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Today we published our latest Global AI Diffusion Report. The global adoption of artificial intelligence continued to rise in the first quarter of 2026. During the quarter, AI usage increased by 1.5 percentage points from 16.3% to 17.8% of the world’s working age population. Intensity of use among economies with the highest rates of AI diffusion also increased, with 26 economies now exceeding 30% of the working age population using AI.

At the top of Microsoft’s National AI Leaderboard, the UAE continued to lead global AI diffusion at 70.1%. The United States finally started to move up the national rankings, albeit only from 24th to 21st based on a 31.3% usage rate by the working age population.

Notable developments in the quarter included accelerating AI adoption in Asia driven in part by improving AI capabilities in Asian languages. South Korea, Thailand, and Japan saw the greatest movement. More broadly, the quarter brought continued widening of the AI gap between the Global North and South, with usage now at 27.5% in the North and 15.4% in the South. These trends are discussed below, including a deeper dive on the positive impact of enhanced multilingual AI capabilities in Japan.

To track all these trends, we continue to measure AI diffusion as the share of people worldwide between ages 15 and 64 who have used a generative AI product during the reported period. This measure is derived from aggregated and anonymized Microsoft telemetry and adjusted to reflect differences in OS and device-market share, internet penetration, and country population. Additional details on the methodology are available in our AI Diffusion technical paper.^[1]

No single metric is perfect, and this one is no exception. Through the Microsoft AI Economy Institute, we continue to refine how we measure AI diffusion globally, including how adoption varies across countries in ways that best advance priorities such as scientific discovery and productivity gains. For this report, we rely on the strongest cross-country measure available today, and we expect to complement it over time with additional indicators as they emerge and mature.

Sectorally, the quarter saw strengthened AI coding capabilities leading to a dramatic increase in production of software code. This was reflected in production by Anthropic’s Claude Code, the OpenAI’s Codex, and Microsoft’s GitHub Copilot. Git pushes – through which software developers put coding changes online – increased 78% year over year globally. Interestingly, the quarter brought added evidence that, at least for now, AI coding capabilities may be increasing demand for the employment of software developers.

As discussed in more detail in the report, when developer productivity increases, the cost of building software declines. If demand for software is elastic, organizations can respond by building more software across a wider range of use cases. It is still too early to know the full labor-market impact of AI-assisted coding, but the available data shows that in 2025, total U.S. software developer employment reached approximately 2.2 million, rising 8.5% year over year and marking a record high for the profession. Early data for the first quarter of 2026 shows that software developer employment in March 2026 was about 4% higher than in March 2025.

Download the latest Global AI Diffusion report. and explore the data here.

[1] A. Misra, J. Wang, S. McCullers, K. White, and J., L. Ferres, “Measuring AI Diffusion: A Population Normalized Metric for Tracking Global AI Usage,” Nov. 04, 2025, arXiv: arXiv:2511.02781. doi: 10.48550/arXiv.2511.02781.

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2026 Gartner® Magic Quadrant™ for Cyber Threat Intelligence: Key Takeaways for Security Leaders

Threat Intelligence Blog | Flashpoint

By: Flashpoint

6 May 2026 at 17:14

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2026 Gartner® Magic Quadrant for Cyber Threat Intelligence: Key Takeaways for Security Leaders

Market Dynamics and Growth of the Threat Intelligence Market

The threat intelligence market has expanded in both scope and strategic importance as organizations contend with a broader and more complex threat environment. What was once a supporting function within security operations is now expected to inform decisions across vulnerability management, fraud prevention, and enterprise risk. This shift has raised the bar for how intelligence is collected, analyzed, and applied.

Gartner describes this evolution as a move toward unified cyber risk intelligence (UCRI) — an approach that brings together diverse internal and external data sources with advanced analytical capabilities to improve decision-making. As noted in The Evolution of Threat Intelligence Is Unified Cyber Risk Intelligence, “the future of threat intelligence is unified cyber risk intelligence (UCRI)… defined by the convergence of multisignal collection and advanced analytical capabilities.” In our opinion, this model reflects the reality that no single source provides sufficient visibility, and that intelligence must be corroborated across environments to be actionable.

