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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

8. How do I balance Frontier Transformation with sustainability? 

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

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

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

Next steps to lead in the era of Frontier Transformation

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

Explore Microsoft AI tools and solutions for your Frontier Transformation. 

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

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

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

Integrating cloud functionality

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

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

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

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

Serving the person, not just the consumer

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

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

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

COMPANY INFORMATION

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

The post María Almenara: The First Data-Driven Peruvian Bakery 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.

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

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

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

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

Intelligence that shows up in real work 

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

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

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

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

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

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

Trust: from agent experimentation and sprawl to enterprise control 

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

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

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

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

Introducing the Frontier Suite

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

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

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

The post Introducing the First Frontier Suite built on Intelligence + Trust appeared first on The Microsoft Cloud Blog.

In this Q&A, Michelle introduces M12, considers what kinds of AI-powered solutions will drive the next wave of AI innovation, highlights some of M12’s recent investments, and explains how Microsoft Marketplace can help startups reach enterprise customers.

What is M12, and how does it differ from traditional venture capital firms? 

M12 is Microsoft’s venture fund. We’re an early-stage fund focused on finding innovative AI startups and technologies that can leverage the power of Microsoft. And with that, we’re looking at the big picture—not just the companies that are winning, but those that are driving the systems of the future.

In today’s venture environment, there’s a lot of capital fighting to invest in the top AI founders and startups, so investors need something extra to stand out and win deals.

At M12, we’re backed by the power of Microsoft, which means a few things: instant credibility with potential partners, as well as access to its ecosystem,  expertise and research, and global go-to-market (GTM) motion. But most importantly, the team is built for impact. We help ensure that our startups have a custom plan and a dedicated resource to help make that plan a reality.  

Our team is a unique mix of founders, researchers, and folks who have been in the trenches across product innovation, finance, go to market, and business development. While our skill sets may be diverse, we put our collective expertise toward a common goal: to help promising companies win.  

What kinds of AI-powered solutions or business models do you believe will define the next wave of innovation? 

The last few years we’ve seen a lot of experimentation—thousands of AI fueled products have been launched—some finding spectacular product market fit, reaching more than USD100 million annual recurring revenue (ARR) in less than a year of launch, while others stuck in the pilot stage with low adoption or questionable durability.

We believe we are now entering a new phase of AI that’s less about experimentation and more about putting into production and delivering measurable outcomes. Buyers are holding new technology accountable to real return on investment (ROI) on shorter time horizons—is your product saving the enterprise money, driving measurable efficiencies, or generating new revenue opportunities.

We see the next wave of application technology embedded deeper into enterprise workflows, training on proprietary data, more domain-aware agents that move beyond assistance to coordinating multi-step work across teams, and orchestration tools that go beyond copilots. We believe that early use cases of AI like software coding and customer support will continue to scale, but it’s been interesting to see momentum in fields that traditionally have been slower to adopt new technology such as medicine, law, and accounting.

At M12, we’ve been thinking deeply about the next evolution in models beyond text-based large language models (LLMs), particularly world models, and how data from the physical world brings about new innovations, particularly in science.

We are also focused on the foundational layers that make AI possible at scale— infrastructure, tooling, data systems, and how to make AI factories more efficient, sustainable, and performant. You can see that in our recent investments in nEye.AI and Neurophos, and you’ll continue to see us make bets in these areas.

On the business side, we’re seeing rapid change. New pricing models like outcome-based and consumption-based pricing, faster adoption cycles particularly in small and midsize business (SMB) and individual buyers, and a sharper focus on ROI are reshaping how value is created.

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What are the key criteria you look for when evaluating businesses to invest in?

We look at a combination of factors and because we invest early in a company’s lifecycle, we focus deeply on the strength of the team, their conviction, and their long-term vision. The best teams are shipping quickly, adopting the latest models, listening closely to customers, and adjusting based on real-world feedback. We are finding that velocity is “the” moat for many AI companies. We also look at market size and opportunity and increasingly, a founder’s plan for how to differentiate in a crowded market, and how we can support the business.  

