry IQ, and the newly announced Web IQ. You can catch up on all the developer innovation from Microsoft Build through Satya Nadella’s keynote, Kyle Daigle’s blog post, and the Microsoft Build CLI.

What’s Working in Agentic AI

The 2026 Agent Confidence Index report reveals where agents are trusted, the challenges they face, and what leaders should do next

Download the 2026 Agent Confidence Index

The post The 2026 Agent Confidence Index: Where 300 builders see real momentum appeared first on The Microsoft Cloud Blog.

1. Will AI amplify the intelligence of my organization and the attributes that make my company unique within its industry to grow my business; or will it use my intelligence for its own benefit, learning from my most important business flows and leveraging my intellectual property?
2. Can I trust that the outcomes are providing durable return on investment and that these solutions are running within the confines of my governance and security standards?
3. How do I get the visibility, control, flexibility and business model innovation needed to manage the costs associated with AI and maximize value?

I consistently advise customers that they need to build their own IQ on a platform of intelligence that is model-diverse, open and heterogeneous at every layer of the stack. Models are commoditizing. No company should be dependent upon any one model or any one model’s harness. Over the weekend, Satya warned of a world where every company across every sector is ceding value to a few models that eat everything they see. AI that is intended for growth should amplify the intelligence of an organization so that it compounds from within.

Companies also need an observability platform that provides governance, management, security and Financial Operations (FinOps) to ensure the ROI with AI. This enables AI to be trusted within the environment over which it reasons and puts the business in control of the outcomes.

Intelligence + Trust is embedded across Microsoft 365 Copilot, GitHub Copilot and Copilot Studio, where model diversity aligns cost and performance to each task. Microsoft IQ optimizes workflows, so context is routed efficiently and reduces unnecessary compute. Agent 365 is the control plane to observe, govern, manage and secure agents. We have built a system to manage AI spend as a core enterprise capability, not an afterthought. It is delivered across clouds and model providers without locking customers into a single approach.

Managing costs at scale

As agent usage scales, organizations need a clear set of levers to manage cost:

Model diversity. Any given inferencing model, model harness or agentic loop on its own does not help build out an organization’s IQ in ways that compound its intelligence. Both Microsoft 365 Copilot and GitHub Copilot are model-diverse by design without locking customers into a single provider. Different models — like GPT-5.5 or Claude Opus 4.8 — serve distinct roles with different economics. Matching the right intelligence to each task optimizes performance and cost.

Your IQ. Agents struggle with raw data. Significant compute is spent interpreting structure and context before useful work begins. The Microsoft IQ platform empowers your IQ by turning raw data into usable intelligence, continuously building a semantic understanding of how your organization operates across Microsoft 365 and line-of-business systems. It provides agents with the context they need upfront rather than requiring them to reconstruct it. The result is measurable: faster execution, higher accuracy and lower token usage. This is how intelligence compounds within your organization.

Financial operations. FinOps became critical when companies moved to the cloud and requires even greater attention as AI shifts from fixed pricing to usage-driven models. With Foundry and Agent 365, we are providing tools to help our customers optimize their AI costs today.

Frontier business models

Business models are evolving as we use AI to drive business outcomes. The User Subscription License (USL) has become the foundation, providing a package of capabilities for a predictable per-user-per-month fee. Usage-based licensing has emerged for long-running, multi-tasking agents, where cost aligns directly to the work performed.

Microsoft gives customers a unique combination of business model flexibility and integrated product experiences that is unmatched in the market. Microsoft 365 Copilot and GitHub Copilot use both models — a USL offering with not only value and capabilities, but flexible consumption on top. Today we’re announcing the general availability of Copilot Cowork worldwide, which requires the Microsoft 365 Copilot USL and is then usage-based.

Our model-diverse strategy allows customers to purchase capacity with the flexibility to use the right model for the job based on model strengths, economics and the latest innovations. Microsoft Agent Factory provides a single consumption model spanning Microsoft 365 Copilot (including Cowork), GitHub Copilot and agents built in Fabric, Foundry and Copilot Studio.