At the same time, the scale of available data continues to increase, introducing new challenges around prioritization and context. Gartner notes that organizations “receive vast amounts of threat data, and filtering out false positives, redundant information and irrelevant alerts to extract actionable intelligence remains a significant challenge. This “noise” can overwhelm security teams and lead to important threats being missed.” This is where AI plays a growing role. Techniques such as machine learning and natural language processing are increasingly used to correlate signals, identify patterns, and surface relevant risks faster. As intelligence becomes more integrated across the enterprise, the ability to combine multisource collection with AI-driven analysis is shaping how organizations evaluate platforms and build modern threat intelligence programs.

How Security Teams Are Evaluating Threat Intelligence

From Flashpoint’s experience working with the most discerning security and intelligence teams, the value of a threat intelligence platform is measured in how it performs in practice — how quickly it surfaces relevant activity, how much context it provides, and how easily it supports decision-making across workflows.

We see three areas consistently shape how intelligence is evaluated, supported by a combination of human expertise and AI-driven analysis:

Access to high-signal environments: Intelligence is most useful when it reflects activity at its source. Access to closed forums, encrypted messaging platforms, and illicit marketplaces provides the context needed to understand how threats develop and move.
Context that supports prioritization: Vulnerability and threat data require context to be actionable. Understanding how activity is discussed and operationalized in real environments allows teams to focus on what requires attention.
Integration into operational workflows: Intelligence must fit into the systems and processes teams already rely on. Integration across SIEM, SOAR, and internal workflows allows intelligence to be applied consistently at scale.

These areas are closely tied to how Flashpoint has built its platform and how it supports organizations operating in complex threat environments.

Where Intelligence Comes From Matters

A large part of how intelligence performs in practice comes back to the source of the data itself.

We believe, and our customers continue to validate, that Flashpoint’s approach is centered on primary-source collection. That means accessing environments where threat activity is actively discussed, coordinated, and developed, including closed forums, encrypted messaging platforms, and illicit marketplaces. These environments require sustained access and ongoing validation, but they provide a level of visibility that is difficult to achieve through surface-level collection alone.

From our experience, working from these sources changes how intelligence is used. Activity can be observed earlier and understood with more context, with discussions, relationships, and intent preserved.

In practice, this allows teams to:

Identify emerging activity before it becomes widely visible
Maintain context across conversations, actors, and environments
Reduce time spent investigating low-value or unverified signals

Intelligence Has to Fit Into How Teams Actually Operate

Collection alone doesn’t determine whether intelligence is useful. We believe it also has to be delivered in a way that aligns with how teams work.

In our experience, most security teams already have established workflows tied to SIEMs, SOAR platforms, and internal processes. Intelligence that integrates into those workflows can be applied consistently across investigation and response.

In practice, we see this support:

Delivery of intelligence directly into existing systems
Consistent application across automated and analyst-driven workflows
Reduced friction between intelligence, investigation, and response

Over time, this consistency allows teams to build repeatable processes around intelligence rather than treating it as a separate function.

Context Drives Prioritization

The same dynamics apply to vulnerability intelligence.

From our experience, understanding which vulnerabilities exist is only one part of the problem. Determining which ones require attention in a given environment depends on context — how those vulnerabilities are being discussed, shared, or used in active threat activity.

We have seen first-hand that when vulnerability data is connected to real-world activity, teams can:

Prioritize remediation based on active threat relevance
Align vulnerability management with observed adversary behavior
Reduce reliance on static scoring as the sole decision driver

Applying This in Practice

For organizations evaluating providers, challenge intelligence sources, challenge collection agility, challenge exploit prioritization and above all ask yourself is this a partner with a long-term track record of navigating the world’s most complex threat environments?

To see how Flashpoint, the world’s largest private provider of threat intelligence can help you make better decisions, faster and with confidence, schedule a demo.

Gartner Disclaimer

Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Flashpoint.

Gartner, Magic Quadrant for Cyber Threat Intelligence Technologies, Jonathan Nunez, Carlos De Sola Caraballo, Jaime Anderson, May 4, 2026.

Gartner, The Evolution of Threat Intelligence Is Unified Cyber Risk Intelligence, By Jonathan Nunez, 15 September 2025.

Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.

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Advancing AI evaluation with the Center for AI Standards (US) and Innovation and the AI Security Institute (UK)

Microsoft On the Issues

By: Natasha Crampton

5 May 2026 at 17:02

Today, Microsoft is announcing new agreements with the Center for AI Standards and Innovation (CAISI) in the US and the AI Security Institute (AISI) in the UK to advance the science of AI testing and evaluation, including through collaborative work to test Microsoft’s frontier models, assess safeguards, and help mitigate national security and large-scale public safety risks. These agreements matter because ongoing, rigorous testing is essential to building trust and confidence in advanced AI systems. Well-constructed tests help us understand whether our systems are working as intended and delivering the benefits they are designed to provide. Testing also helps us stay ahead of risks, such as AI-driven cyberattacks and other criminal misuses of AI systems, that can emerge once advanced AI systems are deployed in the world.

