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.

But behind these numbers are the real stories—organizations that have moved beyond experimentation to embed AI at the heart of how they operate. These “AI Challengers”—bold, AI-first businesses that are not just adapting to change but actively challenging the status quo and shaping the future.

These AI challengers haven’t just implemented new tools—they’ve reimagined what’s possible when AI becomes a core business capability. Find out how these companies are pulling ahead:

BOQ Group—Human-led transformation for banking reimagined

BOQ Group champions an employee and customer first approach to AI transformation. “At BOQ Group, we are committed to transforming the way we work and serve our customers by building an AI-ready workforce,” explains Chief Information Officer Craig Ryman.

The bank’s strategic rollout of Microsoft 365 Copilot delivered extraordinary results: over 70% of users now save 30 to 60 minutes each day. The impact extends far beyond time savings—completing business risk reviews in one day instead of three weeks, creating training programs in one day instead of three weeks, and improving report quality while speeding up sign-off processes from four weeks to one week.

BOQ’s approach emphasizes the critical insight that having a “human in the loop” is critical to AI adoption. The organization’s experience reveals universal adoption phases: users start with personal productivity gains, then focus on targeted opportunities, before ultimately transforming how work gets done entirely.

AI transformation is not just a technological transformation but a people-led transformation changing how we work. This is why it’s critical that any AI transformation starts by listening to and understanding team needs, spotting opportunities, and tackling challenges head-on to embrace the opportunities.

Enveda—Cracking the chemical code of life with AI

Enveda is innovating with AI by reinventing what is possible in medicine. It is focused on revolutionizing drug discovery by unlocking the potential of the vast majority of undiscovered molecules in nature. Enveda is using generative AI to identify and analyze thousands of compounds simultaneously, which significantly speeds up the drug development process and reduces costs.

“Today, nine out of ten drug candidates don’t make it through clinical trials, despite years of research and massive investment. This 90% failure rate pushes the cost of bringing a single new medicine to market as high as $6 billion. It’s an approach that simply can’t scale,” states CEO and Founder Viswa Colluru. 

At Enveda, AI is changing that. By decoding nature’s chemistry at scale, it is delivering drug candidates to clinical trials four times faster and at nearly one-tenth the cost.

AvePoint—Using AI to transform business inside and out

AvePoint is driving business innovation by embedding AI-powered capabilities into its product suite with Copilot. AvePoint also demonstrates the power of being your own best customer with its internal AI adoption. 95% of pilot participants actively use Copilot, with employees saving one to three hours per week by automating repetitive tasks, allowing them to focus on higher-value work.

As Mario Carvajal, Chief Strategy and Marketing Officer, noted, “Our investors care about efficiency, and AI is helping us deliver that. By freeing up time for higher-value work, we’re making our teams more effective and our business more competitive.” 

To accelerate adoption, AvePoint had two key strategies: upskilling its employees and creating focused, department-specific initiatives. AvePoint also encouraged a dialogue that sparked curiosity, built confidence and helped AI become a natural part of its daily workflows. As AI continues to evolve, AvePoint is positioned to lead the way, proving that the right foundation is key to unlocking its full potential. 

Eaton—Revolutionizing its energy management using AI

Eaton showcases how industrial companies use AI across complex global operations. “AI offers limitless potential for innovation, providing transformative technical opportunities that align with our growth objectives and advance our mission for sustainability and energy resilience by supporting grid flexibility, enhancing energy management, and delivering superior service and outcomes for our customers.,” explains Executive Vice President and Chief Information Officer Katrina Redmond. 

The company’s implementation of Copilot specialized agents brings functional expertise to areas like finance, sales, human resources, and service, handling repetitive, mundane tasks and freeing teams to focus on higher-value, strategic work that enables them to better serve their customers. By embedding AI into its culture and adopting a “think AI first” mindset, Eaton aims to drive further advancements in both technology, organizational strategy and will ensure that it can fully harness AI’s immediate potential while fostering sustained innovation across all aspects of its business.

The agent-enabled workplace

Each organization is driving innovation and demonstrates different aspects of the agent-enabled workplace—environments where AI agents work alongside human teams to accomplish complex business objectives, but all point toward a future where intelligent systems amplify human potential. 

Their success reinforces a critical insight: AI transformation requires more than technology adoption. It demands fundamental rethinking of business processes and competitive strategies. The organizations that recognize this—and act boldly on it—will define the next decade of business innovation. The future is here—and it’s time to claim your place in it. Will you lead or follow? 

Ready to join the AI challengers?

Explore how Microsoft’s AI solutions can transform your organization. Connect with our team to discuss your AI strategy or watch detailed case studies featuring each of these remarkable organizations.

Find the resources to support your AI journey:  

• Explore Microsoft’s AI solutions.
• Advance your AI transformation with AI business resources.
• View more AI Challengers executive insights.
• Listen to the Leading the Shift podcast to hear advice from leaders navigating the AI platform shift.

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¹ IDC 2025 Worldwide CEO Survey — Part 1: Overarching Insights, Business Priorities, and Risks, doc #US53155225, April 2025

² IDC, 2025 CEO Signature Report: Transforming Business for an AI World, doc #US53393625, June 2025

The post AI-powered innovation: How leading organizations are shaping the future appeared first on The Microsoft Cloud Blog.

But achieving personalization at scale requires more than AI and data analytics—it demands a powerful, secure, and adaptive infrastructure that enables you to deploy AI. Without a scalable, high-performing cloud foundation, businesses face challenges like latency issues, fragmented data, and high operational costs—all while grappling with the growing importance of data security and compliance. For organizations ready to embrace the future, building the right infrastructure foundation is the first step toward achieving personalization at scale—empowering them to innovate faster, respond in real time, and deliver transformative, trustworthy customer experiences. 

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Overcoming barriers to personalization at scale 

Achieving personalization at scale comes with its share of challenges. Businesses often contend with fragmented data systems, privacy and compliance concerns, and the complexity of acting on data in real time. While these hurdles can seem daunting, understanding them is the first step toward finding solutions. 

Fragmented data is one of the most common obstacles to personalization. Customer information is often scattered across systems, departments, or even physical locations, making it difficult to gain a unified view. For example, PointClickCare found that siloed healthcare data across providers delayed critical care decisions, highlighting the importance of breaking down these barriers to enable better insights.

It’s common for people to work with multiple healthcare professionals for different treatments and prescriptions, for the best care, everyone needs to access, use, and trust the most current, accurate information.

Andrew Datars, Senior Vice President of Engineering at PointClickCare

Real-time data processing adds another layer of complexity. Personalization requires immediate insights and responses, but many businesses struggle with legacy systems that can’t handle fluctuating demands. MediaKind, for example, encountered difficulties delivering real-time media experiences during peak events—putting customer satisfaction at risk. With the increase in competition in the industry and the pace of innovation around engaging with customers through video, they needed to find a way to match their current demands and innovation needs. “People get really upset when their entertainment is offline. Seconds of downtime costs broadcasters and streamers millions of dollars in advertising and brand revenue,” Allen Broome, MediaKind’s Chief Executive Officer notes. 

