In a world where technology evolves at breakneck speed, it’s astonishing to realize that many businesses still rely on systems built decades ago. Imagine this: 220 billion lines of COBOL code are still running in production today, powering critical operations in industries ranging from finance to government. These systems, often maintained by developers who are now in retirement homes, underscore a stark reality—our modern economy is deeply intertwined with aged technology. This reliance on legacy systems poses significant risks and challenges, yet it also highlights the resilience and longevity of COBOL. As we forge ahead into the future, the question remains: how long can we sustain this dependence on the past?  

Innovations like generative AI are quickly becoming the baseline for how organizations differentiate. From companies like the Volvo Group using Microsoft Azure AI and Microsoft Azure AI Document Intelligence to streamline their invoice and claims process (saving Volvo employees about 850 hours a month) to Medigold Health using Azure OpenAI Service to automate administrative tasks for clinicians giving them time to focus on patient care.

Organizations are sensing that if they don’t truly transform, they risk being left behind and missing the AI wave. “AI is redefining work and it’s clear we need new playbooks,” said Ryan Roslansky, CEO of LinkedIn. “It’s the leaders who build for agility instead of stability and invest in skill building internally that will give their organizations a competitive advantage and create more efficient, engaged, and equitable teams.”

Innovation requires transformation and modernization of your business across people, process, and technology

Setting a strong cloud foundation is paramount for organizations striving to achieve superior differentiation. However, migrating to the cloud isn’t the end point, it is merely the starting point and a pathway to further improvements. Continuous cloud migration and modernization make it significantly easier for organizations to deliver successful transformation initiatives and be future-ready.

In fact a 2024 Forrester study states that, “Organizations must increasingly adopt a mindset of continuous modernization to keep pace with shifting customer expectations, drive innovation, and fuel profitable growth. Just moving to the cloud is not enough: Modernization, incorporating advances like generative AI (GenAI), is playing a critical role in driving competitive advantage.”¹

Continuous modernization is an ongoing process that features a clear technology strategy built around innovation and employee training, integrated key metrics tied to business outcomes, and upgrades to your technology stack powered by the right strategic partnerships.

But there are challenges and requirements standing in the way of continuous modernization

Many businesses recognize the need to take this sort of approach to modernization: according to a 2023 Forrester survey, 89% of decision-makers said their firm plans to increase or at least maintain their current application modernization investments over the next year to achieve key business priorities and address modernization gaps. However, only one in five respondents said their firm has already begun to overcome foundational barriers in its application modernization journey to bring critical value back to the business.

Why? For one, many legacy systems can’t support the requirements of modern tech like AI-powered applications, leading to excessive manual processes and clunky stopgap measures. In fact, 53% of business decision makers (BDMs) say that operations are simply too slow at their firms to take the next step in their application modernization journey according to the Forrester survey.

Once organizations get to the implementation phase of modernization, 48% of survey respondents say that they lack required IT skills, which can make it difficult to to plan and execute holistic modernization, and they also have a hard time filling employee tech skill gaps.

So how can businesses best position themselves to mitigate these challenges and achieve modernization success? Earlier, I mentioned that continuous modernization is an ongoing process that features a clear technology strategy built around innovation and employee training, integrated key metrics tied to business outcomes, and upgrades to your technology stack powered by the right strategic partnerships.

How to think about modernization

Modernizing applications is a transformative journey that requires careful planning and strategic decision-making to balance immediate operational needs with long-term goals.

Organizations must begin by thoroughly assessing their current technical landscape, business objectives, industry trends, and internal capabilities before selecting the most appropriate modernization path—whether that’s using managed platform as a service (PaaS) services for maximum cloud benefits, containerizing applications with Azure Kubernetes Services, reimagining applications as cloud-native services, or using Azure’s hybrid capabilities to evolve at your own pace. The right approach depends on your specific circumstances and constraints, with options ranging from incremental improvements for established systems to comprehensive application refactoring for organizations seeking full cloud advantages.

Ultimately, a well-executed Azure modernization strategy does more than just update technology, it liberates IT teams from routine maintenance tasks, allowing them to focus on innovative initiatives that drive competitive advantage and business growth in an increasingly digital marketplace.

Azure can support your continuous modernization process at each step along the journey

We understand that navigating any transformation project can be daunting, but Azure helps companies modernize every day by offering comprehensive guidance, expert help, cost-saving strategies and tools, and more. Embracing Azure’s managed app and data PaaS lets you automate manual tasks and streamline and standardize development processes—empowering your developers and IT teams to be more productive and focused on innovative solutions for your customers.

Understanding the state of your IT estate

Any cloud migration and modernization project starts with getting a consolidated view of app, data, and infrastructure to understand your IT estate.