While Microsoft regularly undertakes many types of AI testing on its own, testing for national security and large-scale public safety risks necessarily must be a collaborative endeavor with governments. This type of testing depends on deep technical, scientific, and national security expertise that is uniquely held by institutions like CAISI in the US and AISI in the UK and the government agencies they work with. By combining that government expertise with Microsoft’s experience building and deploying AI systems at global scale, together we are better positioned to anticipate and manage national security and public safety risks in ways that build public trust and confidence in advanced AI systems.

Improving AI evaluation science through cooperative research and operational experience

Advancing the science of AI evaluation requires more than isolated research or one-off testing. It depends on sustained collaboration between industry, government, and research institutions. Through our new and expanded partnerships with the US and UK governments—alongside national security–focused evaluations of model capabilities—Microsoft is bringing technical expertise and operational experience to strengthen AI evaluation methods and practical testing foundations.

In the US, with CAISI, Microsoft and NIST will collaborate on improving methodologies for adversarial assessments—testing AI systems in ways that probe unexpected behaviors, misuse pathways, and failure modes, much like stress-testing whether airbags, seatbelts, and braking systems work effectively and reliably in safety-critical driving scenarios. This work involves co-developing more systematic and reproducible approaches to evaluation, including shared frameworks, datasets, and workflows for assessing safety, security, and robustness risks in advanced AI systems. It also builds on our AI Red Team’s novel research and tools to detect compromised models at scale.

In the UK, with AISI, Microsoft will collaborate on research related to frontier safety and security, including methods for evaluating high-risk capabilities and the effectiveness of the safeguards used to address them. The partnership will also include societal resilience research examining how conversational AI systems interact with users in sensitive contexts.

These collaborations are designed to improve measurement science, evaluation methodologies, practical testing workflows, and real-world mitigation impact. They reflect a shared commitment to rigorous, practical approaches that can make safeguards stronger and evaluations more reliable.

Looking ahead

No organization can address these challenges alone. Our partnerships with CAISI and AISI are a key part of a wider effort to build the institutions, research base, and shared methodologies needed for effective AI testing. This effort also includes:

Pursuing research and evaluation in collaboration with other AI institutes globally while helping advance shared priorities and methodologies for testing through the International Network for AI Measurement, Evaluation and Science.

Helping deliver industry best practices through the Frontier Model Forum (FMF), an initiative dedicated to advancing the science and practice of frontier AI safety and security. Through the FMF, we are working with other leading AI developers to support independent research, develop shared evaluation methodologies, and promote transparency around risk mitigation strategies.

Contributing to MLCommons, a multistakeholder non-profit that develops and operationalizes testing tools such as AILuminate, a family of safety and security benchmarks. In February, we announced efforts underway with institutions in India, Japan, Korea, and Singapore to expand AILuminate to support multilingual, multicultural, and multimodal evaluation, helping to make sure that AI systems work well in the languages and cultural contexts in which people around the world use them.

As AI capabilities advance, so too must the rigor of the testing and safeguards that underpin them. We will apply what we learn from these partnerships directly into how we design, test, and deploy AI systems, ensuring that progress in evaluation science translates into safer, more secure products for our customers. As these partnerships progress, we will share what we learn and look for opportunities to apply insights and best practices to AI testing more broadly.

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Strengthening cyber capacity in Kenya: A new toolkit with lessons for the region

Microsoft On the Issues

By: Kaja Ciglic

4 May 2026 at 16:00

When a major cyber incident hits, the first decisions aren’t technical—they’re human. Who takes the lead? How quickly can information be shared? When should governments step in, and how do you protect public trust while keeping essential services running?

These questions are at the heart of Microsoft’s Advancing Regional Cybersecurity (ARC) initiative, launched in 2025 to help governments strengthen cyber preparedness through practical, public-private collaboration. Today, we’re sharing the first tangible output of that work: the ARC Kenya Exercise Report & Toolkit, developed through a tabletop exercise held in Nairobi in December 2025.