Privacy and compliance can create significant challenges for businesses aiming to deliver personalized experiences. Analyzing sensitive customer data requires navigating a maze of strict regulations, such as ensuring data residency, meeting regional compliance requirements, and safeguarding user trust. These challenges are particularly pronounced in industries like legal, where the sensitivity of data and the complexity of workflows add additional layers of difficulty. Harvey, a platform designed for the legal sector, faces these exact hurdles. Security is paramount for Harvey due to the need to comply with varied regional security requirements and ensure that data never crosses regional boundaries. “The reason it’s been so hard to build technology for industries like legal is the workflows are so varied and complex, and no two days are the same,” explains Gabe Pereyra, Co-Founder and President at Harvey. By prioritizing security and compliance from the ground up, Harvey provides a trusted solution tailored to one of the most demanding industries. 

While these challenges are real, they are manageable with the right strategies. Recognizing and addressing these barriers allows businesses to take their first steps toward achieving personalization at scale, turning these obstacles into opportunities for growth. 

Redefining customer engagement with cloud and AI technologies 

Scaling personalization to meet modern customer expectations is a complex challenge, but cloud and AI technologies make it practical. Together, they empower organizations to process vast amounts of data, generate actionable insights in real time, and deliver tailored experiences at scale. 

For many organizations, data is scattered across disconnected systems, creating silos that prevent a unified view of customer behaviors and needs. Overcoming this barrier requires modernizing infrastructure to centralize data, enable seamless integration, and provide real-time access to actionable insights. Cloud platforms like Microsoft Azure make this possible by offering secure and scalable solutions that unify fragmented data sources into a single, comprehensive view. For example, PointClickCare leveraged Azure to consolidate siloed healthcare data from multiple systems into a unified network. PointClickCare modernized their infrastructure by deploying a cloud-based solution with key Azure products like Windows Server, Azure SQL Managed Instance, and Azure OpenAI Service to securely integrate data, streamline workflows, and enable real-time access to critical patient information. This transformation provided healthcare providers with actionable insights, improved operational efficiency, and enhanced patient care.  

Personalization hinges on immediacy, and AI-powered cloud platforms enable businesses to process massive streams of data in real time, offering insights and actions when they matter most. Overcoming this challenge requires infrastructure that can handle both the scale and speed of data processing without delays. LALIGA achieves this by leveraging cloud-based AI and machine learning to analyze over 3 million data points per match, all processed in real time. Operating within a hybrid environment, they ensure consistent performance by distributing workloads intelligently across on-premises and cloud systems using Microsoft Azure Arc. This allows LALIGA to deliver engaging digital and in-stadium experiences, from detailed match statistics to personalized player insights, enhancing how fans connect with the game. 

To ensure real-time data provision, cloud infrastructure must be capable of adapting to variable demands. Cloud solutions provide elastic scalability, ensuring organizations can handle varying workloads without compromising performance. With 30 teams, more than 500 players, and each team playing 82 games per season, not including playoffs, the NBA have an enormous amount of player data to collect and analyze. In exploring how AI could help them process data on all on-court players’ specific live body movements, analyzing things like speed, dunk height, number of passes and dribbles, and even injury risk, simultaneously, can create a need for elastic scalability. The NBA used a Microsoft Azure solution, based on Azure Kubernetes Service (AKS), that can manage and process up to 16 gigabytes of raw data per game, not including RGB video signals—sometimes more if the game goes into overtime. The new solution is deployed and operational, and the data being collected is already helping the NBA better understand players’ strengths and weaknesses and improve their performance.  

Lastly, trust and security are fundamental to achieving personalization at scale. In today’s environment, businesses must be able to navigate strict regulatory requirements, safeguard sensitive customer data, and maintain user trust while delivering tailored experiences. Overcoming these challenges requires implementing robust security measures, such as end-to-end encryption, role-based access controls, and compliance monitoring, all of which can be enabled and streamlined through cloud platforms. Azure provides a unified environment where businesses can securely integrate data, enforce regulatory compliance across regions, and monitor potential risks in real time, ensuring sensitive information is protected at every stage. Harvey, for example, leveraged advanced encryption, access management, and compliance tools to meet the stringent security requirements of its clients. This solution enables law firms to confidently protect sensitive client data while delivering innovative, AI-powered legal services. As Harvey’s Chief Executive Officer explained, “Law firms trust Azure because it allows them to deliver cutting-edge, AI-driven legal services without compromising on security or compliance.” This commitment to security enables Harvey to focus on innovation while maintaining trust with its clients. 

Transform your business with scalable personalization 

Personalization at scale is essential for businesses striving to stay competitive in today’s rapidly evolving market. Customers increasingly expect experiences that feel tailored, anticipate their needs, and build trust. As cloud and AI technologies continue to advance, the opportunities for deeper, more impactful personalization will only expand. 

You can stay ahead of the competition by delivering personalized experiences that resonate with your customers. Here are some essential steps you can take to get started today:  

• Audit your data landscape to identify silos and unify disparate systems into a centralized platform for streamlined insights.
• Establish robust data governance policies to ensure compliance, security, and transparency, earning and maintaining customer trust.
• Invest in scalable, elastic cloud infrastructure that grows with your needs, so you can handle the demands of real-time personalization.
• Empower your teams with the training and tools needed to effectively leverage AI and cloud technologies, making personalization a reality. 

By acting now, businesses can not only meet today’s customer expectations but also pave the way to lead in a future driven by secure, scalable, and transformative personalization.

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¹ McKinsey & Company, The value of getting personalization right—or wrong—is multiplying, November 2021.

The post Personalization at scale: How cloud and AI are redefining customer engagement appeared first on The Microsoft Cloud Blog.

The AI platform shift brings immense opportunity, but the road to success isn’t always easy or clear. That’s why we’ve asked customers, partners, Microsoft experts, and other leaders to share their journeys and insights in our new podcast, Leading the Shift.

In each episode, we’ll explore how our guests are using data, AI, and cloud technologies to deliver meaningful and trustworthy innovation to their organizations, customers, and communities. You’ll hear from executives, developers, data scientists, and visionaries across industries in both the public and private sectors. We’ll discuss how the platform shift is affecting everything from data strategy, customer relationships, organizational structure, and culture, to their own lives and career journeys. And, most importantly, they’ll share what they’ve learned along the way, as well as their advice on how to get started and how to navigate bumps in the road.

The first four episodes of Leading the Shift cover a lot of ground, from how data and AI are being used for social impact, to the use of AI to create a fan remix experience for a world-famous band, to the opportunity to use data, AI, and cloud technologies to map the customer journey and truly personalize experiences, to the potential for proprietary data to transform an organization’s competitive advantage.

Throughout these conversations we aim to get at the heart of the approaches, tools, techniques, opportunities, threats, and emerging best practices that leaders are adopting as they learn by doing. We’ll see common themes emerge: the transformative power of data and AI, the importance of trust, the innovation potential of co-creation, and the value of getting hands-on during the process.

Leading the Shift

Listen and learn from our first four episodes, out now.

Listen here

Here’s what you can expect from our first four episodes:

Creating the new field of data for social impact, with Perry Hewitt, data.org

You’ve heard about data-driven products and services, and even data-driven business models. But in our premiere episode, Perry Hewitt, Chief Marketing and Product Officer at data.org, discusses how the organization is using data and AI to create an entirely new field—data for social impact.