Ultimately, we’re looking for incredible teams that are learning quickly, innovating with customers, and building with durability in mind. 

What are some of your recent investments and what made them stand out?

M12 meets hundreds of startups each year and typically invests in 18 to 20 early-stage companies a year. We aim to balance our portfolio with a mix of companies that have nearer term adoption and traction and those with longer time horizons.

• Inception Labs is pioneering a diffusion large language model (LLM) approach, which has some performance advantages over transformers. Its early—a “foundation model” and frontier investment that we’re excited by.
• Outset is an AI-moderated research platform that is fundamentally reshaping how enterprises operate and understand their customers, which is exactly what we look for in teams and technologies—they already have an impressive list of customers, including Microsoft, Uber, and Hubspot. 
• Neurophos is tackling one of the biggest bottlenecks in AI infrastructure: the inability of GPUs to scale efficiently across cost, power, and footprint. The team has developed a manufacturable optical processing unit that compresses GPU-scale compute into a dramatically smaller, cooler, and more sustainable form, delivering up to 100× performance and energy efficiency compared to today’s leading systems.
• Entire is approaching the next general wave of developer platforms from first principles, architecting a new platform from the ground up for agent-to-human collaboration. We’re excited to invest in Entire and support a team that is inventing a new paradigm of how developers and AI work together.

Where do you see the most promising opportunities for AI to disrupt industries globally, and how is M12 positioning itself to lead in those areas?

The biggest opportunities for AI disruption are in industries where complexity, scale, and constraints intersect—areas like enterprise transformation (this could be system of records being unbundled or completely rethought, hyper-personalized employee agents and applications), next gen cybersecurity, tooling and infrastructure that needs to be rebuilt when agents are writing the majority of software code, and innovations brought on by world models deployment are also top of mind.

M12 is uniquely positioned to support founders tackling these challenges because we invest where Microsoft brings deep expertise—enterprise environments, technology, global scale, and mission-critical systems. Our investors are thesis driven and often will spend months getting to know a space, going deep, which builds credibility with founders before an investment.  

How are you seeing founders adapt their strategies to thrive in an AI-first world, and what advice would you give them?

Founders are shipping and executing faster, focusing on deeper integrations with customers, and building community and brand awareness quickly as part of their go-to-market. Many enterprises today are running multiple proofs of concept across similar AI tools and we believe this next year customers will focus and consolidate. There will be a major shift towards deciding which solutions deliver real ROI and are ready for wide-scale production. 

Founders who succeed will be the ones who build deeply integrated, customized workflows that fit into how customers actually operate. We’re seeing startups pairing product innovation with services, like forward-deployed engineers, to accelerate adoption early on, getting feedback loops started quickly as well with access to unique data to make their products sticky and “must haves.”

We’re also seeing companies rethink how they operate internally. One of our portfolio companies, Allstacks, which was founded more than 5 years ago, radically shifted their go-to market strategy last year to become AI native, where AI tools and agents are integral parts of each operating function. It was critical work and a good example of how forward-thinking companies are reinventing their operations to match their product innovation.

Many AI native companies are operating incredibly leanly, even as they scale, due to the use of AI in all elements and functions of their business. 

How does M12 evaluate which AI startups have the potential to scale and make a lasting impact?

We spend a lot of time distinguishing between the hype cycle and the durability cycle. Markets can move quickly, we’re seeing that more than ever, but lasting companies are built deliberately over many years.

The startups with the greatest potential are those that design with constraints in mind, whether that’s power, capital efficiency, inference economics, or customer trust, and still find ways to deliver meaningful value.

Why is collaboration between corporations and startups essential for accelerating AI transformation globally?

AI transformation and adoption especially in the enterprise doesn’t happen in isolation. Startups bring speed, creativity, and new ideas. Corporations bring scale, trust, and real-world deployment environments.