Our integrated product experiences put AI in the flow of work for both knowledge workers and software developers and manage capacity fluidly across the two. Historically these personas have been distinct, but increasingly the line between them is blurring. Coding is becoming a mainstream knowledge worker skill and chat and Cowork are becoming modalities important for software development. With Microsoft 365 and GitHub, we offer market-leading tools for both roles and make it easy to seamlessly manage capacity based on availability and need.

Agent 365: The control plane

As organizations adopt agents from Microsoft, another provider or build their own, a control plane is essential. Agent 365 gives IT and security leaders a single place to observe, govern, manage and secure agents across the organization. It builds on the Microsoft stack that enterprises trust: Entra for identity, Defender for threat protection, Purview for data governance and Intune for endpoint management. We are extending Agent 365 to include cost management, so organizations can monitor and manage agent spend alongside security and compliance. As the Frontier Firm operating model takes hold, leaders will manage human and agentic work as a single system, with visibility into both performance and cost.

The two most essential elements in any AI solution are Intelligence + Trust. At Microsoft, this conviction shapes how we design every layer of our AI platform. Microsoft IQ enables organizations to harness their own unique IQ, bringing context to data and embedding AI directly into the flow of work to deliver faster, more accurate and more trusted outcomes while safeguarding assets and protecting intellectual property. Agent 365 provides that trust layer, ensuring every agent and AI artifact is observed across the environment so organizations can move decisively from experimentation to enterprise impact with confidence. As Jay Parikh put it at Build, AI alone will not change your business. The system running it will.

We have built this system for our customers and partners, where intelligence compounds from within and every agent operates with control, visibility and trust. Together, we can scale human ambition and define how AI delivers measurable business impact across every role, organization and industry.

Judson Althoff is the chief executive officer of the commercial business at Microsoft. He is responsible for the product strategy, sales, services, support, marketing, operations and revenue growth of the company’s commercial business, which operates in more than 120 regional and national subsidiaries globally.

The post Achieving success with AI appeared first on The Microsoft Cloud Blog.

That tension shows up most clearly when AI systems cross borders—touching sensitive data, operating under different regulations, and supporting teams around the world.

Every four to five days, a new regulation targeting AI, cybersecurity, or data privacy is introduced—with more than 1,000 global policy initiatives across 69 countries, and 100-plus nations enforcing privacy laws.¹

In 2026, digital sovereignty is about managing risk, so you can scale AI using the tools and environments your business depends on as sovereignty requirements evolve. To maintain global velocity while managing risk, your steering committee should answer this fundamental question:

Can we meet localized requirements—controlling where data is processed, who can access systems, and how operations continue during disruptions—without additional complexity as requirements evolve?

To help leaders navigate these challenges, we offer a practical guide: Grow Your Business with AI You Can Trust. This guide provides a grounded approach to navigating sovereignty decisions in real environments, covering governance, operational control, and responsible AI deployment without adding unnecessary complexity.

Navigating the 5 common sovereignty scenarios

Sovereignty rarely shows up as a single requirement. If you’re scaling AI, you’re likely encountering it through a small set of recurring scenarios—often as you expand across regions, partners, and regulatory environments:

1. You operate in markets with evolving regulatory requirements.
   
2. You are scaling AI across regions and need clear governance over data processing.
   
3. You need provable controls over who can access sensitive data—across vendors, operators, and jurisdictions.
   
4. You must meet data residency requirements without fragmenting tools, teams, or operating models.
   
5. You need consistent control across global operations because downtime or loss of control in one region now has immediate impact across your business.
   

One example shows how these scenarios come together in practice.

Sovereignty in practice: Raiffeisen Bank International

Raiffeisen Bank International developed an internal generative AI assistant, using Microsoft Foundry to help employees summarize legal, regulatory, and banking documents and retrieve information more quickly. The platform supports employees across the bank’s operations in multiple European markets, helping staff resolve customer requests faster and focus on higher-value work.

Used by more than 20,000 employees, the solution provides faster access to critical information while supporting the bank’s regulatory and operational requirements across jurisdictions—without compromising safeguards.