Perry shares how data.org is working with organizations around the world to co-create solutions to some of the world’s greatest challenges, such as dispelling misconceptions about women’s health in India, upskilling migrant Venezuelan women in Chile, and creating intensive AI curricula for teachers, students and businesses in rural Mississippi.

It’s a rigorous and innovative approach built around trust, respect, and co-creation, and is as applicable to business as it is to the public sector.

Remixing the Coldplay fan experience with AI, with Robby Ingebretsen, Pixel Lab

In this episode, Robby Ingebretsen, Founder and Creative Director of Pixel Lab, an award-winning creative agency, talks about how he and his team built a fan remix experience that builds on the release of Coldplay’s new album, MOON MUSiC, and its film compendium, A Film For The Future.

The fan remix experience offers people the opportunity to join a community of Coldplay fans to create their own remix of the film using inputs that match their mood and attribute choices and contribute to the film as their piece is added to the future playback.  

It’s a wide-ranging conversation that explores the impact of digitalization and platform shifts in the music and technology industries, the impact and opportunities of AI, and how co-creation can unlock new opportunities for creativity, engagement, and innovation for customers and consumers across a range of industries. Read more about how this experience was built with Azure AI Foundry.

Data doesn’t just fuel generative AI—it goes both ways, with Shirli Zelcer, dentsu

Shirli Zelcer began her career as a statistician and is now Chief Data and Technology Officer at dentsu, an integrated growth and transformation partner to the world’s leading organizations. It’s a fascinating role, and her roots in data, combined with a deep understanding of AI, have prepared her to bring data and AI together to help dentsu and its clients unlock new sources of value.

Shirli shares a bit about her journey, including how she’s seen data and analytics evolve from a back-office practice to a C-suite priority. We explore a range of topics, including new approaches to generating audiences, the opportunity to combine structured and unstructured data to better understand customer needs and behavior, the value of synthetic data, and—underlying all of this innovation—the imperative to use intelligent data and technologies in a trustworthy, responsible, and privacy-compliant way.

Your proprietary data is your competitive advantage, with Teresa Tung, Accenture

In this episode, we talk with Teresa Tung, Global Lead of Data Capability at Accenture, about the evolving role of data in AI strategy. We explore the strategic value of proprietary data, how generative AI can help organizations realize value from unstructured data, the changing landscape of data governance, and how synthetic data can model sensitive scenarios in a safer way. We also discuss how generative AI can help organizations jumpstart data capability.

Teresa is a prolific inventor, holding over 225 patents and applications, and leads the vision and strategy that ensures that Accenture is prepared for ever-changing data advancements. It’s a real treat to hear her share what she’s seeing in the industry and what she believes will help organizations deliver value to their customers and clients.

Looking ahead with Leading the Shift

Leading the Shift will release new episodes in the last week of each month. Listen, like, and subscribe wherever you get your podcasts, including Spotify, Apple Podcasts, and YouTube.

Listen to Leading the Shift now

The post Introducing Leading the Shift, a new Microsoft Azure podcast appeared first on The Microsoft Cloud Blog.

The Cloud Cultures series is an exploration of the intersection between cloud innovation and culture across the globe.

Once known for its dominance in the coal, steel, and manufacturing industries, the American Rust Belt is entering a new era of innovation. Thousands of startups, a focus on homegrown talent, and a rich culture of resilience are sparking an unmistakable resurgence in the region. 

Excited to explore this industrious spirit and a cloud culture closer to home, I ventured to the Northeastern and Midwestern states—the famed Rust Belt—to learn how entrepreneurial adaptability is energizing both people and businesses in the area. 

Rediscovering an entrepreneurial spirit through cloud innovation

My journey began on a winter day in Cincinnati, where the Ohio River borders Kentucky—a scene set with icy winds swirling over city streets and expansive farms. But it’s clear that the weather doesn’t deter progress here. I ducked into a cozy coffee shop to escape the cold and meet with my cohost, Devon Allen, a Microsoft colleague, and product marketing manager for Azure.

Devon is a unique cohost for this episode because of her ties to the region: she has deep roots in Appalachia and went to school in Ohio. Over coffee, she shared examples of how people in this area of the country are embracing adaptability and leaning into educating the next generation of talent, and in the process, are more resilient than ever before. Caffeinated and eager to explore, we parted ways to conduct our first interviews with local leaders.

Synthetaic represents a wave of new startups 

Devon started off with a visit to Lambeau Field, the home of the NFL’s Green Bay Packers and a symbol of the area’s vibrant character. There, she met with Corey Jaskolski, CEO of Synthetaic, a startup with a remarkable mission. Beginning as a project within TitletownTech—an incubator for tech startups formed in partnership between the Green Bay Packers and Microsoft—Synthetaic’s mission is to help organizations exponentially accelerate speed-to-insight and leverage AI for good.

Corey Jaskolski is not just Synthetaic’s CEO; he’s a National Geographic Fellow, explorer, engineer, and MIT graduate. Through his global expeditions, Jaskolski recognized the potential of technology to enhance exploration and conservation efforts in some of the world’s most beautiful and unforgiving environments.

Synthetaic’s RAIC (Rapid Automatic Image Categorization) solution automates the analysis of large, unstructured datasets so organizations can train and deploy AI models radically faster than other approaches. While other image processing tools require deep and time-intensive calibration, RAIC can immediately detect and classify anything from a single source image, exponentially accelerating speed-to-value and reducing the risk of human error.

Synthetaic is just one of more than 18,000 startups re-energizing the region—a truly staggering number. I was heartened to see how an area famous for its industrial history is recapturing the entrepreneurial spirit with cloud innovation at the forefront.

University of Cincinnati nurtures innovators and talent 

While Devon learned how AI can positively impact the world, I visited the University of Cincinnati’s 1819 Innovation Hub, a beacon of inspiration on campus that has helped UC contribute $10.6B in local economic impact. Experiencing this one-stop shop for technological advancement, ideas, and problem-solving, it was clear why the Rust Belt is flooded with incredible talent and forward-thinking innovators. In the modern, beautiful building that houses the Innovation Hub, I saw firsthand the spirit of innovation that has taken root in these states. 

During my visit, I was fortunate to attend a class at the Innovation Hub. After an inspiring question and answer session with a group of students, I spoke with Assistant Vice President Kate Harmon, leader of the Center for Entrepreneurship, Associate Professor Aaron Bradley who teaches design thinking and leads the innovation scholars program, and a current student, Jay Kothari, to learn more about the work happening at UC to bridge technology and AI across all industries. Entrepreneurial adaptability is a focal point of this urban public university, providing students with a plethora of classes, resources, and learning opportunities to help them succeed. It’s even in the school motto: “NEXT Lives Here.” In fact, a recent study shows that founders of a U.S. startup who studied or worked at UC are 3.3 times more likely to achieve unicorn founder status—the highest odds ratio in the nation. Our discussion illuminated how advances in cloud technologies will continue to impact education going forward, and how the students are empowered to innovate with technology to improve their own communities.