When those strengths come together, we see not an additive but multiplier effect. Corporations like Microsoft can serve as a bridge between early-stage founders and global enterprise customers, helping startups move faster while deploying AI responsibly and at scale.  

For example, Microsoft Marketplace is a great way for startups to transact with enterprise customers—we have a portfolio development team that is solely focused on opportunities like this, helping our portfolio companies join the marketplace and get ready to sell to enterprises, get through procurement and generally navigate the opportunities to partner with Microsoft and our customers.

That collaboration is what can turn breakthrough technologies into lasting impact, and it’s why partnerships are so critical in this next chapter of AI. 

Ready to learn more? Discover resources and tools to accelerate your AI journey

• Learn more about M12, Microsoft’s venture fund
• Explore cloud solutions, AI apps, and agents on Microsoft Marketplace
• Get the Prompt Guide for Business Leaders to turn AI intent into clear, actionable decisions
• Discover how Microsoft AI brings intelligence into the flow of work

The post FYAI: Why startups will help accelerate global AI transformation appeared first on The Microsoft Cloud Blog.

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

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

Why AI transformation and sustainability belong together

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

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

Five practices for sustainable AI transformation

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

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

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

What the research shows

AI can deliver better results—faster and more sustainably

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

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

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

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

What this looks like in practice

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

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

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

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

Becoming a Frontier organization—responsibly

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

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

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

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

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

What leaders can do next

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

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

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

Strategic Guide: Aligning AI Transformation with Sustainability Goals

Read the guide

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The 2026 Formula 1 regulation changes usher in a new era of racing for the sport, with increased electrification, efficiency and sustainability, representing one of the most significant technical evolutions in modern Formula 1 history. As the Mercedes-AMG PETRONAS F1 Team prepares for this transformation, it is partnering with Microsoft to harness the power of its trusted cloud and enterprise AI technologies across the business, from the factory to the racetrack.

“Our sport is driven by those who lead through innovation,” said Toto Wolff, CEO and Team Principal, Mercedes-AMG PETRONAS F1 Team. “We are delighted to partner with Microsoft, one of the world’s foremost technology leaders, whose name is synonymous with groundbreaking innovation. This partnership also reflects our commitment to staying at the forefront of performance and progress. By putting Microsoft’s technology at the center of how we operate as a team, we will create faster insights, smarter collaboration and new ways of working as we look ahead to the next generation in F1.”

In a sport where races are decided by tenths of a second and every decision is data driven, Formula 1 represents the ultimate stress test for modern enterprise systems: extreme data volumes, real-time decision making, global operations and zero margin for error. United by the belief that technology is a competitive advantage, Microsoft and the Mercedes-AMG PETRONAS F1 Team will look to set a new standard for how enterprise technology drives performance at the highest levels of competition.

“This partnership puts Microsoft’s cloud and enterprise AI technologies at the heart of racing performance, where milliseconds matter and data determines outcomes,” said Judson Althoff, CEO, Microsoft commercial business. “Together with the Mercedes-AMG PETRONAS F1 Team, we are harnessing data and turning it into real-time intelligence that powers faster decisions, smarter strategies and sustained competitive advantage — both on and off the track.”

Racing at the speed of data

Modern Formula 1 cars are defined by precision and pace. Each Mercedes-AMG PETRONAS F1 Team car carries more than 400 sensors, generating over 1.1 million data points per second. From tire degradation and aerodynamic behavior to Energy Recovery System deployment and evolving track conditions, every variable must be interpreted in real time.

Microsoft Azure and its AI capabilities will expand the Team’s existing high-performance computing and data capabilities, both the factory and trackside, with scalable cloud and AI resources supporting simulation workloads, performance analysis, race strategy modeling and cross-team analytics. The flexibility and agility of this platform will help ensure engineers and strategists have real-time insights available at the moments that matter most.