This can be a daunting first step, with applications siloed in different parts of your organization that are hard to understand together. Through our Solution Assessment Program, we provide a robust set of resources that enable you to run a comprehensive assessment of your IT estate. By streamlining your first steps, you can focus on creating a cohesive strategy and commencing your modernization projects.

Use outcome-aligned technical skilling to help your employees operate with new paradigms

By equipping teams with the right skills, businesses can unlock the full potential of modernized applications, ensuring successful transformations that drive measurable business outcomes. Azure offers extensive skilling workshops and tools for IT pros, developers, technical managers, and others that teach employees at every level of your organization how new technologies impact them and their work.

These role- and scenario-based trainings are easy to use for busy IT and developer teams and allow them to quickly understand and use their new tools to build AI-powered modernized apps. Skilling can be the difference between transformative, modernized applications and partially implemented, ineffective initiatives.

Working with Azure to modernize means factors that often lead to success are built into the process, allowing you and your team to focus on innovating.

“I think it has been a very well-rounded partnership. We’ve learned how to work in lockstep and be productive as we work together,” says Sahil Gupta, NBA Senior Vice President and Head of Application Development. “We’ve learned how to better utilize Microsoft Cloud and the resources and data systems that exist at Microsoft. We are committed to staying current with innovative technology like Web 3.0 and metaverse—bringing that knowledge into the NBA has been paramount.”

Wherever you are on your digital transformation journey, we want to help you take the next step

Whether you’ve already begun your cloud journey or are planning to commence soon, Azure can help you actualize your transformation vision regardless of your cloud approach—whether hybrid, single, or multi-cloud.

Microsoft has a robust partner ecosystem of Azure specialized partners that support organizations in their continuous modernization efforts.

Modernize for AI Innovation

Accelerate app and data estate readiness for AI Innovation with Microsoft Azure.

Learn more

¹ “Checklist: Steps To Operationalize AI Innovation Through Application Modernization,” Forrester, June 2024

The post Accelerate AI innovation and business transformation: Scaling AI transformation with strategic cloud partnership appeared first on The Microsoft Cloud Blog.

One of the highlights of my career has always been connecting with customers and partners across industries to learn how they are using technology to drive their businesses forward. In the past 30 years, we’ve seen four major platform shifts, from client server to internet and the web to mobile and cloud to now—the next major platform shift to AI.

As today’s platform shift to AI continues to gain m omentum, Microsoft is working to understand just how organizations can drive lasting business value. We recently commissioned a study with IDC, The Business Opportunity of AI, to uncover new insights around business value and help guide organizations on their journey of AI transformation. The study found that for every $1 organizations invest in generative AI, they’re realizing an average of 3.7x return—and uncovered insights about the future potential of AI to reshape business processes and drive change across industries. 

Today, more than 85% of the Fortune 500 are using Microsoft AI solutions to shape their future. In working with organizations large and small, across every industry and geography, we’ve seen that most transformation initiatives are designed to achieve one of four business outcomes:

1. Enriching employee experiences: Using AI to streamline or automate repetitive, mundane tasks can allow your employees to dive into more complex, creative, and ultimately more valuable work.
2. Reinventing customer engagement: AI can create more personalized, tailored customer experiences, delighting your target audiences while lightening the load for employees.
3. Reshaping business processes: Virtually any business process can be reimagined with AI, from marketing to supply chain operations to finance, and AI is even allowing organizations to go beyond process optimization and discover exciting new growth opportunities.
4. Bending the curve on innovation: AI is revolutionizing innovation by speeding up creative processes and product development, reducing the time to market and allowing companies to differentiate in an often crowded field.

In this blog, we’ve collected more than 200 of our favorite real-life examples of how organizations are embracing Microsoft’s proven AI capabilities to drive impact and shape today’s platform shift to AI. We hope you find an example or two that can inspire your own transformation journey.

IDC InfoBrief: sponsored by Microsoft, 2024 Business Opportunity of AI, IDC# US52699124, November 2024 

Enriching employee experiences

Generative AI is truly transforming employee productivity and well-being. Our customers tell us that by automating repetitive, mundane tasks, employees are freed up to dive into more complex and creative work. This shift not only makes the work environment more stimulating but also boosts job satisfaction. It sparks innovation, provides actionable insights for better decision-making, and supports personalized training and development opportunities, all contributing to a better work-life balance. Customers around the world have reported significant improvements in employee productivity with these AI solutions:

1. Access Holdings Plc adopted Microsoft 365 Copilot, integrating generative AI into daily tools and, as a result, writing code now takes two hours instead of eight, chatbots launch in 10 days instead of three months, and presentations are prepared in 45 minutes instead of six hours.
2. Adobe is connecting Adobe Experience Cloud workflows and insights with Microsoft 365 Copilot to deliver generative AI-powered capabilities that enable marketers to increase collaboration, efficiency, and creativity.
3. Amadeus empowers its teams to focus their time and skills on value-added tasks with Microsoft 365 Copilot by summarizing email threads, chat, or transcripts, and summing up information from diverse sources.
4. ANZ has invested in Microsoft 365 Copilot, GitHub Copilot, and Copilot in Microsoft Edge to boost productivity and innovation across its workforce. 
5. Asahi Europe & International (AEI) has adopted Microsoft 365 Copilot, saving employees potentially 15% of time previously spent on administrative tasks.
6. AXA developed AXA Secure GPT, a platform powered by Azure OpenAI Service that empowers employees to leverage the power of generative AI while targeting the highest level of data safety and responsible use of the tool.
7. Axon Enterprise developed a new AI tool with Azure OpenAI Service called Draft One, resulting in an 82% decrease in time spent on reports, which freed up officers to engage more with their community.
8. Aztec Group enhanced productivity and client experience by trialing Microsoft 365 Copilot with 300 staff, uncovering “unlimited” use cases and plans for a wider rollout.
9. Bader Sultan & Bros. Co. W.L.L implemented Microsoft 365 Copilot to enhance employee productivity and speed up customer response times.
10. Bancolombia is using GitHub Copilot to empower its technical team, achieving a 30% increase in code generation, boosting automated application changes to an average of 18,000 per year, with a rate of 42 productive daily deployments. 
11. BaptistCare Community Services is using Microsoft 365 Copilot to save employees time as they navigate workforce shortage challenges allowing them to focus more on the people they care for.
12. Barnsley Council was recognized as “Double Council of the Year in 2023” for its implementation of Microsoft 365 Copilot, which modernized operations and reduced administrative tasks, leading to improved job satisfaction and increased creativity.
13. BlackRock purchased more than 24,000 Microsoft 365 Copilot licenses spanning all employees, functions, and locations, helping improve the Copilot experience, including co-developing new features and functions.
14. British Heart Foundation is testing Microsoft 365 Copilot and in its initial test, users estimate that Microsoft 365 Copilot could save them up to 30 minutes per day.
15. Buckinghamshire Council deployed Microsoft 365 Copilot with staff reporting productivity improvements, quality enhancements, and time savings which are enabling the different teams to do more with less. 
16. Campari Group adopted Microsoft 365 Copilot to help employees integrate it into their workflow, resulting in time savings of about two hours a week from the support of routine activities such as email management, meeting preparation, content creation, and skill acquisition.
17. Capita is using GitHub Copilot for productivity improvements as well as improvements in developer satisfaction, recruitment, and retention.
18. CDW used Microsoft 365 Copilot to improve work quality for 88% of users, enabling 77% to complete tasks faster, and increasing productivity for 85% of users.
19. Chi Mei Medical Center is lightening workloads for doctors, nurses, and pharmacists with a generative AI assistant built on Azure OpenAI Service. 
20. E.ON is focused on Germany’s energy transition, leveraging Microsoft 365 Copilot to manage the complex grid in real-time, increasing productivity and efficiency for its workforce.
21. Enerijisa Üretim has adopted Microsoft 365 Copilot to streamline meeting summaries, reformat documents, and compile reports, enabling employees to concentrate on more strategic and fulfilling activities instead of spending six hours in meetings.
22. EPAM is deploying Microsoft 365 Copilot to consolidate information and generate content and documents. 
23. Farm Credit Canada implemented Microsoft 365 Copilot which resulted in time savings on routine tasks for 78% of users, with 30% saving 30 to 60 minutes per week and 35% saving over an hour per week, allowing employees to focus on more value-added tasks.
24. Finastra used Microsoft 365 Copilot to automate tasks, enhance content creation, improve analytics, and personalize customer interactions, with employees citing a 20% to 50% time savings.