The future of innovation in the American Rust Belt 

To conclude our journey, we indulged in one of Devon’s favorite local eats at the 1940s diner, Camp Washington Chili. In Cincinnati, I learned there is more than one way to enjoy this comfort food—there are five. Served over spaghetti and topped with warmed red kidney beans, diced raw onions, and shredded cheddar cheese, a bowl of five-way chili was a unique and delicious way to end the trip.

As we dug in, we chatted about our interviews and reflected on the grit and dedication embodied by everyone we spoke with. Devon shared how Jaskolski, another local, saw an abundance of talent with these same traits and understood the advantages of starting a company in the Midwest. For example, his commute to Synthetaic is only four minutes—allowing him to spend more time with his family and embrace creativity in his downtime. This was an important consideration for himself and his employees. I also told Devon about the captivating conversations I had with the University of Cincinnati’s 1819 Innovation Hub students. Their drive and forward-thinking ideas will continue to shape this region into a tech hub of the Midwest, or a “Silicon Heartland,” as Kate Harmon put it. 

I was struck by the energy that’s paving the way for a bright future in the Rust Belt. There is change happening here—undoubtedly influenced by the acceleration of digital transformation we see on a global level. But it’s the heart and soul of the people, their ambition to adapt and grow, and their industrious heritage, that makes the resurgence possible.

I’m excited to watch this area continue to nurture their deep talent pool and innovate with technology to create positive impact—but for now, there are more cloud cultures to explore. See you on my next adventure, this time much further East! See you in Japan.

Learn more

• Watch more Cloud Cultures episodes 

The post Cloud Cultures, Part 8: Recapturing the entrepreneurial spirit in the American Rust Belt appeared first on The Microsoft Cloud Blog.

AI is currently at the forefront of global technological advancement, permeating various sectors from insurance to energy, driving efficiency, innovation, and transformative changes in society. With ongoing developments in machine learning and natural language processing, AI continues to reshape industries, offering a glimpse into a future where technology and human ingenuity intersect in exciting new ways. The expanding footprint of AI promises both unprecedented opportunities and considerations for responsible implementation.  

For me personally, one of the most exciting aspects is seeing the revolution of industries set into motion as sector-specific use cases begin to emerge. The number of Azure AI customers continues to grow with more than 65% of the Fortune 500 companies now using Microsoft Azure OpenAI Service, which underscores the critical role of partnerships and industry innovation to scale AI solutions to full potential across sectors.

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This willingness of industry leaders to be pioneers of AI was on bold display during the Microsoft AI Tour stop in Paris, part of the global event series designed to help decision makers and developers discover new opportunities with AI and advance their knowledge. Organizations such as Schneider Electric, The Groupama Group, Amadeus, Onepoint, AXA, and TotalEnergies are not just adopting AI; they’re redefining its potential. These groundbreaking use cases are shedding light on a future where AI is not just a tool, but a catalyst for a richer, more efficient, and more sustainable world.

Groupama’s virtual assistant optimizes policyholder service management

The Groupama Group, a premier mutual insurance group in France, has introduced a cutting-edge virtual assistant within its Employee Savings unit, harnessing the power of Azure OpenAI Service, Azure AI Search, and the Microsoft Bot Framework, to streamline customer managers’ interactions with policyholders. First ideated during an AI hackathon, the assistant has been embraced by the unit’s entire staff and boasts an impressive 80% success rate in providing accurate, dependable, and verifiable information.

“Our managers save a considerable amount of time and are able to carry out their work in much better conditions,” shared François-Xavier Enderlé, Head of Digital Transformation, “and this clearly enhances the quality of the relationship we maintain with our customers.”

Groupama has also stood up an interdepartmental AI-centered think tank, AI Factory, which is currently exploring more than 25 AI use cases aimed at revolutionizing claims processing, enhancing customer service through tools like a new FAQ chatbot, and streamlining the underwriting process for efficiency. Further, Groupama aims to democratize AI technology through training on AI prompting, empowering employees to innovate and improve operational efficiency and customer engagement.

Amadeus enhances employee efficiency with Copilot for Microsoft 365

Amadeus, a global technology provider for the travel industry, has deployed Copilot for Microsoft 365 to streamline work and free employees to focus on value-added tasks. Seamlessly integrated into Microsoft Teams, Word, PowerPoint, and Outlook, Amadeus’ Copilot solution has significantly improved operational efficiency.

“One of the challenges for large-scale, global organizations is the collaboration and the data management,” explains Marco Ruiz González, Product Manager and Solution Architect who supervised the deployment. “We are generating a large amount of data from different countries, and it’s very useful to have quick access to all this data.”

Early results are promising: pilot users reported substantial time savings in communication drafting, enhanced efficiency in email and meeting management, and improved information gathering and content translation capabilities.

With a 90% adoption rate among the initial 300 pilot users, half of whom engage with Copilot weekly, Amadeus plans to extend Copilot to 3,000 employees over the next six months, prioritizing adoption training tailored to diverse user profiles.

Schneider Electric leads the charge in sustainable energy management with AI

Schneider Electric is tackling the complex issue of optimizing energy use and performance with its EcoStruxure platform. By combining Azure OpenAI Service and Internet of Things (IoT), EcoStruxures merges Schneider Electric’s industry knowledge with Microsoft AI technology, enabling sustainable energy solutions and efficient energy management on a global scale. This includes dynamic control of energy performance, decision-making on the use of renewable energy sources, and overall energy optimization.

“People are using sustainable energy solutions to both produce and consume energy, and they can optimize how to produce or store that energy on the grid as it makes sense,” says Yoann Bersihand, Vice President of AI Technology at Schneider Electric. “Without AI, there is no way that we could address a problem as complex as this.”

The platform is designed with a layered architecture, planning future enhancements to integrate AI directly into hardware for efficient and sustainable energy management, especially beneficial for customers with limitations on using cloud services.

Schneider Electric has expanded its partnership with Microsoft, integrating Azure OpenAI Service into its operations to enhance efficiency and innovation across various processes. The integration enables the creation of solutions such as the Resource Advisor Copilot, leveraging large language model technology for data analysis and decision support, and Jo-Chat GPT, an internal tool enhancing employee productivity through generative AI. Further innovations include a programmable logic controller (PLC) code generation assistant that helps engineers quickly create high-quality, tested, and validated code, the Finance Advisor and Knowledge Bot, aimed at improving financial decision-making and customer service, respectively, as well as plans to incorporate GitHub Copilot to boost offer creation and Microsoft Copilot for Sales to support frontline staff. These advancements signify Schneider Electric’s commitment to leveraging generative AI for operational excellence and innovation.

“We didn’t want AI just to be an extra layer on top of the data teams. We decided to really go all-in on AI and not simply create proofs of concepts,” explained Yoann Bersihand, Schneider Electric’s Vice President of AI Technology, capturing Schneider Electric’s commitment to fully integrating AI into its operations to lead innovation in the energy sector.

Onepoint unlocks productivity company-wide with generative AI

An early adopter of AI, technology and consulting firm, Onepoint, is infusing AI at every level of the company with Microsoft’s turnkey generative AI solutions: Azure OpenAI Service, GitHub Copilot, and Copilot for Microsoft 365.