Executive checklist: Scaling with resilience

Use the guide to align your AI steering committee on these critical checkpoints:

• Define trust: Establish clear Responsible AI principles for your brand.
  
• Secure by design: Shift to a security-first posture across all AI operations.
  
• Govern the loop: Use the “Map, Measure, Manage” framework to mitigate risks.
  
• Support sustainability: Build systems with socio-economic and environmental impact in mind.
  
• Ensure visibility: Confirm your platform supports the 4 capabilities needed for agent observability.
  
• Address digital sovereignty requirements: Understand common sovereignty scenarios and core principles to help your organization address them.
  

As AI becomes core to how your business operates, sovereignty moves from a technical consideration to a leadership one. Our e-book guide can help you understand sovereignty scenarios and principles to help your steering committee take the next step—clearly, confidently, and at scale.

¹ Footnote includes:

• “The AI regulations that aren’t being talked about,” Deloitte Insights, Deloitte, November 10, 2023
• OECD.AI: The OECD’s Hub for AI Policy, Organization for Economic Co-operation and Development
• “Building a Foundation for AI Success: Governance,” Microsoft Cloud Blog, Microsoft, March 28, 2024
• “2025 AI Index Report,” Stanford Institute for Human-Centered Artificial Intelligence
• “AI Regulations Around the World,” Mind Foundry Blog, Mind Foundry, January 13, 2026
• “Identifying Global Privacy Laws Relevant to DPAs,” IAPP News, International Association of Privacy Professionals, March 19, 2024
• “Data Protection and Privacy Legislation Worldwide,” UNCTAD, United Nations Conference on Trade and Development, February 17, 2026

The post Your AI steering committee’s 2026 checklist: Sovereignty appeared first on The Microsoft Cloud Blog.

• Author: You’re producing the work, calling on AI to help as needed — a line of code, a sentence, a chart.
• Editor: You set the intent and AI creates the first draft for you to edit and approve.
• Director: You create a spec and hand off entire tasks for AI to execute in the background.
• Orchestrator: You design a system where multiple agents run in parallel across a workflow, flagging exceptions and escalations to you.

Every business leader knows the world is changing, but far fewer have a clear picture of what to do about it. These four patterns are the place to start. The real work ahead for leaders is redesigning their firm’s operating model around the collaboration patterns.

As agent use increases, human involvement doesn’t disappear — it changes shape. What declines is the amount of tactical, step-by-step execution work humans do themselves. And what rises is the need for humans to set direction, define standards and evaluate outcomes.

Ultimately, the goal is not to move every task and business process to the fourth pattern. Instead, it’s up to leaders to help their organizations develop clarity around matching workstreams to the right collaboration pattern. That’s the shape of the Frontier Firm: defined by how deliberately leaders design work across functions, matching the level of human involvement to the outcome.

What the data shows

Our 2026 Work Trend Index research reinforces this shift across roles and industries. We analyzed trillions of anonymized Microsoft 365 productivity signals and surveyed 20,000 workers using AI across 10 countries. We also spoke with leading experts in AI, work and organizational psychology to help us unpack the insights from the data and understand where all this is going. The conclusion is consistent: the constraint is no longer what people can do, it is how work is structured around them.

• AI lifts individual potential. A privacy-preserving analysis of more than 100,000 chats in Microsoft 365 Copilot shows that 49% of all conversations support cognitive work — helping workers analyze information, solve problems, evaluate and think creatively. This shift is already visible in output, with 58% of AI users saying they’re producing work they couldn’t have a year ago, rising to 80% among Frontier Professionals, the most advanced AI users in our research. Additionally, when AI users were asked which human skills are most important as AI takes on more work, they said two topped the list: quality control of AI output (50%) and critical thinking — that is, analyzing information objectively and making a reasoned judgment (46%).
• The Transformation Paradox. We are seeing a pressure point emerge within the organization where the pull to perform collides with the push to transform. 65% of AI users surveyed fear falling behind if they don’t use AI to adapt quickly, yet 45% say it feels safer to focus on current goals than to redesign work with AI. And only 13% of workers say they’re rewarded for reinvention of work with AI even if results aren’t met. The same forces accelerating AI adoption are holding it back.
• Every organization is a learning system. Our results show that organizational factors like culture, manager support and talent practices account for more than 2X the AI impact of individual factors like mindset and behavior (67% vs. 32%). Specifically, the findings underscore the importance of an AI-ready environment: a culture that treats AI as a strategic advantage and encourages experimentation, managers who model and incentivize AI use and talent practices that build skills and create space to apply them. The real question isn’t whether people have the right skills, it’s whether the organization is built to unlock them.