25. Four Agency Worldwide increased employee productivity using Microsoft 365 Copilot to generate ideas for creative work and support administrative-heavy processes, data analysis, and report generation, allowing staff to focus on outreach and less time doing paperwork.
26. Goodwill of Orange County developed an AI-powered app using Azure AI capabilities to help more people, including those with developmental, intellectual, and physical disabilities, work in unfilled e-commerce positions.
27. Honeywell employees are saving 92 minutes per week—that’s 74 hours a year! Disclaimer: Statistics are from an internal Honeywell survey of 5,000 employees where 611 employees responded.
28. Insight employees using Copilot are seeing four hours of productivity gained per week from data summarization and content creation.
29. Joos uses Microsoft 365 Copilot to grow its brand with worldwide collaboration by streamlining meetings, optimizing presentations, and improving communications.
30. Kantar is harnessing the power of Microsoft 365 Copilot by reducing costly, time-consuming IT processes and boosting productivity for employees.
31. KPMG Australia is using Microsoft Azure OpenAI Service, Azure AI Search, and Microsoft 365 Copilot to perform advanced text analysis of dozens of client source documents to identify full or partial compliance, or noncompliance, in a fraction of the time required for manual assessments.
32. LGT is launching Microsoft Copilot LGT to improve efficiency, showing users save an average of an hour a week even in the pilot phase. 
33. Lotte Hotels & Resorts has been creating a new work culture that allows employees to work more efficiently and focus on the nature of the work by adopting Microsoft Power Platform for automation.
34. MAIRE is leveraging Microsoft 365 Copilot to automate routine tasks, saving more than 800 working hours per month, freeing up engineers and professionals for strategic activities while supporting MAIRE’s green energy transition by reducing their carbon footprint.
35. McDonald’s China chose Microsoft Azure AI, GitHub Copilot, and Azure AI Search to transform its operations, resulting in a significant increase in AI adoption, consumption, and retention from 2,000 to 30,000 employee transactions monthly.
36. McKnight Foundation adopted Microsoft 365 Copilot for all staff, saving time, increasing productivity, and freeing space to focus on strategic priorities.
37. Morula Health is using Microsoft 365 Copilot to enhance productivity, streamline medical writing tasks, and ensure data security, ultimately improving efficiency and client satisfaction. 
38. Motor Oil Group is achieving remarkable efficiency gains by integrating Microsoft 365 Copilot into its workflows, with staff spending minutes on tasks that used to take weeks. 
39. Nagel-Group uses Azure OpenAI Service to help employees quickly access information which saves time, creates efficiency and transparency, and leads to higher-quality answers overall.
40. National Australia Bank is leveraging Microsoft 365 Copilot for daily productivity and data analysis and insights and Microsoft Security Copilot to quickly analyze millions of security event logs and allow engineers to focus on more important areas.
41. NFL Players Association integrated Azure AI Services and Azure App Service into their video review process, reducing review time by up to 73%, significantly increasing efficiency and enhancing player safety through consistent rule enforcement.
42. O2 Czech Republic boosts productivity and streamlines meetings with Microsoft 365 Copilot, revolutionizing how information is shared and making automation a part of daily work.
43. Onepoint developed a secure conversational agent based on Azure OpenAI Service, which delivers productivity gains of between 10% and 15% across all business lines.
44. Orange Group has more than 40 use cases with Azure OpenAI Service and GitHub Copilot across business functions to support employees in their day-to-day tasks, enabling them to concentrate on higher value-added activities.
45. Oxford University Hospitals NHS Foundation Trust implemented Microsoft 365 Copilot to improve staff report productivity by saving one to two hours a week, or simple formatting tasks down to a matter of seconds, enabling more resources to deliver frontline services.
46. PA Consulting transformed its sales operations with Microsoft 365 Copilot, so its people can invest more time on the activities that have the biggest impact for clients and maximize the strategic value they provide. 