Neo, Onepoint’s secure conversational agent built on Azure OpenAI Service, leverages a library of prompts and business-oriented solutions to quickly generate reports and analyses, increasing productivity for 3,300 employees across the company. Onepoint has also piloted GitHub Copilot, resulting in higher-quality code, better documentation, and productivity gains around 40% on code production.

“The pilot showed us that if developers were properly acculturated to the product, it was really possible to make a quantum leap in productivity,” asserts François Binder, Partner Data & AI for Onepoint.

Addressing the challenge of acculturating employees to AI technology and practices, Onepoint has instituted an “AI Office” to ensure both technical and non-technical staff understand and adopt AI effectively. By providing structured training, fostering an AI community, and overseeing the deployment of AI solutions, the unit seeks to bridge knowledge gaps and biases related to AI among both technical and non-technical employees.

“We’re doing everything we can to fully embark our team in the generative AI adventure and give each of our consultants the means to become augmented consultants,” insists Binder.

What’s more, Onepoint is strategically integrating generative AI solutions into its offerings, along with personalized training to ensure customers are well-versed in AI’s capabilities and best practices, extending the benefits of AI to their customers as well.

AXA’s secure generative AI platform boost productivity of global employees

AXA, a global leader in insurance and asset management, is embracing the digital future through generative AI with the launch of AXA Secure GPT. Developed in collaboration with Microsoft and powered by Azure OpenAI Service, this AXA Secure GPT is designed to equip AXA’s 140,000 employees with cutting-edge AI tools in a secure and efficient manner.

Addressing the challenge of safely integrating public AI advancements within the corporate environment, AXA Secure GPT ensures the utmost privacy and control over data by employing robust filtering and classification, alongside secure cloud tenancy to keep all data and interactions within a controlled environment. Stringent authentication protocols and comprehensive security controls monitor and protect against potential threats. By leveraging Microsoft’s content filtering and adding an extra layer of security, AXA Secure GPT exceeds the current standards for data privacy and security, ensuring a reliable and secure tool for its employees.

With the goal to scale from 1,000 current users to all 140,000 global employees by mid-2024, AXA provides comprehensive AI support and training which includes leveraging Microsoft consulting services for optimal technological use and architecture design, alongside a dedicated change management program in each country to ensure smooth integration.

“As an employer, it is our responsibility to provide our employees with the best tools to enhance their comfort and enable them to focus on high-value activities,” said Vincent De Ponthaud, Head of Software & AI Engineering at AXA. Tailored training sessions and a specially curated prompt library, aimed at enhancing productivity across various departments, empower AXA employees to focus on high-value activities.

TotalEnergies supports operational transformation with AI and low-code solutions

Multi-energy company, TotalEnergies, has implemented Copilot for Microsoft 365 to support operational transformation. In the initial testing phase involving 300 employees, the company observed enhanced operational efficiency and improved user experience. Concurrently, TotalEnergies is empowering its workforce with Microsoft Power Platform, enabling them to develop low-code/no-code solutions integrated with other company applications and databases, thereby streamlining the resolution of various day-to-day challenges.

“In line with our pioneering spirit, TotalEnergies is committed to digital transformation and supports its employees so that they can make the most of it,” said Patrick Pouyanné, CEO of TotalEnergies. “The new technologies of generative artificial intelligence and of ‘low code no code’ will provide them with the simplification and autonomy they need to put their skills and creativity even further at the service of our company’s transition strategy.” In pursuit of this objective, TotalEnergies employees will receive training dedicated to the understanding and utilization of the new AI tools effectively.

AI for everyone

The Microsoft AI Tour provided a compelling opportunity to witness firsthand the pinnacle of regional innovation and to glimpse the far-reaching global impact poised to shape our future. Reflecting on the transformative journey of AI within France alone, it becomes evident that we’re venturing into an unprecedented era of technological advancement. The success stories of companies like Schneider Electric, Groupama, Amadeus, Onepoint, and TotalEnergies illustrate how the synergy between AI and human ingenuity propels progress and transformation across diverse sectors, transformation that will doubtlessly reach beyond borders to the benefit of organizations across the globe.

It’s also important to recognize that our exploration with AI is in its infancy and the horizon for transformative impact is limitless. It’s critical that business leaders scaffold AI innovation within an architecture of responsible AI, which include the development of ethical guidelines that address transparency, equity, accountability, and privacy; building diverse teams; investing in employee education around responsible AI use; and collaboration with industry bodies and policymakers to establish regulatory frameworks that can guide responsible deployment. When innovation and responsibility are aligned, we draw closer to ensuring that the potential for transformational impact of AI will be harnessed for the benefit of society as a whole.

Take the next step in your AI journey by exploring Microsoft AI solutions, diving into The AI Strategy Roadmap, and getting skilled up with Microsoft Learn’s AI learning hub to ensure you’re ready to leverage Microsoft AI to its fullest potential.

The post Groundbreaking AI innovation is transforming industries across France appeared first on The Microsoft Cloud Blog.

AI is redefining the boundaries of what’s possible, but the unique demands of AI—from vast data volumes and high-speed processing requirements to complex security and compliance challenges—require a strategic approach to data and technology infrastructure.

“It’s been over a year now since generative AI became mainstream. We are through the science experiment phase and leading companies are now putting AI into action,” says Wangui McKelvey, General Manager, Microsoft Azure Data Analytics.

In this post, we’ll focus on the five data and technology fundamentals required to deliver meaningful, sustainable, and responsible value creation with AI:

1. Align technology strategy and business strategy
2. Assess infrastructure needs and goals
3. Prepare your data estate to smooth the path from proof-of-concept to production
4. Consider build-versus-buy decisions
5. Determine a strategy for regulatory compliance and safeguarding AI assets

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Building a Foundation for AI Success: A Leader’s Guide

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Align technology strategy and business strategy

Successful AI projects begin with a clear, prioritized, and valued set of business objectives, such as maximizing productivity and efficiency, improving customer experience, or growth-oriented objectives such as revenue acquisition or product innovation. These goals will help you prioritize use cases against likelihood of impact and realistically assess feasibility based on data and infrastructure requirements. It’s also useful to think of your technology investments in aggregate as an investment portfolio, which will enable you to set clear success criteria and reallocate resources across projects as needed.

Assess infrastructure needs and goals

Moving successfully from proof-of-concept (POC) to production with AI depends on a mix of technology and business factors that, ideally, must work together.

“Understanding how your business strategy maps to your product strategy, and then how your product strategy maps to your infrastructure, is key,” says Omar Khan, General Manager, Microsoft Azure Product Marketing. “AI-optimized infrastructure will help accelerate both building AI solutions and integrating AI into applications.” From a technology perspective, the most critical requirement is access to infrastructure that is built for AI—with the ability to run large AI workloads and perform securely and reliably at scale.

• Cloud-based AI deployments leverage third-party cloud service providers to access scalable and flexible computing power without the need for extensive on-premises infrastructure. This option allows for cost efficiency with pay-as-you-go models and access to a variety of AI services.
• Colocation, or the practice of renting space within a third-party data center to house privately-owned servers and networking equipment with data, applications, AI services, and infrastructure all in one place—minimizes transfer times and leads to lower latency, which is crucial for real-time and high-performance AI applications. Colocation also provides cost savings because centralized infrastructure is more efficient to manage, maintain, and scale, reducing overall operational costs.
• On-premises deployment refers to hosting and running applications and infrastructure within an organization’s physical premises or datacenters. While this deployment option gives organizations more control over their IT infrastructure, it can mean high upfront costs for hardware, ongoing maintenance responsibilities, and limited scalability.