“It is a privilege to welcome Microsoft into the Mercedes-AMG PETRONAS F1 Team partner ecosystem,” said Richard Sanders, Chief Commercial Officer, Mercedes-AMG PETRONAS F1 Team. “Microsoft’s technology already plays a central role in how we operate as a business, and this partnership opens new opportunities to innovate as we look toward the next era of technological development. I look forward to seeing how our teams collaborate to unlock new ways of working across the organization.” 

Fueling human ambition

Microsoft 365 and GitHub already underpin many of the Mercedes-AMG PETRONAS F1 Team’s engineering and operational workflows across its headquarters in Brackley and Brixworth, as well as trackside in the paddock. Building on this foundation, the team will expand its use of Microsoft 365 to unlock new levels of agility, accelerate innovation and enhance operational efficiency across the business.

Microsoft’s GitHub development tools and platforms help engineers innovate faster, optimize performance and push the boundaries of design, modeling and simulation. Going forward, the team’s engineering, simulation and software development groups will deepen their integration of GitHub to modernize and accelerate development workflows enabling greater consistency, speed and efficiency.

Scaling for performance

Working with Microsoft Azure to accelerate AI technology experimentation and scale, the Mercedes-AMG PETRONAS F1 Team used real-time sensor data and Azure cloud tools to pilot intelligent virtual sensors, enabling rapid testing without waiting for new on-premises infrastructure.

With Azure Kubernetes Service (AKS), they were able to easily adjust computing power, scaling up when demand is high and down when it’s not, delivering meaningful technological advancements while meeting strict financial and regulatory requirements.

From road to track

For more than 30 years, Microsoft and Mercedes-Benz have collaborated across the automotive value chain, from AI-powered smart factories and electric vehicle telemetry to onboard vehicle intelligence and cloud-enabled engineering systems. From the factory floor to Formula 1, this new partnership builds on that foundation, bringing the same innovative mindset and digital capabilities into the world’s premier motorsport.                                                  

About the Mercedes-AMG PETRONAS F1 Team 

Mercedes was born to race — and we’ve been doing it since 1901. Today, the Mercedes-AMG PETRONAS F1 Team competes at the pinnacle of motorsport: the FIA Formula One World Championship. 

The pioneering spirit of our company founders lives on in our commitment to innovation and performance. As the world’s original automobile manufacturer, Mercedes-Benz has defined the cutting edge of technology for over a century. Today, our F1 team exists to demonstrate the best of the brand’s performance on the global stage. 

Based in Brackley and Brixworth, UK, over 2,000 committed team members work with a singular mission: to win the world championship. From 2014 to 2021, we secured a record eight consecutive Constructors’ Championships, and we are hungry for more. 

Our journey is not just about performance on the track; we also strive to make a positive impact on the world and inspire future generations. We are proud signatories of the Climate Pledge, and we are leading the way in building a more sustainable and inclusive sport. 

For more information, please visit www.mercedesamgf1.com. 

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Today’s business environment demands more with less. Organizations must deliver better personalization, higher volume, and increasingly complex insights while operating with greater efficiency. The gap between stakeholder expectations and what teams can realistically deliver continues to widen. 

Microsoft’s recent insights on Frontier Transformation address these challenges by embedding AI into the core of operations. Frontier Firms are organizations that treat AI as a foundational capability and are already transforming how they work. 

Frontier Firms don’t simply automate; they adapt. By adding adaptive intelligence to existing systems, they unlock three advantages: 

• Awareness: Systems perceive conditions in real time. 
• Reasoning: They prioritize tasks based on business needs. 
• Interaction: They communicate in natural, intuitive ways. 

Early adopters see small improvements compound quickly. These include faster service, more accurate recommendations, fewer equipment surprises, and clearer insights into peak times and bottlenecks. As agentic AI matures, companies can offer guidance and assistance that feels intuitive. Employees gain more time for high-value work, and leaders gain deeper visibility into operations. 

Frontier Transformation is more than a technology upgrade. It represents a shift in operating model. Organizations that treat AI as a foundation will lead the next wave of business innovation. 