Developed with Kenya’s National Computer and Cybercrime Coordination Committee (NC4) and RiskSight, the toolkit is a practical planning resource designed to help government and cross-sector leaders prepare for cyber crises before they occur. It is grounded in real conversations among leaders from government, regulators, critical infrastructure operators, law enforcement, academia, and the private sector working through what a serious cyber incident would demand of them, together.

Stress‑testing decisions before a crisis hits

The ambition of the “Silicon Savannah” makes Kenya a compelling setting for this work. Its digital economy is expanding rapidly—from mobile‑first financial services to cloud‑enabled public infrastructure—positioning the country as a regional technology leader. But rapid digital growth also brings increased exposure to more sophisticated cyber threats. As systems become more interconnected, a serious cyber incident can quickly disrupt essential services, undermine public trust, and threaten economic stability.

Kenya’s approach recognizes this reality and reflects a critical principle: cybersecurity is not separate from innovation; it is one of the conditions that allows digital transformation to scale safely. The ARC initiative embodies this philosophy and helps decision makers confront the practical realities of coordination, escalation, and response in this complex environment.

This is exactly what the ARC Kenya tabletop exercise was designed to do. The objective was not to test tools but to stress‑test decision making under pressure. Participants were challenged with complex scenarios—including AI‑enabled breaches, ransomware attacks, and infrastructure‑level disruptions. The focus was not on technical fixes but on leadership clarity, cross‑agency coordination, and real‑time decision making in high‑pressure environments.

The outcome was both a roadmap for the unknown and a clear recognition of the need for shared expectations before a crisis begins—particularly around leadership and authority, trusted information sharing channels, and agreed response frameworks. These gaps, identified by participants themselves, now form the backbone of the ARC Kenya Toolkit.

What the ARC Kenya toolkit delivers

The toolkit translates the lessons of the exercise into concrete actions that leaders can take now—before the next incident occurs. It also serves as a practical and specific 12‑month roadmap for strengthening Kenya’s cyber preparedness, moving from lessons identified to durable, institutional capability. Specifically, the toolkit provides recommendations to:

Clarify national leadership during major cyber incidents, enabling government, regulators, law enforcement, and critical infrastructure operators to coordinate more quickly, with fewer gaps and overlaps.

Establish practical, standards‑aligned incident response models for the entire country, including priority playbooks that teams can train on and execute consistently.

Strengthen operational readiness across sectors, with better coordination between security operations centers (SOCs), clearer escalation thresholds, and more reliable incident reporting pathways.

Deepen trusted information sharing and public‑private collaboration through common handling rules, safer “good‑faith” reporting mechanisms, and regular joint exercises to build muscle memory before a crisis.

Taken together, these elements enable leaders not only to respond more effectively to cyber incidents, but to institutionalize preparedness, coordination, and resilience across the national cyber ecosystem. For African countries more broadly, the model also offers a practical pathway to strengthen regional cyber cooperation—by aligning expectations around escalation, information sharing, and public‑private coordination before a cross‑border incident occurs. By translating high‑level principles into practical, repeatable approaches to crisis readiness, the toolkit underscores the value of trusted international partnerships and alignment with global norms for responsible state behavior in cyberspace.

Why Kenya’s approach matters beyond its borders

Many countries across the Global South are grappling with similar challenges: fragmented ownership of critical infrastructure, uneven cyber capacity across sectors, and the need to coordinate rapidly under pressure. While firmly grounded in Kenya’s national context, the lessons from ARC Kenya are therefore intentionally designed to resonate far beyond its borders and to be highly transferable.

Importantly, this work does not end in Kenya. We are already building on these lessons through ARC engagements in other regions, including a new workstream in Mexico, applying the same approach to strengthen preparedness, coordination, and resilience across different national contexts.

By design, the ARC initiative is not simply a record of a single exercise. It is a foundation others can build on—at a national or regional level—offering leaders a practical starting point to turn shared responsibility into sustained capability.

Explore the ARC Kenya Toolkit & Tabletop Exercise

Actionable Recommendations

Roundtable and Tabletop Exercise

Exercise Annex

For more than a decade, the Microsoft Digital Crimes Unit (DCU) has persistently disrupted cybercrime and nation-state threats targeting people, organizations, and critical infrastructure. Explore major disruptions—and the ongoing cases and operations behind them here: Disrupting cyberthreats since 2008 | Microsoft

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From capability to responsibility: Securing our global digital ecosystem with next‑generation AI

Microsoft On the Issues

By: Amy Hogan-Burney

1 May 2026 at 16:00

Cybersecurity is at a turning point. Advanced AI models are dramatically accelerating vulnerability discovery and creating conditions ripe for exploitation, underscored by the announcement of Claude Mythos Preview. This marks a shift, and whether this technology will favor defenders or attackers will depend on the choices we make now.