Prepare your data estate to smooth the path from proof-of-concept (POC) to production

Data is the fuel that powers AI technology, so planning for any successful AI implementation requires that you identify the right data sources and ensure that the data is complete, of high quality, in the right format, and representative of your target customers and business objectives.

“Organizations continue to see their data as their competitive advantage,” says Wangui McKelvey. “Unlocking insights from their data, across their organization, in a single, integrated platform, empowers businesses to take advantage of AI. If you don’t understand the insights you can deliver from your data with AI, then you’re going to be left behind.”

Consider what to build vs. what to buy

The decisions you make today to buy, build, or modernize your technology infrastructure can significantly influence your ability to execute on future goals, so it’s essential to choose a path that is supportive of your organization’s vision. Here are some of the considerations and trade-offs:

• Build: A “build” strategy enables you to tailor solutions precisely to your needs and implement your strategic business vision. Custom-built AI applications give organizations greater flexibility and control over the development process, facilitating scalability to accommodate future growth and evolving business needs.
• Modernize: In some scenarios, existing AI applications may still deliver value, but need an update to meet current demands. This approach can be beneficial when you have substantial investments in legacy AI infrastructure, but technology has evolved and your applications need to catch up.
• Buy: Some businesses buy prebuilt AI solutions, which may be a viable option if your AI use cases align with existing products. However, prebuilt AI solutions offer limited customization, reducing the ability to support more specific business needs. Other important considerations include integration complexities with existing IT systems, scalability limitations, and cumulative long-term costs, including licensing fees and upgrades.

Determine a strategy for regulatory compliance and safeguarding your AI assets

Regulatory compliance, particularly with the General Data Protection Requirement (GDPR) and the coming EU AI Act, introduces a set of technical, legal, and operational considerations for infrastructure choices.¹ Factors such as data sensitivity, data residency, scalability, and governance all play a part in architecture decisions, whether organizations choose on-premises, cloud, or co-located deployments. One critical factor to consider is access to sophisticated security measures that utilize machine learning, AI, and global threat intelligence databases to contribute to a more robust defense against cyber threats.

“Contrary to common belief, on-premises environments are often less secure than the cloud,” says Omar Khan. “Despite the sense of control associated with in-house infrastructure, cloud-based security solutions have evolved significantly, offering more advanced tools and technologies for threat detection and mitigation.”

Next steps

Stay tuned for the next post in our series, “Building a Foundation for AI Success: AI strategy and experience,” in which we will explore the factors that contribute to a successful AI strategy and experience for customers. We will follow the next entry with dedicated posts focusing on organization and culture, and AI governance.

Download a copy of “Building a Foundation for AI Success: A Leader’s Guide.”

¹EU AI Act.

The post Building a foundation for AI success: Technology and data strategy appeared first on The Microsoft Cloud Blog.

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Dentsu drives creativity and growth for brands, supported by Microsoft Copilot.
Enriching employee experiences and shaping the future of work with copilot technology

Bayer employees are collaborating better on worldwide research projects and saving time on daily tasks with Copilot for Microsoft 365, while Finnish company Elisa is helping knowledge workers across finance, sales and customer service streamline routine tasks. Banreservas is driving employee productivity and enhancing decision-making, and Hong Kong’s largest transportation companies — Cathay and MTR — are streamlining workflows, improving communications, and reducing time-consuming administrative tasks. Across professional services, KPMG has seen a 50% jump in employee productivity, Dentsu is saving hundreds of employees up to 30 minutes per day on creative visualization processes, and EY is making it easier to generate reports and access insights in near real-time with Copilot for Microsoft 365. In Malaysia, financial services organization PNB is saving employees time searching through documents and emails and AmBank employees are enhancing the quality and impact of their work. At Hargreaves Lansdown, financial advisers are using Copilot for Microsoft 365 and Teams to drive productivity and make meetings more inclusive. Avanade is helping sellers save time updating contact records and summarizing email threads with Copilot for Dynamics 365, while HSO Group, Vixxo, and 9altitudes are streamlining work for field and service teams.

Employee and customer in store
Organizations are creating their own Generative AI assistants to help employees improve customer service.
Reinventing customer engagement with generative AI to deliver greater value and increased satisfaction

MECOMS is making it possible for utility customers to ask questions and get suggestions about how to reduce power consumption using Microsoft Fabric and copilot on their Power Pages portal. Schneider Electric has built a Resource Advisor copilot to equip customers with enhanced data analysis, visualization, decision support and performance optimization. California State University San Marcos is finding ways to better understand and personalize the student journey while driving engagement with parents and alumni using Dynamics 365 Customer Insights and Copilot for Dynamics 365. With Azure OpenAI Service, Adecco Group is bolstering its services and solutions to enable worker preparedness as generative AI reshapes the workforce, UiPath has already helped one of its insurance customers save over 90,000 hours through more efficient operations, and Providence has developed a solution for clinicians to respond to patient messages up to 35% faster. Organizations are building generative AI assistants to help employees save time, improve customer service and focus on more complex work, including Domino’s, LAQO and OCBC. Within a few weeks of introducing its copilot to personalize customer service, Atento has increased customer satisfaction by 30% while reducing operational errors by nearly 20%, and Turkey-based Setur is personalizing travel planning with a chatbot to customize responses in multiple languages for its 60,000 daily users. In the fashion industry, Coats Digital launched an AI assistant in six weeks to make customer onboarding easier. Greece-based ERGO Insurance partnered with EBO to provide 24/7 personalized assistance with its virtual agent, and H&R Block introduced AI Tax Assist to help individuals and small business owners file and manage their taxes confidently while saving costs.

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Novo Nordisk is building out GitHub Copilot integration to decrease repetitive research and engineering tasks.
Reshaping business processes to uncover efficiencies, improve developer creativity and spur AI innovation

Siemens built its own industrial copilot to simplify virtual collaboration of design engineers and front-line workers, accelerate simulation times and reduce tasks from weeks to minutes. With help from Neudesic, Hanover Research designed a custom AI-powered research tool to streamline workflows and identify insights up to 10 times faster. With Microsoft Fabric, organizations like the London Stock Exchange Group and Milliman are reshaping how teams create more value from data insights, while Zeiss is streamlining analytics workflows to help teams make more customer-centric decisions. Volvo Group has saved more than 10,000 manual hours by launching a custom solution built with Azure AI to simplify document processing. By integrating GitHub Copilot, Carlsberg has significantly enhanced productivity across its development team; and Hover, SPH Media, Doctolib and CloudZero have improved their workflows within an agile and secure environment. Mastery Logistics Systems and Novo Nordisk are using GitHub Copilot to automate repetitive coding tasks for developers, while Intertech is pairing it with Azure OpenAI Service to enhance coding accuracy and reduce daily emails by 50%. Swiss AI-driven company Unique AG is helping financial industry clients reduce administrative work, speed up existing processes and improve IT support; and PwC is simplifying its audit process and increasing transparency for clients with Azure OpenAI Service. By leveraging Power Platform, including AI and Copilot features, Epiq has automated employee processes, saving over $500,000 in annual costs and 2,000 hours of work each month, PG&E is addressing up to 40% of help desk demands to save more than $1 million annually, and Nsure is building automations that reduce manual processing times by over 60% and costs by 50%. With security top of mind, WTW is using Microsoft Copilot for Security to accelerate its threat-hunting capabilities by making it possible for cyber teams to ask questions in natural language, while LTIMindtree is planning on using it to reduce training time and strengthen security analyst expertise.