Agentic AI is reshaping customer experience 

This shift is already visible in retail, where agentic robots are transforming customer experience and improving operational performance. Customers expect fast, personalized service, yet retailers often face staffing constraints, training gaps, and unpredictable demand. 

Industry studies show: 

• 75% of consumers are more likely to purchase when recommendations feel relevant. 
• Nearly 40% of in-store complaints relate to wait times. 
• Inventory inaccuracies account for 4–8% of lost sales. 

These challenges reflect a broader pattern across frontline-heavy industries. Customer expectations continue to rise, and employee workloads grow more complex. 

Microsoft’s Work Trend Index reinforces this dynamic. Frontline employees say AI tools that reduce repetitive tasks, surface real-time information, and streamline customer interactions have the biggest impact on satisfaction and performance. As organizations integrate adaptive intelligence into daily workflows, these benefits build on each other and help accelerate Frontier Transformation. 

Recent industry research shows that retail and consumer packaged goods organizations are generating significant business value from generative and agentic AI, with early deployments consistently delivering multi-times ROI and accelerating impact across frontline operations.

Agentic AI creates new possibilities for stores. Instead of relying on rigid automation, it blends environmental awareness, adaptive reasoning, and conversational interaction to help teams respond in real time. 

ADAM: From beverage service to customer care 

Richtech Robotics’ ADAM beverage robot illustrates how quickly agentic systems can enhance the customer experience. Richtech, based in Las Vegas, designs and commercializes autonomous robotic solutions for hospitality, retail, logistics, and manufacturing. Through a close, hands-on collaboration between Richtech’s engineering team and the Microsoft AI Co-Innovation Labs, the two companies jointly developed new adaptive intelligence for ADAM—transforming it into a conversational, context-aware assistant powered by Microsoft Azure AI. These enhancements enabled ADAM to move beyond routine beverage preparation and support richer customer interactions.

Today, ADAM: 

• Adjusts recommendations based on weather, time of day, and promotions. 
• Responds naturally to customer requests like “less sweet,” “extra ice,” or “what’s seasonal?” 
• Notifies staff about ingredient or equipment issues before problems occur. 
• Uses vision models to maintain speed and quality during busy periods. 

Retailers report smoother operations and better customer feedback. ADAM is context aware, conversational, and reliable—qualities customers consistently reward and areas where AI has historically struggled. 

While ADAM is a retail example, the pattern extends far beyond beverage automation. Across logistics, healthcare, hospitality, and manufacturing, Frontier Firms are adding ambient intelligence and agentic workflows to physical operations and seeing meaningful gains as a result. 

Unlocking retail transformation at scale 

Once retailers see how intelligence enhances a single customer interaction, the next question naturally follows: where else can this help? Building on the advancements made with ADAM, Richtech Robotics is extending these capabilities through its Agentic Store initiative. By applying vision, voice, and agentic reasoning to common in-store tasks, the initiative helps retailers address friction points that slow down the shopping experience. 

Examples under development include: 

• Robots that guide customers to products.
• Systems that detect empty shelves or misplaced items.
• Voice-enabled, in-aisle assistance.
• Real-time adjustments based on foot traffic or local events.

This approach does not require heavy hardware investments. These workflows are software-driven and build on existing store infrastructure. It reflects how Frontier Firms drive transformation by spreading intelligence across the ecosystem rather than upgrading a single process at a time. 

Retailers gain clearer visibility into peak demand, customer behavior, product movement, and service quality without increasing manual tracking. As one store manager described it, “it feels like having a second set of eyes that never gets tired.” 

Convenient, high-quality service becomes a blueprint for store-wide intelligence. In the coming years, a clear difference will emerge between retailers that treat AI as a tool and those that treat it as a foundation. The latter will set the pace for the industry. 