With the right safeguards, these capabilities can help trusted defenders identify and fix vulnerabilities across critical systems in hospitals, power grids, water, and telecommunications. Released irresponsibly or not properly secured, however, those same capabilities could be abused by malicious actors, threatening the foundations of our digital ecosystem.

Much of the discussion has rightly focused on risks. As advanced AI models speed up the discovery of vulnerabilities, the way we fix them must speed up too. That means stronger pre-deployment risk assessments and close collaboration between governments, frontier AI developers, software providers, and the broader ecosystem to ensure these tools reduce, rather than increase, cyber risk. This is particularly important as AI systems themselves have become high‑value targets, requiring stronger protection of models, systems, data, and underlying infrastructure.

This is ultimately an international challenge. Neither software supply chains nor threat actors stop at borders. Neither can our response. Meeting this moment will require shared approaches across countries, sectors, and systems—rooted in trust, shared standards, resilience, and responsible use.

This moment is also an opportunity. Security has been and remains the top priority at Microsoft. Over the last two years, through our  Secure Future Initiative, we have strengthened our security foundations for this age of AI, in part by using AI to accelerate vulnerability discovery and remediation. We have also invested in fundamental AI for security research, including the development of open-source industry benchmarks that can be used to evaluate whether models are ready for real-world security work. We are accelerating that work through deeper public-private collaboration and in partnership with AI, including Anthropic’s Project Glasswing and OpenAI’s Trusted Access for Cyber program.

Securing our digital ecosystem with next‑generation AI is within reach but is not automatic.

Building secure foundations for the era of frontier AI

Ensuring advanced AI technologies are used to strengthen cybersecurity requires deliberate and urgent action. We are sharing the following recommendations as practical steps governments, industry, and the broader ecosystem can take to ensure these tools, often referred to as “frontier AI”, reinforce the security foundations on which digital societies depend. And we hope to continue to partner with model providers, industry and government so we can work together to improve security outcomes for all.

1. Reinforce core cybersecurity practices

Advanced AI can strengthen cybersecurity only when strong, consistent cyber hygiene is already in place. As frontier AI accelerates vulnerability discovery and response, core practices such as rapid patching, access control, and system resilience become more critical, not less.

Security gains in the frontier AI era depend on close coordination between technology providers advancing new capabilities and the organizations responsible for operating, updating, and securing real‑world systems. Without this interdependence, advanced AI cannot deliver durable improvements in security. No organization can solve these cybersecurity problems alone.

That is why sustained investment in what we know works remains essential: secure‑by‑design product lifecycles, Zero Trust architectures, multi‑factor authentication, least‑privileged access, and ongoing security training. Broad adoption and harmonization of established cybersecurity frameworks to ensure consistent resilience across AI‑enabled systems. Trusted cloud environments that enable these practices at scale, supporting secure data handling, continuous patching, and the secure deployment of AI‑enabled tools for defenders.

2. Release advanced capabilities responsibly

As frontier AI systems gain reasoning, coding, and agentic capabilities, some of the most serious security risks arise before deployment, including realistic misuse involving multi‑step reasoning, tool use, and reconnaissance. Technical safety benchmarks remain important, but they are insufficient without rigorous, real‑world testing.

As a result, governments are increasingly establishing pre‑deployment evaluations that combine technical testing with threat modeling. These assessments are most effective when frontier developers work closely with organizations that track national‑security risks. Investing in secure evaluation environments and modern testing methods can help governments keep pace as capabilities advance.

Responsible release practices, including phased and controlled access, are a critical extension of this approach. Our work with Anthropic in Project Glasswing offers one practical model, enabling trusted defenders to evaluate advanced capabilities in constrained settings prior to broader release. Similarly, OpenAI and Microsoft work closely through Trusted Access for Cyber program, and we already support OpenAI’s use of scoped, early deployments for safety and security testing.

Responsibility does not end at release. Organizations that deploy frontier models are often best positioned to detect emerging misuse and should monitor, mitigate, and share threat information. Microsoft is working with peers through the Frontier Model Forum to advance best practices for evaluating and managing cyber risk and enable information sharing. Governments should encourage continued industry collaboration to restrict access for identified threat actors and counter adversarial or malicious use of advanced AI.