The firms that build a new operating model today won’t just move faster in the short term. They’ll build something more durable, setting themselves up to create value in ways that we can’t yet conceive of: an organization that learns faster than its competitors, compounds its own intelligence and gets harder to catch with every cycle.

For deeper analysis, see the 2026 Work Trend Index Report.

Enabling the Frontier Firm with Copilot Cowork — now mobile, extensible and enterprise-ready

None of an organization’s system scales without infrastructure that brings people and agents into the same flow of work with connected data and the ability to manage and govern it all. Microsoft 365 Copilot is built for exactly that.

Today, we’re expanding Copilot Cowork with new capabilities for Frontier customers to help organizations move from isolated AI tasks to coordinated, multistep work. Cowork enables people to define outcomes and delegate work across apps, business systems and data, with execution that stays directed and controlled throughout.

This update introduces Copilot Cowork Mobile for iOS and Android, along with a growing plugin ecosystem for Cowork, bringing more of an organization’s tools and data into these experiences. This includes native plugins across Microsoft services like Dynamics 365 and Fabric, and partner integrations available in the coming weeks like LSEG (London Stock Exchange Group), Miro, monday.com, S&P Global Energy and more. Organizations can also build custom plugins to turn their own workflows and expertise into reusable, scalable processes. Additionally, a first wave of federated Copilot connectors in Researcher and Microsoft 365 Copilot Chat is generally available today from partners like HubSpot, LSEG (London Stock Exchange Group), Moody’s, Notion and more.

Together, these updates extend Copilot Cowork from a task-based assistant into an extensible platform that helps orchestrate work across Microsoft and third-party systems. With management and governance through Microsoft Agent 365, organizations can deploy and scale agents across core business functions like sales, service and operations.

For more on these product innovations: Microsoft 365 blog.

AI is no longer an experiment. It is an execution challenge. Employees are already working across all four patterns. The open question for every leadership team is whether they can catch up. Access to AI won’t be the advantage for much longer. How the work is designed around it will be.

Jared Spataro, CMO, AI at Work at Microsoft, shapes how every organization applies AI and agents to reduce costs, create new value and define the future of work. He leads research, strategy and product across Copilot, Copilot Studio, Microsoft 365, Dynamics 365 and Power Platform.

The post How Frontier Firms are rebuilding the operating model for the age of AI appeared first on The Microsoft Cloud Blog.

To maintain velocity and control in 2026, steering committees must answer a fundamental question:

Do we have line-of-sight and control over the AI agents being deployed knowing exactly what they are, what data they touch, and what they are doing?

To help leaders navigate this complexity, we have refreshed our core framework: Grow Your Business with AI You Can Trust. This guide is a practical roadmap for structured decision-making across security and governance, now introducing a critical new pillar for 2026: Observability.

AI committee checkpoint: You cannot govern what you cannot see

As AI spreads across teams and tools, observability becomes the prerequisite for scaling. Without a centralized view, “shadow AI” and unmanaged agents may create significant risks, from security vulnerabilities to sensitive data leakage.

To achieve enterprise readiness, your AI steering committee should be able to answer four foundational questions:

• Inventory: What agents currently exist across our environment?
• Identity: Who is using these agents and for what purpose?
• Access: What systems and specific data sets do they have permission to touch?
• Outcomes: What workloads are they driving and what results are they producing?

Four capabilities for AI platform visibility

In our updated guide, we frame observability through four technical capabilities every enterprise platform should support:

1. Registry: A single source of truth to track every AI asset in the organization.
2. Agent analytics: Real-time data on performance, usage patterns, and costs.
3. Agent map: A visualization of the connections between agents, users, and data.
4. Role-specific oversight: Tailored dashboards that give IT, security, and business leaders the specific metrics they need.