Steps toward Frontier Transformation 

Agentic AI gives retailers a practical and achievable path forward. It elevates customer experience, reduces operational strain, and creates the foundation for smarter and more adaptive stores. Organizations that embrace Frontier Transformation position themselves as Frontier Firms, ready to scale faster, work more intelligently, and unlock new value through the combination of human judgment and AI-driven insight. 

The journey begins with small, strategic steps and a bold vision for what is possible. To explore the broader business impact of AI across frontline and customer-facing roles, review Microsoft’s Work Trend Index: The year the Frontier Firm is born.

Explore how organizations are transforming with AI, and learn how you can build your own generative AI proof of concept with the Microsoft AI Co-Innovation Labs.

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Akers lives with ADHD, dyslexia and dysgraphia, meaning tasks like reading, writing and organizing information require extra effort and creativity. She recalls having to turn down an invitation to read a passage at her brother’s wedding, and the confusion in one of the first teams she led at work when she referred to everyone by their first names, although several shared the same one, because she couldn’t easily read more complicated last names.

But as technology has evolved, so has Akers’ toolkit. AI-powered aids such as Copilot are helping her manage the cognitive load, shifting the focus from hurdles to strengths so she can communicate and lead in ways that once felt out of reach. She’s part of a growing wave of business professionals with neurodivergent traits — differences in brain function, including autism and attention-deficit/hyperactivity disorder (ADHD) — who are finding greater confidence and efficiency through AI.

There’s so many positive things that come out of having a brain that thinks differently.

Kim Akers
“When I saw the ability to take an input in, like here’s what I’m trying to communicate in an email, and then get it back in seconds and have it be 90% of the way there, that was a game changer,” says Akers, who uses Copilot at work and at home. “When the tech got good enough that you could use prompts, it really effectively cut down a lot of your prep work.”

Now that she can set her own meetings with Copilot’s help in Outlook, she has more control over her calendar and her days. She uses Microsoft 365 Copilot across the apps to do things like summarize documents, write emails and streamline meeting preparation by building lists of questions to ask her team about projects underway.

The tool helps her analyze sales data and draft outlines for presentations. It even helps her support her kids with their homework by generating practice problems or breaking down big assignments into manageable steps.

“Dr.
Dr. Cornelia C. Walther, a researcher and author who focuses on “prosocial AI” — systems designed to amplify human potential and foster equity (photo provided by Walther)
“Neurodivergent leaders who harness the full range of their natural and artificial assets are a beautiful illustration of the potential that the hybrid future offers for all of us,” says researcher and author Dr. Cornelia C. Walther, who focuses on “prosocial AI” — systems designed to amplify human potential and foster equity.

AI can be a bridge to greater inclusion and a connector that helps people participate more fully in society, says Walther, a senior fellow at the Wharton Neuroscience Initiative and Harvard’s Learning and Innovation Lab. The tools can help people with neurodivergence curate a new inner dialogue, moving beyond the self-judgment that can come with feeling different, she says.

“AI can serve as a sort of translator, not of language, but of ability,” Walther says. “It can make sure there is a path that connects your ability and makes it useful in the way in which society is currently normed.”

Recent research from professional services network EY underscores this, finding that generative AI can reduce barriers and support more inclusive ways of working. That’s significant for a workforce where an estimated 15-20% of people — and an even higher share of Gen Z — identify as neurodivergent.

In the EY survey of 300 employees with disabilities or neurodivergence across 17 organizations worldwide, respondents described how tools like Copilot helped with initiating tasks, organizing thoughts, spotting mistakes and improving accuracy. They said Copilot helped them stay on top of emails, focus in meetings instead of taking notes, and draft documents, spreadsheets and presentations — especially useful for those with dyslexia.

The study found Copilot’s impact goes beyond productivity. Participants said the tool’s support in making it easier to communicate, manage information and stay organized in turn boosted their confidence, motivation and impact. Many noted that Copilot helped them play to their strengths and overcome common hurdles, with 68% saying it reduced work anxieties and 71% saying it gave them hope.