3. Modernize vulnerability management

AI is changing both the speed of vulnerability discovery and what constitutes meaningful security risk. Faster discovery only improves security if triage, validation, and remediation can keep up.

As AI accelerates discovery, vulnerability management must shift from tracking raw volume to reducing real‑world risk. That means prioritizing vulnerabilities that are genuinely exploitable, assigning clear responsibility for triage and remediation, and using phased, risk‑based disclosure when private coordination improves safety. Above all, systems must be designed around validation and realistic remediation capacity, not the assumption that more findings automatically lead to better security.

Developers of frontier AI models should embed vulnerability coordination and disclosure directly into responsible‑release frameworks. And work with governments and industry to ensure findings are routed to the right owners, acted on early, and supported by clear coordination pathways.

4. Fix faster: Strengthen and accelerate response and remediation

As AI accelerates vulnerability discovery, remediation must keep pace. Initiatives such as DARPA’s AI Cyber Challenge show how AI can help both find and fix flaws in open‑source software. Hardening defenses requires investment not just in detection tools but in the people, processes, and infrastructure responsible for fixing vulnerabilities, especially in critical sectors.

Much of the software underpinning critical infrastructure relies on open‑source components maintained by small teams or volunteers with limited security capacity. A surge in AI‑enabled discovery risks overwhelming existing triage and disclosure processes. Efforts such as the GitHub Secure Open Source Fund, alongside investments by Microsoft and others through the Linux Foundation, Alpha‑Omega, and OpenSSF, are helping maintainers adapt in ways that are practical and aligned with existing workflows.

Governments should treat remediation capacity as a core resilience priority, including sustained investment in and support for maintainers, surge capacity during large discovery events, and modernized disclosure pathways—recognizing that effective remediation still largely depends on human judgment, coordination, and time.

5. Advance AI security internationally

AI security is essential to deploy AI at scale. Because AI systems, supply chains, and the risks they introduce operate across borders, national approaches alone will not be sufficient.

Governments and industry should work together to build interoperable international foundations for AI security, including risk evaluation, coordinated vulnerability disclosure, and information sharing. Priorities should include strengthening the defensive use of AI, preventing misuse through shared norms and safeguards, and securing AI systems- and the AI technology stack.

Global participation is critical. Countries and organizations with limited cybersecurity resources or legacy infrastructure are often the most exposed. International cooperation should prioritize capacity‑building, ensuring that the security benefits of AI are realized broadly and equitably.

AI security is not just a safeguard; it is an enabler for innovation and growth. By acting collectively and moving quickly, governments and industry can strengthen global digital resilience and unlock the trusted adoption of AI across economies, critical infrastructure, and public services.

Meeting the moment: Use frontier AI capabilities to build trust and confidence

Meeting this moment is ultimately about trust: not in any single technology or provider, but in our collective ability to introduce advanced AI responsibly.

Used deliberately and built on strong security foundations, these capabilities can strengthen cybersecurity and reinforce confidence in the systems society depends on. The choice is not between innovation and security but whether we enable them to reinforce one another.

That outcome is within reach. With governments, industry, and infrastructure operators aligned, advanced AI can be deployed in ways that match real‑world defensive capacity and support trusted, lawful action. Done right and working together, frontier AI can help protect the digital infrastructure that underpins modern life and build lasting confidence in its resilience.

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One year on: Progress on our European digital commitments

Microsoft On the Issues

By: Samer Abu-Ltaif, President - Microsoft Europe, Middle East & Africa (EMEA) and Jeff Bullwinkel - VP & Deputy General Counsel, Corporate External & Legal Affairs, Microsoft EMEA

30 April 2026 at 08:00

Europe is moving fast to capture the benefits of artificial intelligence, recognizing its potential to raise productivity, strengthen competitiveness, and help modernize public services. At the same time, organizations across Europe are focused on digital sovereignty and resilience: retaining control over their data and critical operations in a period of geopolitical volatility.

These priorities go together. That is why one year ago, we announced a set of European digital commitments to respond to these expectations. They focused on five areas:

Help build a broad AI and cloud ecosystem across Europe
Uphold Europe’s digital resilience even when there is geopolitical volatility
Continue to protect the privacy of European data
Help protect and defend Europe’s cybersecurity
Help strengthen Europe’s economic competitiveness, including for open source

Together, they reflect a simple principle: Europe should be able to use global technology at scale, under European rules, with confidence that it will remain available, secure, and under customer control.