The strategic impact: Accenture

Accenture saw innovation stall at the pilot stage as fragmented tools slowed their path to production. By implementing a centralized platform with built-in observability, they unified monitoring across development and deployment.

Accenture has already deployed more than 75 use cases across industries, with 16 in production, reducing AI app build time by 50%.

Executive checklist: Scaling with control

Your AI steering committee can use the refreshed guide as a checklist to support a secure foundation for AI scaling:

• Define trust: Establish clear responsible AI principles for your brand.
• Secure by design: Shift to a security-first posture across all AI operations.
• Govern the loop: Use the “Map, Measure, Manage” framework to mitigate risks.
• Achieve sustainability: Build systems with socio-economic and environmental impact in mind.
• Address digital sovereignty requirements: Understand common sovereignty scenarios and core principles to help your organization address them.
• Ensure visibility: Confirm your platform supports the 4 capabilities for agent observability.

The post Your AI steering committee’s 2026 checklist: Observability appeared first on The Microsoft Cloud Blog.

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.

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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.

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1. Preparing for the integration of AI and agents.
2. Strengthening training so that everyone has the necessary skills. 
3. Fostering a culture that prioritizes cybersecurity. 

Preparing for the integration of AI and intelligent agents

Preparing for AI and agent integration calls for careful strategy, thoughtful business planning, and organization-wide adoption under solid governance, security, and management. Microsoft’s AI adoption model offers a step-by-step guide for businesses embarking on this journey and the guide offers actionable insights and solutions to manage AI risks.

Strengthening training so that everyone has the necessary skills

Technology alone isn’t enough. People are your strongest defense—and the foundation of trust. That’s why skilling emerged as a central theme throughout these past months and will continue beyond. Frontier Firms—those structured around on-demand intelligence and powered by “hybrid” teams of humans plus agents—lead by fostering a culture of continuous learning. Our blog “Building human-centric security skills for AI” offers insights and guidance you can apply in your organization.  

• Lean into your unique human strengths: Your team’s judgment, creativity, and experience are irreplaceable. Take time to invest in upskilling and reskilling them, so they can confidently guide and manage AI tools responsibly and securely. Explore Microsoft Learn for Organizations for resources to support your learning journey.
• Stay curious and agile through continuous learning: Building security resilience is an ongoing process. Regularly refresh your AI and security training, offer time and resources for employees to explore new skills, and create a supportive, engaging environment that motivates continuous growth. Find in AI Skills Navigator, our agentic learning space, AI and security training tailored to different roles.  

Investing in skilling doesn’t just reduce risk—it accelerates innovation by giving teams the confidence to explore new AI capabilities securely. 

Skilling is an ongoing practice that needs to constantly evolve alongside the business and technology landscape. Staying ahead requires an enterprise-wide strategy that aligns ever-changing business priorities with always-on skill-building. 

—Jeana Jorgensen, Corporate Vice President, Microsoft Learning

Fostering a culture that prioritizes security

As AI impacts everyone’s role, make security awareness and responsible AI practices shared priorities. Encourage your team to weave security thinking into their daily routines—creating a safer environment for all. As Vasu Jakkal, Corporate Vice President of Microsoft Security highlighted in her blog “Cybersecurity Awareness Month: Security starts with you,” it is critical that security become part of your organization’s culture and norms. 

Check out our new e-book, Skilling for Secure AI: How Frontier Firms Lead the Way for practical steps for leaders to upskill their workforce in identity management, data governance, and responsible AI practices.

From awareness to action

In the agentic AI era, people continue to be our most valuable resource. It’s essential to empower them with AI and equip them with the skills they need to use AI responsibly and securely. Cybersecurity awareness should go beyond designated months or campaigns; true awareness means taking meaningful action.   