47. Petrobras used Azure OpenAI Service to create ChatPetrobras, which is streamlining workflows, reducing manual tasks, and summarizing reports for its 110,000 employees.
48. Petrochemical Industries Company automates work processes to save time with Microsoft 365 Copilot from weeks to days, hours to seconds.
49. PKSHA Technology is optimizing their time on critical work by increasing efficiency in meeting preparations, data analytics, and ideation with the help of Microsoft 365 Copilot.
50. Providence has collaborated with Nuance and Microsoft to accelerate development and adoption of generative AI-powered applications, helping improve care quality and access, and reduce physician’s administrative workloads. 
51. RTI International adopted Microsoft 365 Copilot to gain productivity wherever possible, allowing staff to focus on their areas of expertise, delivering even better science-backed solutions for clients.
52. Sandvik Coromant is using Microsoft 365 Copilot for Sales to drive efficiency and accuracy, shaving at least one minute off each transaction, allowing sellers and account managers to focus their expertise on responding to customers’ needs with analysis, creativity, and adaptability.
53. Sasfin Bank built a solution on Microsoft Azure that centralized 20,000 documents to analyze contract clauses and provide real-time snapshots, moving guesswork into data-driven decision-making.
54. Scottish Water implemented Microsoft 365 Copilot reducing mundane tasks to a minimum, and thus freeing up time for employees to work on the more meaningful tasks.
55. Shriners Children’s developed an AI platform allowing clinicians to easily and securely navigate patient data in a singular location, enhancing patient care, and improving the efficiency of their healthcare services. 
56. Siemens is leveraging Azure OpenAI Service to improve efficiency, cut downtime, and address labor shortages.
57. Softchoice employees are experiencing firsthand how Microsoft 365 Copilot can transform daily workflows, realizing productivity gains of 97% reduction in time spent summarizing technical meetings and up to 70% less time spent on content creation.
58. Syensqo utilized Azure OpenAI Service to develop a custom AI chatbot in three months, which improved their internal data management, decision-making, and overall efficiency.
59. Teladoc Health uses Microsoft 365 Copilot to revolutionize its telehealth operations, automating routine tasks, boosting efficiency, and increasing productivity.
60. Telstra developed two cutting-edge generative AI tools based on Azure OpenAI Service: 90% of employees are using the One Sentence Summary tool which resulted in 20% less follow-up customer contact and 84% of customer service agents using the Ask Telstra solution.
61. Topsoe achieved 85% AI adoption among office employees in seven months, significantly enhancing productivity and business processes.
62. Torfaen County Borough Council utilized Microsoft 365 Copilot to streamline back-office processes, resulting in significant time savings and enhanced productivity for both business and children’s services teams, with further rollouts planned.
63. Trace3 leveraged Microsoft 365 Copilot to streamline and enhance processes across the business and with clients, such as reducing the time it takes human resources (HR) recruiting managers to respond to applicants within a couple of days instead of several weeks.
64. Unilever is reinventing their marketing process with Copilot, saving time on briefing tasks, automatically pulling in relevant market data, content and insights to accelerate campaign launches. 
65. Uniper SE implemented Microsoft 365 Copilot to reduce time spent on manual and repetitive tasks, and help workers focus on more pressing work, such as developing enhanced solutions to speed up the energy transition.
66. Unum Group built a custom AI application to search 1.3 terabytes of data with 95% accuracy using Azure OpenAI Service. 
67. Virgin Atlantic adopted Microsoft 365 Copilot and GitHub Copilot and is seeing real business benefits, including productivity improvements, enabling new ways of working.
68. Visier built a generative AI assistant that leverages Azure AI and Azure OpenAI Services to deliver workforce analytics and actionable insights for more than 50,000 customers.
69. Virtual Dental Care developed an AI application Smart Scan that leverages Azure to reduce paperwork for mobile dental clinics in schools by 75% and frees dentists to devote more time to patient care.
70. Zakladni Skola As Hlavkova adopted Microsoft 365 Copilot and saw a 60% improvement in handling administrative documents, decreased lesson preparation from hours to few minutes, increased inclusivity, and enhanced communication with students and parents.