One year on, we take stock of how we’ve put those commitments into practice.

1. Building a broad AI and cloud ecosystem across Europe

A year ago, we detailed plans to increase our European datacenter capacity by 40%, expand cloud operations across 16 European countries, and reach more than 200 datacenters on the continent by 2027. Since then, we have announced new multi-billion euro investments in Portugal, Norway, and the UK, adding to the increased investments announced in Denmark, Germany, France, Italy, Sweden, Spain, Poland, and Switzerland. We also launched new cloud regions in Austria, Denmark, and Belgium. Together, this growing capacity is helping European organizations access cloud and AI capabilities closer to home while supporting sustainable growth through investments such as matching 100% of our annual global electricity consumption with renewable energy.

We emphasize now, as we did when first announcing our digital commitments, that European laws apply to our business practices in Europe, just as local laws govern local practices elsewhere in the world. We remain committed not only to building digital infrastructure for Europe, but also to respecting the role that laws across Europe play in regulating our products and services.

2. Upholding Europe’s digital resilience in a volatile geopolitical environment

For many customers, digital sovereignty is now about more than where data is stored. Institutions and businesses across Europe also want to know whether they can rely on critical digital services when geopolitical pressures rise, and whether they can adopt advanced AI capabilities without losing control.

We have made our Digital Resilience Commitment legally binding in contracts with European national governments and the European Commission, including a commitment to promptly and vigorously contest in court any order by any government to suspend or cease cloud operations in Europe.

We also committed to continuity measures, including expanded partnerships with European cloud partners that can support our customers’ operational continuity in extreme scenarios. Reinforcing this approach, we launched a European resiliency partnership with Delos Cloud to safeguard business continuity in Europe in times of crisis. This work also supports closer cooperation among Europe’s sovereign cloud providers, including crisis response coordination and continuity options designed to help customers maintain operations even in the event of geopolitical disruptions.

We also expanded our strategic partnership with Capgemini to offer fully integrated, managed sovereign cloud services. In addition, we are deepening our collaboration with Accenture to help organizations design and implement sovereign cloud and AI solutions, supporting customers in highly regulated sectors as they balance innovation with control, compliance, and resilience.

To further strengthen governance and operational oversight in Europe, Microsoft’s European activities are now overseen by a board of directors composed exclusively of European nationals, reinforcing regional accountability and our commitments to cybersecurity, resilience, and compliance under European law.

3. Protecting the privacy of European data

Privacy, transparency, and customer control remain central to Europe’s expectations for cloud and AI. That’s why over the past year we have built a portfolio of sovereign cloud options, spanning public cloud, private cloud, and national partner solutions, so that customers can choose the level of control and oversight that best fits their legal, operational, and risk requirements. This portfolio spans infrastructure, productivity, and AI workloads across cloud, hybrid, or fully local deployments.

We have continued to implement our Defending Your Data Initiative, including our commitment to challenge government data requests for EU public‑sector or commercial customers where we have a lawful basis to do so.

We also completed the EU Data Boundary, enabling European customer data to be stored and processed within the EU. We have since expanded these commitments to cover AI-powered productivity services, so that the processing of customer data for tools like Copilot can also take place within Europe.

In order to further reinforce transparency and oversight, we announced Data Guardian, which ensures that all remote access by Microsoft engineers to systems that store and process customer data in Europe is approved and monitored by personnel residing in Europe and logged in a tamper-evident ledger.

Over the past year, we have strengthened our sovereign solutions through new contractual assurances, closer partnerships with European providers, and expanded customer support.

The Microsoft Sovereign Cloud has been enhanced to help customers meet Europe’s growing expectations for control, resilience, and compliance without slowing down innovation. Recent updates add new governance and operational controls, expand productivity options for regulated environments, and strengthen encryption, while making it easier to use advanced AI capabilities that are fully customer-controlled. This includes solutions where AI models can run on customer-owned infrastructure with limited connectivity or even in fully disconnected environments. Earlier this week, we added new capabilities to our private cloud offering allowing organizations to run much larger workloads locally.

Sovereign Landing Zone provides a cloud architecture that embeds governance, compliance, and sovereign controls, helping European organizations deploy cloud environments that align with European regulatory requirements, with less complexity.

External validation of this approach continues to grow. Microsoft was named a leader in Forrester’s latest assessment of sovereign cloud platforms, recognizing the strength of our public cloud, private cloud, and partner-operated approach.