Here are three actions you can take today to maximize your AI investments: 

1. Share the Be Cybersmart Kit with your employees. It includes tips for protecting yourself from fraud and deepfakes, guidance on safe AI usage, and key security best practices.
2. Invest in people: Focus on upskilling initiatives that support your AI transformation, cloud modernization, and security-first strategies.
3. Champion a security-first culture: Ensure cybersecurity is integral to every business discussion and woven into your overall strategy. 

Microsoft guide for securing the AI-powered enterprise

Download the guide

The post From awareness to action: Building a security-first culture for the agentic AI era appeared first on The Microsoft Cloud Blog.

Explore Microsoft Cybersecurity Awareness resources

As part of the Microsoft Secure Future Initiative (SFI), we have committed to embed security into every layer of our technology, culture, and governance—placing security above all else. Since its launch in November 2023, SFI has mobilized the equivalent of more than 34,000 engineers to proactively reduce risk and strengthen security across Microsoft and the products and services we offer our customers. A great example of this is mitigating advanced multifactor authentication attacks, where phishing-resistant multifactor authentication now protects 100% of production system accounts and 92% of employee productivity accounts. In addition, we continue to reduce the risk of compromise during new employee setup by enforcing video-based verification, now at 99%.¹

Enabling your security-first approach

This year, we have also developed new resources and tools to support security professionals in keeping their organizations secure, particularly as we enter this next era of AI. Building upon our learnings with SFI, we have created SFI patterns and practices, which is a new library of actionable guidance designed to help organizations implement security at scale.

In addition to best practices for security professionals, we continue to add articles to our Be Cybersmart Kit, which is a great starting point for security professionals that need to educate their organizations on how to be safe. The Be Cybersmart Kit contains articles on AI safety, device security, domain impersonation, fraud, secure sign-in, and phishing. The kit is just one of the many resources available on the Microsoft Cybersecurity Awareness site. 

Be Cybersmart

Help educate everyone in your organization with cybersecurity awareness resources and training curated by the security experts at Microsoft.

Get the Be Cybersmart Kit.

Those seeking more in-depth resources can access expert-level learning paths, certifications, and technical documentation to continue their cybersecurity education. And for students pursuing the field of cybersecurity, the Microsoft Cybersecurity Scholarship Program and educational opportunities like Microsoft Elevate are here to help. The goal of all these programs is to help foster a culture that puts security and continuous learning first for students and professionals alike.

Security-first in action: Franciscan Alliance

A great example of a security-first culture, especially around education and awareness training, is Franciscan Alliance, a non-profit Catholic health care organization based in Indiana. Franciscan Alliance employs a proactive and interactive strategy for cybersecurity awareness and employee education.

“We believe cybersecurity education should be continuous, engaging, and empowering—because informed employees are our strongest defense.”

—Jay Bhat, Chief Information Security Officer (CISO), Franciscan Alliance

The organization conducts monthly phishing simulations and quarterly assessments to expose staff to realistic scenarios consistently. Employees who do not pass the quarterly assessments are provided with additional training rather than being penalized, which supports a culture centered on learning and development. Training programs incorporate gamification elements to enhance accessibility and retention. Additionally, employees receive a monthly newsletter covering relevant security topics that support safe practices both professionally and personally.

During Cybersecurity Awareness Month, weekly editions are distributed, along with timely updates on emerging threats, including breaches and attacks. Franciscan Alliance also organizes threat briefings in partnership with external partners and utilizes resources such as Microsoft’s Cybersecurity Awareness materials to inform its training initiatives.

Developing security competencies in the age of AI

As organizations rapidly embrace AI, making security the first priority is not just a best practice—it’s a necessity. AI systems are powerful tools that can transform business productivity, but without robust governance and security measures, they can also introduce significant risks. To address these challenges and empower security-first leadership, we invite C-level executives to register for Microsoft’s upcoming webinar “Trust in AI: Accelerate Business Growth with Confidence,” which will feature critical discussions on how to build trust in AI for your organization.

Get started here:

• Explore the Cybersecurity Awareness Website.
• Download the Be Cybersmart Kit and share it with your teams.
• Explore SFI patterns and practices for actionable security guidance
• Learn ways to keep your personal devices and data safer online with Microsoft 365.
• Sign up for the AI Skills Navigator program that provides AI learning path trainings.
• College students can apply for the Microsoft Cybersecurity Scholarship Program.