Reinventing customer engagement

We’ve seen great examples of how generative AI can automate content creation, ensuring there’s fresh and engaging materials ready to go. It personalizes customer experiences by crunching the numbers and boosting conversion rates. It makes operations smoother, helping teams launch campaigns faster. Plus, it drives innovation, crafting experiences that delight customers while lightening the load for staff. Embracing generative AI is key for organizations wanting to reinvent customer engagements, stay ahead of the game, and drive both innovation and efficiency.

71. Absa has adopted Microsoft Copilot to streamline various business processes, saving several hours on administrative tasks each day.
72. Adobe leverages Azure to streamline the customer experience, harnessing the power of the connected cloud services and creating a synergy that drives AI transformation across industries.
73. Acentra Health developed Medscribe, a web application that uses Azure OpenAI Service to generate draft letters in a secure, HIPAA-compliant enclave that responds to customer appeals for healthcare services within 24 hours, reducing the time spent on each appeal letter by 50%.
74. Alaska Airlines is using Azure, Microsoft Defender, and GitHub to ensure its passengers have a seamless journey from ticket purchase to baggage pickup and started leveraging Azure OpenAI Service to unlock more business value for its customer care and contact centers.
75. Ally Financial is using Azure OpenAI Service to reduce manual tasks for its customer service associates, freeing up time for them to engage with customers. 
76. BMW Group optimizes the customer experience connecting 13 million active users to their vehicles with the MyBMW app on Azure, which supports 450 million daily requests and 3.2 terabyte (TB) data processing.
77. Boyner has tripled its e-commerce performance using Azure, seeing a rise in customer satisfaction, engagement, conversion rate, and revenue.
78. Bradesco Bank integrated Azure to its virtual assistant, BIA, resulting in reduced response time from days to hours, improving operational efficiency and client satisfaction.
79. Capgemini Mexico integrated GitHub Copilot to support scalable AI implementations which has led to improved customer experiences and increased efficiency.
80. Capitec Bank uses Azure OpenAI Service and Microsoft 365 Copilot, enabling their AI-powered chatbot to assist customer service consultants in accessing product information more efficiently, saving significant time for employees each week.
81. Cdiscount is leveraging GitHub Copilot and Azure OpenAI Service to enhance developer efficiency, optimize product sheet categorization, and improve customer satisfaction.
82. Cemex used Azure OpenAI Service to launch Technical Xpert, an AI tool used by sales agents to provide instant access to comprehensive product and customer solution information, significantly reducing search time by 80%. 
83. Chanel elevated their client experience and improved employee efficiency by leveraging Microsoft Fabric and Azure OpenAI Service for real-time translations and quality monitoring.
84. City of Burlington created two AI-powered solutions: MyFiles system using Microsoft Power Platform for building permits, and CoBy, an around-the-clock customer support assistant using Microsoft Copilot Studio.
85. City of Madrid created an AI virtual assistant with Azure OpenAI Service offering tourists accurate, real-time information and personalized responses in more than 95 languages.
86. Cognizant is making performance management more effective and meaningful with Azure Machine Learning to help clients across industries envision, build, and run innovative digital enterprises.
87. Coles Group has leveraged Azure to enhance its digital presence and improve customer engagement, rolling out new applications to its stores six times faster without disrupting workloads.
88. Commercial Bank of Dubai used Azure to upgrade its application infrastructure, improving transaction security and speed so individual customers can now open an account and start banking in about two minutes.
89. Dubai Electricity and Water Authority has significantly improved productivity and customer satisfaction by integrating multiple Microsoft AI solutions, reducing task completion time from days to hours and achieving a 98% customer happiness rate.
90. Elcome uses Microsoft 365 Copilot to improve the customer experience, reducing response times from 24 hours to eight hours.
91. elunic developed shopfloor.GPT based on Azure OpenAI Service, leading to increased productivity for customers, saving 15 minutes per request.
92. Estée Lauder Companies is leveraging Azure OpenAI Service to create closer consumer connections and increase speed to market with local relevancy.
93. First National Bank (FNB) is using Microsoft 365 Copilot for Sales to help bankers create professional, thoughtful emails in 13 native South African languages to enhance customer interactions, streamline communications, and reinforce its commitment to innovation and customer service. 
94. Flora Food Group migrated to Microsoft Fabric to offer more detailed and timely insights to its customers, enhancing service delivery and customer satisfaction.