To help customers put this into practice, we opened our first three European Sovereignty and Resilience Studios in Munich, Brussels, and Amsterdam, where governments and enterprises work side by side with Microsoft’s engineers, policy experts, and security teams to capture the full promise of cloud and AI. Additional studios are planned to open in Microsoft’s nine other Innovation Hubs across Europe.

4. Helping protect and defend Europe’s cybersecurity

Cyber threats don’t stop at national borders, and Europe’s security depends on strong public‑private cooperation. During the last year, we have rolled out our European Security Program (ESP), an offering available at no cost to governments across the UK, EU, EFTA, and EU accession countries. It expands threat intelligence sharing and prioritizes new partnerships and investments to help protect critical infrastructure, disrupt cybercrime, and strengthen Europe’s collective ability to respond to attacks.

This program is live across 27 countries across Europe, providing support at no cost within a clear scope through structured briefings, early warnings, and tailored information sharing relevant to each country’s environment.

We have provided cybersecurity support to NATO, Ukraine, and other European governments, including threat intelligence, election protection, and disrupting attacks targeting European governments, companies, and citizens.

Since the start of Russia’s full-scale invasion of Ukraine in 2022, when we helped move critical data and services to secure datacenters across Europe and defend against sustained cyberattacks and eventual kinetic attacks, Microsoft has continued to support the country without interruption, providing more than $600 million in free technology, security, and financial assistance.

We have also expanded collaboration by embedding investigators with Europol’s European Cybercrime Centre (EC3). Together, we are translating technical threat intelligence into coordinated operational action, linking visibility into cybercriminal infrastructure with law enforcement’s ability to investigate, coordinate, and disrupt. This model underpinned recent cybercrime takedowns, including Tycoon 2FA, Lumma Stealer, and RedVDS. And, through our partnership with CyberPeace Institute, more than 300 European nonprofits are receiving cybersecurity support.

All of this work was reinforced in July with the appointment of Freddy Dezeure as Deputy Chief Information Security Officer, a European national based in Europe, who is coordinating Microsoft’s compliance with European cybersecurity regulations. Our European executive cybersecurity presence and oversight are closely aligned with Microsoft’s broader cybersecurity governance, combining European guidelines with globally consistent security practices.

5. Strengthening Europe’s economic competitiveness, including for open source

We continue to support open ecosystems, including open source, to keep our AI and cloud platforms accessible and interoperable, and to give customers deployment options that fit their needs. There are almost 25 million European software developers active on GitHub, making more than 155 million contributions to public projects in the last year alone. Through Microsoft Foundry, customers can choose from more than 11,000 AI models, both open source and commercial, and run them in sovereign public or private clouds from cloud to the edge. This enables customers to deploy the same Microsoft Foundry model catalog within sovereignty‑aligned infrastructure.

But it is also vital that we support AI solutions that are more multilingual and attuned to cultural context. As part of our commitment to advance European commerce and culture, we launched LINGUA in September 2025 to support projects that collect high‑quality speech and text datasets for Europe’s underrepresented languages. Following an open call, we selected 12 projects spanning 16 languages and dialects across 10 countries, bringing together universities, nonprofits, a government language center, and a public broadcaster to create and digitize open datasets, preserve heritage languages, and develop new evaluation resources for multilingual AI.

We have new AI for Culture projects to digitally preserve iconic European sites and artifacts, including a digital replica of Notre Dame with the French Institut du Patrimoine and Iconem, and we are working with leading institutions to digitize historic cinematic model opera sets and enable access to metadata associated with millions of artifacts. We are also working with the Vatican Library on digitization and AI analysis of historic documents. All of this builds on preservation efforts underway since 2019 for landmarks such as St. Peter’s Basilica in Rome, Mont Saint Michel in France, and Ancient Olympia in Greece.

Relatedly, Céline Geissmann was chosen to lead our Microsoft Open Innovation Center in Strasbourg to work at the intersection of AI, languages, culture, open data, and innovation.

Staying accountable as Europe’s digital landscape evolves

These commitments are our North Star for how we engage in Europe, grounded in European law and values, shaped by European priorities, and designed to progress over time.

As Europe’s digital and geopolitical context continues to evolve, we will keep engaging with policymakers, regulators, customers, and partners to test whether what we are delivering matches what Europe needs. Where it does not, we will adapt.

Trust cannot be claimed. It needs to be earned through our actions, day by day. We are committed to earning that trust by listening, acting, and delivering for Europe.

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