Additionally, Microsoft’s Chief Product Officer of Responsible AI Sarah Bird will moderate the panel, “Cyber and AI, Strategic Risk and Competitive Advantage,” at the NASDAQ Summit on October 21, 2025, at the New York Stock Exchange, where industry experts will provide guidance on governance and security for AI. In this session, experts will discuss real-world use cases, regulatory developments, and the strategic implications of integrating AI into enterprise environments. Events such as these are incredible opportunities for executives to deepen their understanding and lead with confidence in the age of AI.

Get the Be Cybersmart Kit

Make the most out of Cybersecurity Awareness Month

We hope that these resources provide you with the learning, training, and confidence to set you and your organizations up for success—both this month and beyond. Now is the time to build a culture with a security-first mindset by making security part of your daily habits at work, home, and everywhere else. A security-first mindset means staying informed, proactively protecting digital assets, and encouraging others to do the same. Security is a team sport. By promoting vigilance and shared responsibility, we can create a safer world for all.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

¹April 2025 SFI progress report.

The post Cybersecurity Awareness Month: Security starts with you appeared first on The Microsoft Cloud Blog.

It’s a great question, considering that a year ago building an AI agent meant calling in an experienced IT team. Today, teams in finance, human resources, and communications are building their own using low-code tools and off-the-shelf AI like Microsoft 365 Copilot. What once took months and weeks now takes hours and minutes, and often fits right into the tools they already use. IDC predicts over a billion AI agents will be in use by 2028 as AI shifts from answering questions to taking action at scale.¹

Does that mean you should begin with agents? Not necessarily. With so many tools and promises in the market, deciding where to start can be overwhelming. That’s why we created The Business Guide to AI Solutions—to help you cut through the noise and focus on what matters: solving real business problems with the right kind of AI.

The Business Guide to AI Solutions

Choose and apply assistants, agents, and custom tools as part of a secure, scalable AI strategy

Get the guide

Match the solution to your business goals

AI isn’t one-size-fits-all. The best results come from aligning the right AI solution with the specific problem you’re trying to solve. Whether your goal is to boost productivity, streamline operations, personalize customer experiences, or build something entirely new, there’s a path forward. Here’s how to think about your options:

Need to boost team productivity and reduce time spent on repetitive tasks? Start fast with assistants

Our recent 2025 Work Trend Index Annual Report contains a lot of insight into how AI is reshaping work. It also put a spotlight on something many employees struggle with that can stall a company’s progress: the infinite workday. The pace of work keeps accelerating—and for many, that means the day never really ends. People are starting earlier, working later, and staying buried in emails, Microsoft Teams chats, and meeting requests well into evenings and weekends.

Clearly, the pace of business is relentless. Our approach can’t be. A great place to start is AI assistants. And if your priority is to help your team be more productive, off-the-shelf solutions can deliver quick wins. Microsoft 365 Copilot is built into the apps your teams already use. Designed for fast deployment and immediate value across different roles, Copilot can help people work faster by summarizing content, generating drafts, and automating routine work in all functions—including sales, marketing, finance, and human resources.

For example, British Columbia Investment Management Corporation (BCI) increased productivity by 10% to 20% for 84% of Copilot users and increased their job satisfaction by 68%. The business saved more than 2,300 person-hours with automation, reduced the time spent on writing internal audit reports by 30% and saved one month of processing time to analyze 8,000 survey comments. And XP Inc. uses Microsoft 365 Copilot to automate tasks, boosting productivity by saving over 9,000 hours—a 30% increase in audit team efficiency.

Struggling with complex, manual processes that slow down operations? Automate with agents

When you’re ready to streamline more complex, multistep processes, agents can help. These autonomous tools go beyond assistants by taking action on your behalf—coordinating tasks across systems, automating workflows, and supporting business operations at scale.