95. Groupama deployed a virtual assistant using Azure OpenAI Service that delivers reliable, verified and verifiable information, and boasts an 80% success rate.
96. International University of Applied Sciences (IU) adopted Azure OpenAI Service to revolutionize learning with a personalized study assistant that can interact with each student just like a human would.
97. Investec is using Microsoft 365 Copilot for Sales to enhance the bank’s client relationships, estimating saving approximately 200 hours annually ultimately boosting sales productivity and delivering personalized, seamless customer experience. 
98. Linum is using Azure to train their text-to-video models faster and more efficiently without losing performance or wasting resources.
99. Lumen Technologies is redefining customer success and sales processes through the strategic use of Microsoft 365 Copilot, enhancing productivity, sales, and customer service in the global communications sector.
100. McKinsey & Company is creating an agent to reduce client onboarding process by reducing lead time by 90% and administrative work by 30%.
101. Meesho leveraged Azure OpenAI Service and GitHub Copilot to enhance customer service and software development, resulting in a 25% increase in customer satisfaction scores and 40% more traffic on customer service queries.
102. Milpark Education integrated Microsoft Copilot and Copilot Studio and in just four months, improved efficiency and accuracy of student support, decreasing the average resolution time by 50% and escalations by more than 30%.
103. NC Fusion chose a comprehensive Microsoft solution to make marketing engagement activities easier and accurately target the best audience segments.
104. Medgate, a telehealth subsidiary of Otto Group, developed a medical Copilot powered by Azure OpenAI Service that summarizes consultations, supports triage, and provides real-time translations. 
105. Pacific Gas & Electric built a chatbot using Microsoft Copilot Studio that saves $1.1 million annually on helpdesk support. 
106. Pockyt is using GitHub Copilot and anticipates a 500% increase in productivity in the medium to long term as they continue adapting AI and fine-tuning their software development life cycle.
107. South Australia Department for Education launched an AI-powered educational chatbot to help safeguard students from harmful content while introducing responsible AI to the classrooms.
108. Sync Labs is using Azure to create AI-powered solutions that have led to a remarkable 30x increase in revenue and a 100x expansion of their customer base.
109. Syndigo is using Azure to accelerate digital commerce for its customers by more than 40% and expand its customer base.
110. Telkomsel created a virtual assistant with Azure OpenAI Service, resulting in a leap in customer self-service interactions from 19% to 45%, and call volume dropped from 8,000 calls to 1,000 calls a day.
111. Torrens University chose to use Azure OpenAI to uplift its online learning experience, saving 20,000 hours and $2.4 million in time and resources.
112. Trusting Social integrated Azure services to launch AI-driven agents that are changing how banks function and transforming their customer’s banking experience.
113. University of California, Berkeley used Azure OpenAI Service to deploy a custom AI chatbot that supports student learning and help students with complex coursework.
114. University of Sydney created a self-serve AI platform powered by Azure OpenAI Service, to enable faculty to build custom chatbots for enhancing student onboarding, feedback, career simulation, and more.
115. Van Lanschot Kempen is using Microsoft 365 Copilot to reduce the time needed for daily tasks, freeing up time to invest in that crucial personal connection.
116. Virgin Money built an award-winning virtual assistant using Copilot Studio to help build customers’ confidence in their digital products and services.
117. VOCALLS automates over 50 million interactions per year, resulting in a 78% reduction in average handling time aside from a 120% increase in answered calls.
118. Vodafone Group is leveraging Microsoft’s AI solutions, including Azure AI Studio, OpenAI Service, Copilot, and AI Search, to achieve a 70% resolution rate for customer inquiries through digital channels and reduce call times by at least one minute.
119. Walmart is using Azure OpenAI Service to deliver a helpful and intuitive browsing experience for customers designed to serve up a curated list of the personalized items a shopper is looking for.
120. Weights & Biases created a platform which runs on Azure that allows developers to keep records, log successes and failures, and automate manual tasks.
121. World2Meet is providing better customer service and operations with a new virtual assistant powered by Azure.
122. Xavier College is modernizing its student information systems on Microsoft Dynamics 365 and Azure to unlock powerful insights, fostering innovation and data-driven decision making.
123. Zavarovalnica Triglav implemented Dynamics 365 and Azure OpenAI Service to streamline its operations with automated responses and smart rerouting of customer enquiries.