“Hiren
Hiren Shukla, who founded the Neuro-Diverse Centers of Excellence at EY Global (photo provided by EY)
Neurodivergent professionals don’t just benefit from AI tools; they’re often the ones who find the most creative and effective ways to use them, says Hiren Shukla, who founded EY’s global neurodiversity program and lives with ADHD and dyslexia.

When EY ran a six-week innovation sprint with neurodivergent team members using Copilot earlier this year, Shukla says, ideas poured in: 60 to 80 process improvement suggestions, many sparked by the inventive approaches employees took to tackle problems.

“It’s not just AI helping neurodivergence,” Shukla says. “It’s the power of neurodivergence maximizing the use of Copilot. When you harness that divergence and partner with AI, you’ll see greater innovation, higher use cases, more ideation and application of AI.”

As organizations increasingly recognize the value of neurodivergent talent, and as AI tools become more inclusive, the ripple effects go beyond individual careers and corporate innovation to benefit everyone, he says.

This dynamic is especially pronounced at the leadership level, he says, where disclosure is often rare and role models are few.

“We hear a lot about frontline workers using AI, but not enough about neurodivergent leaders,” Shukla says. “Having executives like Kim Akers share their stories is crucial. It activates other leaders out there so they see themselves, lean in more and celebrate how they use AI, whether they disclose their neurodivergence or not.”

AI tools are creating opportunities for people who have been historically left out of mainstream companies and institutions, says Maitreya Shah, the American Association of People with Disabilities’ technology policy director.

“Maitreya
Maitreya Shah, the American Association of People with Disabilities’ technology policy director (photo provided by Shah)
“AI also gives you a level of independence and privacy for things you might not want to ask for help with from others,” he says, such as being able to communicate more effectively or understanding complicated yet sensitive health or financial documents. “That feeling of agency, of being able to do things independently, with AI helping you without involving family members or caregivers — all of that feels very transformative.”

As technology removes barriers, it also helps make room for the unique qualities neurodivergent professionals bring to their teams. For example, people with neurodivergence sometimes have a little extra empathy for and curiosity about others, Akers says, recognizing that they don’t necessarily know “what everybody’s bringing to the table.”

That curiosity draws Akers to set aside time every night to experiment with new tools and prompts, whether it’s exploring a competitor’s product, trying out a new Copilot feature or reading up on the latest advances in AI.

“I like to get my hands dirty, to actually physically try it and see what happens,” she says. “That’s how I stay up on top of it, just because it’s changing so fast.”

But it’s not only about keeping pace with technology; it’s about staying open to new ways of working and connecting. Akers credits her neurodivergence with making her more willing to lean into trial and error and with helping her appreciate the different perspectives her colleagues bring.

AI can serve as a sort of translator, not of language, but of ability.

Dr. Cornelia C. Walther
“When you’re neurodivergent, you have to always be figuring out little hacks,” she says. “You spend a lot of time learning from other people, like, ‘That worked for you, let me try it out.’ Collaborating, problem-solving, being creative, not being stuck on one way to do something, but being pretty open to trying things, and if they don’t work, just trying again with the next thing.”

It’s a blend of empathy, curiosity and adaptability that Akers sees as a leadership advantage — one that’s increasingly vital as AI tools reshape the workplace. By embracing experimentation and valuing difference, she’s not just finding ways to make her own work easier; she’s helping build a culture where everyone’s strengths have room to shine. It’s a commitment she carries into her role as co-executive sponsor of Microsoft’s Disability and Neurodiversity Inclusion Networks, groups dedicated to supporting and empowering employees across the company.

“There are so many positive things,” she says, “that come out of having a brain that thinks differently.”

Lead photo: Kim Akers, chief operations officer for Microsoft’s commercial business and co-executive sponsor of Microsoft’s Disability and Neurodiversity Inclusion Networks (photo by Scott Eklund)

The post How AI helps neurodivergent professionals showcase their strengths appeared first on The Microsoft Cloud Blog.