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VinBrain is harnessing Microsoft’s cutting-edge AI technologies to transform healthcare in Vietnam.
Bending the curve on innovation across industries with differentiated AI offerings

To make disaster response more efficient, nonprofit Team Rubicon is quickly identifying and engaging the right volunteers in the right locations with the help of Copilot for Dynamics 365. Netherlands-based TomTom is bringing the benefits of generative AI to the global automotive industry by developing an advanced AI-powered voice assistant to help drivers with tasks like navigation and temperature control. In Vietnam, VinBrain has developed one of the country’s first comprehensive AI-powered copilots to support medical professionals with enhanced screening and detection processes and encourage more meaningful doctor-patient interactions. Rockwell Automation is delivering industry-first capabilities with Azure OpenAI Service to accelerate time-to-market for customers building industrial automation systems. With a vision to democratize AI and reach millions of users, Perplexity.AI has brought its conversational answer engine to market in six months using Azure AI Studio. India’s biggest online fashion retailer, Myntra, is solving the open-ended search problem facing the industry by using generative AI to help shoppers figure out what they should wear based on occasion. In Japan, Aisin Corp has developed a generative AI app to empower people who are deaf or hard of hearing with tasks like navigation, communication and translation; and Canada-based startup Natural Reader is making education more accessible on-the-go for students with learning differences by improving AI voice quality with Azure AI. To solve one of the most complex engineering challenges — the design process for semiconductors — Synopsys is bringing in the power of generative AI to help engineering teams accelerate time-to-market.

As organizations continue to embrace AI Transformation, it is critical they develop clarity on how best to apply AI to meet their most pressing business needs. Microsoft is committed to helping our customers and partners accelerate pragmatic AI innovation and I am excited by the opportunities before us to enrich employee experiences, reinvent customer engagement, reshape business processes and bend the curve on innovation. As a technology partner of choice — from our differentiated copilot capabilities to our unparalleled partner ecosystem and unique co-innovation efforts with customers — we remain in service to your successful outcomes. We are also dedicated to preserving the trust we have built through our partnership approach, responsible AI solutions and commitments to protecting your data, privacy and IP. We believe this era of AI innovation allows us to live truer to our mission than ever before, and I look forward to continuing on this journey with you to help you achieve more.

The post Embracing AI Transformation: How customers and partners are driving pragmatic innovation to achieve business outcomes with the Microsoft Cloud appeared first on The Microsoft Cloud Blog.

I spoke with Shamim Mohammad, Chief Information and Technology Officer at CarMax, on the Pivotal podcast about his company’s approach to data and AI.

CarMax has applied AI to improve the experience for both customers and employees. For instance, it is using machine learning to provide the best images, reviews, and details for each car. It has built patented technologies to optimize that process, including a recommendation engine that can understand what the customer is trying to do and offer targeted car content.  

When customers look at a car, AI also helps aggregate information about the car from multiple data sets and turns it into easily digestible summaries for the shopper. ChatGPT working in the background to draft these summaries frees time for CarMax’s employees to work on higher-value projects. 

CarMax was one of the early adopters of Microsoft Azure OpenAI Service, and its success in scaling AI has a lot to do with how it organized itself to drive innovation across the company. Here are some highlights from my conversation with Shamim.

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Setting up cross-functional innovation teams

CarMax has set itself up like a digital startup, creating dozens of small, cross-functional innovation teams. Each team is focused on tackling a defined set of business challenges, and resourced with engineering, marketing, and operations talent. They are encouraged to move fast to build and test their solutions. 

Every few weeks, these teams present their progress and results at a product showcase. CarMax senior leaders watch these presentations, provide feedback, and decide which projects to scale. When a good idea is proved effective, teams are empowered to move their solutions to production with minimal bureaucracy. This allows them to quickly iterate and scale. 

When our teams have a good idea, they can optimize and scale it on their own, and then they present their progress on a biweekly basis, and we make a joint determination how and if to proceed further as a team. That’s how the teams work today at CarMax, which is amazing. I feel like I have this massively large company, but it’s still working like a startup.

Shamim Mohammad, Chief Information and Technology Officer, CarMax 

This cross-functional team structure would not have been possible without close leadership alignment. When Shamim first became Chief Information Officer, he partnered closely with the Chief Operating Officer and Chief Marketing Officer to organize these teams so that they could become digital-first. That collaboration has thrived to this day. 

Implementing strong AI governance 

CarMax has created a strong model for AI governance to support its innovation. It set up an AI Center of Excellence that includes top technical leaders, as well as leaders from legal, operations, finance, and marketing. 

This center’s chief role is to ensure that any innovation with AI remains consistent with the company’s core values of transparency and integrity. It focuses on educating CarMax teams about the power and risks of AI, provides guidelines on how to use AI responsibly, and offers tools to help teams evaluate their ideas and projects.  

The work of the AI Center of Excellence has created a culture of responsible innovation within CarMax, allowing teams to feel safe to experiment with AI.  

It starts with creating a culture that empowers employees to experiment and learn. And that’s supported by a strong data foundation. Because if a company is not good with data, they cannot be good with AI.

Shamim Mohammad, Chief Information and Technology Officer, CarMax

Building a foundational data estate for AI 

CarMax knew that the transformation it sought depended heavily on getting its data estate in order. Starting five years ago, the company invested to build a clean and organized data estate in the cloud. That has allowed it to combine the power of AI with its massive trove of car and customer data. 

It started by moving its data to Microsoft Azure. It worked to make that data scalable, updated, and constantly refreshed. It also applied strong data governance policies to ensure security and privacy. 

Today, that data is available for its teams to use. Its early data estate investment has positioned it to drive AI innovation at an incredible pace.  

Our teams have been leveraging our data and AI to create great customer experiences, drive competitive differentiation, and also make the lives of our associates better. 

Shamim Mohammad, Chief Information and Technology Officer, CarMax

Learn more about AI innovation on the Pivotal podcast 

CarMax is an exciting example of what an organization can accomplish if it makes some foundational changes to prime itself for AI innovation.  

By clearly defining achievable goals, providing teams with the environment to experiment and scale, and putting strong AI and data governance in place, it was able to unleash a wave of AI innovation that completely transformed its business. CarMax’s journey offers important lessons for organizations wanting to succeed with AI. 

If you want to hear more about CarMax’s approach, tune into the episode on the Pivotal podcast.

The post How CarMax organized and scaled innovation with Microsoft AI solutions appeared first on The Microsoft Cloud Blog.