Agents are quickly moving from experimental to essential. We recently introduced advancements in memory, reasoning, and access control that make agents more effective across business environments. You can see this in action in the latest Microsoft 365 Copilot innovations, including multi-agent orchestration, agent tuning, and deeper integration with everyday apps.

With Microsoft Azure AI Foundry, developers can access a full stack agent factory with capabilities to automate business processes across the enterprise. For example, Fujitsu boosted sales proposal productivity by 67%, enabling their teams to focus more time on customer engagement.

We’re also investing in open standards to help agents operate securely across systems so they can scale with your business, not just your tech stack. Read the broader vision for what’s next to learn how AI agents are shaping a more open, connected, and productive future.

Whether built with low-code or pro-code tools, agents can have a big impact across teams. Carvana built an AI agent named Sebastian to guide customers through the car buying and selling journey. To continuously improve Sebastian’s performance, they developed Conversation Analysis Review Engine (CARE), an AI-powered platform that analyzes 100% of customer interactions. Together, Sebastian and CARE have helped Carvana reduce inbound calls per sale by over 45% in two years, reflecting a smoother, more efficient customer experience.

Want to tailor AI to your business without starting from scratch? Extend prebuilt solutions

Once you’ve started using Microsoft 365 Copilot, built-in extensibility gives you a way to go further. With Microsoft Copilot Studio, you can connect AI to your own data, fine-tune prompts, and integrate functionality into your existing systems. This allows you to adapt AI to your workflows—without the time and complexity of building something entirely new.

A case in point is Pets at Home, the United Kingdom’s leading pet care business, which used Microsoft Copilot Studio to extend Copilot’s capabilities for its profit protection team. By building a tailored agent that compiles cases for human review, the company streamlined internal workflows and expects to drive seven-figure annual savings, all without starting from scratch.

Looking to create a competitive edge with something truly unique? Differentiate with custom AI

When your needs are highly specific, customization enables you to design unique solutions that reflect your organization’s DNA. With Azure AI Foundry you can build your own agents, train models with your data, and create experiences specifically made for your business.

For example ABB Group, a global leader in electrification and automation, built a custom AI solution called Genix Copilot using Microsoft Azure OpenAI service to tackle complex industrial challenges like asset performance, energy optimization, and emissions monitoring. The result? Up to 35% savings in operations and maintenance, 20% improvement in energy efficiency, and an 80% reduction in service calls, all through a differentiated, AI-powered experience tailored to their customers’ needs.

You can also build AI solutions tailored to your industry using Microsoft’s industry-specific models and tools in Azure AI Foundry. Whether you’re in healthcare, retail, manufacturing, financial services, or education, our Microsoft Industry Clouds provide prebuilt data models, templates, and AI services to help you move faster and deliver value sooner—without compromising on security or compliance.

Build on a foundation of trust

As AI becomes more powerful, so do the risks. Business leaders are asking the right questions: How do we protect sensitive data? How do we ensure compliance? How do we build AI systems that are fair, transparent, and accountable?

At Microsoft, responsible AI isn’t an afterthought—it’s built into every layer of our platform. Our approach is grounded in clear principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.

We also provide the tools and governance frameworks to help organizations:

• Protect sensitive data in every interaction.
• Detect and respond to emerging threats in real time.
• Enforce access control and compliance policies at every level.
• Build user trust through transparency and oversight.

When you invest in AI, you’re not just investing in innovation—you’re investing in long-term resilience. That means choosing a partner who puts trust at the center of every solution.

2025 Responsible AI Transparency Report

Explore progress on our commitments to building responsible AI

Get the report

Make your next move with confidence

Whether you’re just getting started or ready to scale, Microsoft offers AI business solutions that meet you where you are—and grow with you.

• Download The Business Guide to AI Solutions to explore your options and design an AI strategy that fits your organization.
• Visit the Copilot Studio agents hub to see how businesses are using agents to transform operations.

The pace of AI innovation isn’t slowing anytime soon. But with the right strategy, the right tools, and the right partner, you can move forward with clarity and confidence.

¹ IDC Info Snapshot, sponsored by Microsoft, 1.3 Billion AI Agents by 2028, Enterprise Grade and in Production, US53361825, May 2025.

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