The question today isn’t whether AI can deliver value, but how quickly organizations can scale it across their business. Challenges such as aligning business and IT, ensuring data quality, navigating governance and regulatory considerations, and avoiding an overemphasis on experimentation can slow progress and widen the gap between leaders and slow adopters.

At Microsoft Ignite, the core message was clear: AI in the flow of work can unlock human ambition, and scaling with trust and observability is essential. Organizations that embed AI into everyday workflows empower people to achieve more, while trust and observability ensure innovation happens responsibly and at scale.

What sets a Frontier Firm apart

According to a recent study from IDC, 68% of organizations are using AI today, but the real difference lies in how they’re using it. Frontier Firms are realizing returns that are three times higher than slow adopters. What sets these leaders apart is the breadth and depth of their AI adoption. On average, Frontier Firms are using AI across seven business functions, with over 70% deploying AI in customer service, marketing, IT, product development, and cybersecurity.

A Frontier Firm is defined not by its size or industry, but by its mindset and execution. These organizations lead with AI-first differentiation, embedding intelligence across every layer of the business—from employee experiences to customer engagements to core processes. “Becoming Frontier” means moving beyond experimentation to enterprise-scale transformation, unlocking creativity, obsolescing the mundane, and driving competitive advantage in the agentic era. Leaders invest in upskilling, culture, and strong foundations—strategy, data, security, and compliance—to align technology with ambitious goals.

Successful Frontier Firms, as highlighted at Microsoft Ignite, share three common traits in their approach to AI. First, they integrate AI seamlessly into the flow of human ambition, amplifying creativity and accelerating decision-making through everyday workflows. Second, they foster ubiquitous innovation by democratizing AI creation—empowering everyone, from frontline employees to executives, to build agents and solutions that address real business challenges. Third, they prioritize observability at every layer, embedding governance, security, and compliance into all AI systems to ensure visibility, control, and trust as they scale. These traits collectively allow Frontier Firms to lead with agility, resilience, and measurable business impact.

Where AI is delivering business value today

The impact of AI is accelerating across industries. For example, Levi Strauss & Co. reduced project timelines from a year to a day with Microsoft Copilot and Copilot+ PCs. ABB is transforming industrial operations with Microsoft Azure and AI-powered insights, and Land O’Lakes is embedding AI into agricultural workflows to optimize supply chains and accelerate decision-making. These stories demonstrate how AI is driving measurable outcomes at scale.

This broad adoption is translating into measurable business impact. Compared to slow adopters, Frontier Firms report better outcomes at a rate that is four times higher across brand differentiation (87%), cost efficiency (86%), top-line growth (88%), and customer experience (85%). They’re not just automating tasks—they’re unlocking industry-specific value, with 67% monetizing AI use cases tailored to their sector and 58% already using custom AI solutions.¹

Partnering for Frontier transformation

As we’ve already alluded to, becoming a Frontier Firm isn’t just about technology—it’s about strategy, culture, and execution. Microsoft partners with organizations to accelerate transformation and measurable impact, combining deep expertise, integrated intelligence, and a global ecosystem. Trust is at the core of every AI experience, with enterprise-grade security, real-time observability, and automated governance built in.

Leading organizations are already putting these principles into practice—accelerating innovation, transforming customer experiences, and creating new sources of growth. These examples prove that becoming a Frontier Firm isn’t theoretical; it’s happening now.

The future of AI-powered business

The divide between AI leaders and others is growing, reshaping the competitive landscape. Frontier Firms are moving rapidly from pilots to widespread AI adoption, raising the bar for business impact. Microsoft Ignite underscored that the future belongs to organizations that embed AI at every level, empower their people, and lead with trust.

Becoming an AI-First Frontier Firm

Learn how bold organizations across industries are combining human expertise with AI agents to achieve faster growth, greater efficiency, and sustained innovation.

Get the e-book

For organizations ready to take the next step, the Becoming an AI-First Frontier Firm e-book offers practical insights and a roadmap for transformation.

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

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