The importance of data in AI-driven retail fuels the algorithms, insights, and personalized experiences that are increasingly integral to success of the modern retailer. The ability to collect, harmonize, and derive meaningful insights from vast amounts of data empowers retailers to make informed decisions, create personalized experiences, and stay competitive. Understanding that data is key to success, we’ve also released retail data solutions in Microsoft Fabric—helping retailers to standardize and enrich raw data with connectors to engage customers more effectively. Read on to learn how you and your employees can maximize benefits from your data.

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Optimize shopper experiences with personalization  

Generative AI models have vastly improved the experience of chatting with virtual assistants—providing expert advice and bringing ease and convenience to online shoppers. The copilot template for personalized shopping on Azure OpenAI Service (preview) enables retailers to build tailored shopping experiences that allow consumers to shop using natural language. Online shopping is now akin to consulting with a specialist in a store. Personalized shopping taps into the retailer’s vast expertise and knowledge base to apply across shopping situations with the convenience of anytime, anywhere availability. Using a retailer’s current systems and data, this prebuilt template can be embedded into existing experiences, such as a website or app, making it easier for shoppers to find and purchase the products they want. With the prebuilt copilot template, retailers can offer customers personalized expert advice as well as guide the shopper to find unexpected items and learn more about the retailer.  

The copilot template is designed to be easy for any retailer to use. Its open architecture lets each organization leverage existing investments in commerce, inventory, and personalization solutions to support a wide range of buying environments, including e-commerce sites and mobile apps. Designed to have interactive discussions with shoppers, the copilot template can be adapted to each seller’s brand and values, responds to their questions and facilitates decision-making to create a personalized experience that feels natural and easygoing. 

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Increase productivity and efficiency with copilot for store operations   

Whether associates are long-term employees or seasonal workers, empowering the workforce and optimizing their performance is critical to customer satisfaction and retailer success. With the new generative AI-powered copilot template for store operations on Azure OpenAI Service (preview), retailers can build technology that allows frontline workers to quickly and easily access the information needed for their work day, increasing productivity and efficiency with text and voice commands.  

Retail frontline workers can easily get answers to questions on store operating procedures like how to handle refunds or set up product displays. Using natural language, associates can ask questions about the product catalog to support shoppers, review HR policies and benefits, or complete surveys. Copilot template for store operations enables workers to independently manage issues such as addressing damaged items. For example, with a few prompts, an associate can ask copilot template for store operations for the company’s standard operating procedure for replacing damaged products. In addition to getting the right steps to handle the process, the associate can also create a task to replace products and send an alert through Microsoft Teams to the store manager. Copilot template for store operations eliminates the need for pen and paper, data in multiple systems, or the retail frontline tracking down the store manager for every problem that arises.  

Likewise, the copilot template for store operations helps store managers optimize the work experience for their associates and deliver improved customer experiences. They can ask Microsoft Teams for a summary of key performance indicators (KPIs)—such as sales, inventory, and customer feedback. Using copilot template for store operations, a manager can quickly create tasks and assign associates to address. Copilot template for store operations provides retailers insights and information in the normal flow of work, helping managers and associates increase productivity and responsiveness.

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Gain actionable insights fast with retail data solutions in Microsoft Fabric

Microsoft Fabric is a complete analytics platform built for the era of AI. It enables the transformation of data into predictive insights, to ensure better business outcomes and reduce costly data replication and movement to support data analysts and data scientists. With these solutions in place, organizations can also automate duplicative tasks resulting in data efficiency and resource management.   The self-serve ability enables organizations to equip everyone in the company with their own access to these powerful analytics. Underscoring all of this is a commitment to help keep data secure and protected in a single source while meeting stringent compliance requirements.  

Retail data solutions in Microsoft Fabric is an industry specific workload that enables customers to accelerate time to insight generation by unifying, enriching, and modelling industry data on Microsoft Fabric​. Organizations can plan, architect, and design data solutions for data governance, reporting, business intelligence, and advanced analytics. Using data definition, formats, and storage enhancement, a standardized data model is created to help organizations derive actionable insights from large volumes of retailer data. Retail data solutions in Microsoft Fabric provide seamless integration across different systems and applications. By establishing a foundation for naming, data classification, and access controls, retailers can be assured effective governance of their data. 

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Sitecore OrderCloud connector enhances your digital capabilities 

Sitecore OrderCloud connector, one of the key capabilities of retail data solutions, gives you a quick and reliable platform to get commerce data onto Microsoft retail industry standard schema. The connector performs transformation and orchestration on top of the data from Sitecore OrderCloud to align with the data model. The connector works across three key data sets:   

1. Products: All the sellable products available in Sitecore OrderCloud. 
2. Customers: End customers who are shopping from your e-commerce portals. 
3. Orders: Customer generated online sales orders.  

The key role of the connector is to get data into the retail data solutions schema, giving users the benefit of access to solutions that are built on top of retail data solutions. Microsoft Power BI reports on sales, products, and customer data solutions can be enabled on top of Sitecore OrderCloud data out of box. 

Using the connector in combination with Microsoft Power Platform and Dataverse capabilities empowers customers to seamlessly connect data across multiple line-of-business systems to generate AI-driven recommendations and actionable solutions that will help store associates make the right decisions. The connector ensures that no personal customer information is transferred when using Dataverse and Microsoft Power Platform capabilities such as Power BI reports and other related solutions. The Power BI reports provide actionable insights on top of data. Each report provides a specific view of data across sales, customers, and products that can help make impactful merchandising, marketing, and supply chain decisions.  

“Sitecore OrderCloud delivers limitless commerce capabilities and opportunities to consolidate commerce channels into a single managed marketplace. The out-of-the-box integration with Microsoft Fabric unlocks the ability to be a forward-looking AI retail organization. Retail organizations can benefit from stateful services, reliable messaging, orchestration, monitoring, and security, while continuing to focus on their roadmap and strategic business objectives.” Steven Davis, Vice President of Engineering Commerce, Sitecore 

Make strategic product decisions with frequently bought together

Lastly with this release, the frequently bought together model is a data-driven tool that empowers retailers to make informed decisions about product placement and promotions. By analyzing point-of-sale (POS) data, frequently bought together identifies the combinations of products that are most often selected and purchased at the same time. This way, retailers can effectively promote cross-selling activity and boost joint sales by placing associated products closer together.  

Frequently bought together analytics enables retailers to: 

• Find the top revenue products and boost cross-sales by putting identified products closer. 
• Check the lowest revenue products and decide which ones to drop from the product catalogue. 
• Measure how past marketing actions, like new shelf layout or promotion performance, affected the sales of each item in a product group by comparing before and after sales revenues when purchased together. 

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MICROSOFT INTRODUCES PREBUILT AI SOLUTIONS FOR RETAILERSRead the blog 

• Join us at NRF 2024 from January 13 to 16, 2024 in New York City, New York to learn more about Microsoft Cloud for Retail’s cutting-edge AI technologies and how they can optimize your business.
• Join Shelley Bransten at the Microsoft Retail Digital Forum on February 6, 2024 for the How AI Unlocks Value for Retail session to learn about the research and gain insights into what is driving AI transformation among leading retailers.
• To get started, you can sign up here or learn more about our latest capabilities on the Microsoft Cloud for Retail homepage. 

The post Microsoft Cloud for Retail unlocks a new level of productivity with AI appeared first on The Microsoft Cloud Blog.