Reshaping business processes

Transforming operations is another way generative AI is encouraging innovation and improving efficiency across various business functions. In marketing, it can create personalized content to truly engage different audiences. For supply chain management, it can predict market trends so companies can optimize their inventory levels. Human resources departments can speed up the hiring process, while financial services can use it for fraud detection and risk assessments. With generative AI, companies are not just refining their current processes, they’re also discovering exciting new growth opportunities.

124. Accelleron used Microsoft Power Platform to support numerous business applications and simplify processes for service agents and employees, resulting in the onboard of new agents in 30 minutes, compared to two days for other solutions.
125. Accenture developed an AI-powered financial advisor that leverages RISE with SAP on Azure to enhance their infrastructure and integrate financial data.
126. Atomicwork leverages Azure OpenAI to bring together three power capabilities: a conversational assistant, a modern service management system, and a workflow automation platform.
127. Blink Ops fully embraced generative AI to build the world’s first Security Automation Copilot with more than 8,000 automated workflows to help any Security/IT task through prompts.
128. Chalhoub Group is using Microsoft Fabric to modernize its data analytics and streamline its data sources into one platform, increasing agility, enhancing analytics, and accelerating processes.
129. Cineplex is developing innovative automation solutions for finance, guest services, and other departments, saving the company more than 30,000 hours a year in manual processing time.
130. ClearBank moved its services to Azure to gain scalability and efficiency, pushing out 183% more monthly system releases, gaining both scalability and efficiency.
131. Danske Statsbaner increases productivity up to 30% with help from Microsoft AI solutions.
132. Eastman implemented Microsoft Security Copilot realizing the benefits of accelerated upskilling, step-by-step guidance for response, and faster threat remediation.
133. Fast Shop migrated to Azure creating a self-service culture of access to data, eliminating delays, reducing costs, and increasing leadership satisfaction with data while providing more agility in reporting.
134. Florida Crystals adopted a value-added solution across Microsoft products including Microsoft 365 Copilot to reduce telecom expenses and automate industrial process controls.
135. GHD is reinventing the request for proposal (RFP) process in construction and engineering with Microsoft 365 Copilot.
136. GovDash is a software as a service (SaaS) platform that leverages AI to streamline the entire business development lifecycle for government contracting companies using Azure OpenAI Service.
137. Grupo Bimbo is deploying Microsoft’s industrial AI technologies to modernize its manufacturing processes, optimizing production and reducing downtime, driving significant cost savings, and empowering global innovation.
138. Insight Canada implemented Microsoft 365 Copilot to streamline business operations, realizing a 93% productivity gains in functions including sales, finance, and human resources.
139. Intesa Sanpaolo Group enhanced its cybersecurity with AI-enabled Microsoft Sentinel and Microsoft Security Copilot, resulting in faster threat detection, increased productivity, and reduced storage costs.
140. Kaya deployed a custom implementation of Dynamics 365 and Power BI to modernize its supply chain, leading to enhanced visibility, improved planning, and streamlined inter-department operations.
141. Lionbridge Technologies, LLC is using Azure and Azure OpenAI Service to accelerate its delivery times and improve quality, reducing project turnaround times by up to 30%.
142. LTIMindtree integrated Microsoft Security Copilot, offering automated incident response, integrated threat intelligence, and advanced threat analysis.
143. Mania de Churrasco used Azure, Microsoft Power Platform and Microsoft 365 to achieve high efficiency, security, and scalability in its operations, in addition to improving its data intelligence, which indirectly participated in a 20% increase in sales year on year.
144. National Bank of Greece built an Azure-powered Document AI solution to transform its document processing, improving the bank’s accuracy to 90%. 
145. Nest Bank has revolutionized its operations by integrating Microsoft 365 Copilot and Azure OpenAI Service, resulting in doubled sales and increased daily transactions from 60,000 to 80,000 showcasing the transformative impact of generative AI in the financial sector.
146. Network Rail modernized their data analytics solution with Azure, helping engineers understand data 50% faster than before and improve efficiency, passenger experiences, and safety—all while saving costs.
147. Nsure developed an AI-powered agent that uses Copilot Studio and Power Automate to reduce manual processing time by 60% while also reducing associated costs by 50%.
148. Oncoclínicas implemented Azure to transform its entire data ecosystem with a web portal and mobile application that performs all image processing and storage.
149. Pacífico Seguros has adopted Microsoft Security Copilot to optimize its security operations and anticipate and neutralize threats more efficiently and effectively.
150. Parexel adopted Azure Databricks and Power BI, achieving an 85% reduction in data engineering tooling costs, a 30% increase in staff efficiency, and a 70% reduction in time to market for data product delivery.
151. Paysafe used Microsoft 365 Copilot to streamline meetings, information management, and document creation, addressing language barriers, eliminating time-consuming tasks, and boosting creativity along the way.
152. Planted is integrating Azure OpenAI Service to manage everyday tasks more efficiently and facilitate the search for information for innovative process development.
153. Presidio realized dramatic productivity gains saving 1,200 hours per month on average for the employees using Microsoft 365 Copilot and created 70 new business opportunities.
154. Qatar Charity used Copilot Studio to increase its call center efficiency, reducing average handle time by 30%, increased customer satisfaction by 25%, and achieved a 40% reduction in IT maintenance costs.
155. Saphyre uses Azure and AI to provide an intelligent cloud-based solution that automates and streamlines financial trading workflows around client and counterparty life cycle management, reducing manual efforts by 75%. 
156. Swiss International Air Lines migrated and modernized with Azure, achieving up to 30% cost savings, a remarkable boost in platform stability along with enhanced security visibility.
157. ZEISS Group uses Microsoft Fabric to create a secure and trusted data supply chain that can be shared effortlessly across a range of business units.
158. ZF Group builds manufacturing efficiency with more than 25,000 apps and 37,000 unique active users on Microsoft Power Platform.

Bending the curve on innovation

Generative AI is revolutionizing innovation by speeding up creative processes and product development. It’s helping companies come up with new ideas, design prototypes, and iterate quickly, cutting down the time it takes to get to market. In the automotive industry, it’s designing more efficient vehicles, while in pharmaceuticals, it’s crafting new drug molecules, slashing years off research and development (R&D) times. In education, it transforms how students learn and achieve their goals. Here are more examples of how companies are embracing generative AI to shape the future of innovation.

159. Air India has incorporated Microsoft 365 Copilot into multiple departments, unlocking a new realm of operational insights that not only provides critical data on flight punctuality and operational hurdles, but also empowers proactive, collaborative decision making.
160. Agnostic Intelligence deployed Azure OpenAI Service to eliminate time-consuming tasks, saving users up to 80% of their time, and enabling IT managers to focus on innovation and quality assurance.
161. Albert Heijn is using Azure OpenAI Service for everything from customer personalization to demand forecast and food waste projects, making it easier for its customers to change their lifestyle.
162. Amgen is using Microsoft 365 Copilot to boost productivity and has the potential to speed up drug development and support advancements in their business processes.
163. APEC leverages Azure and deep neural network algorithms to develop an app that enables healthcare providers to capture retinal images, increasing the accuracy to identify Retinopathy of Prematurity (RoP) to 90%.
164. ASOS is using Azure AI Studio to help customers discover new looks with genuine shopping insights, personalized conversations, naturalism, and even humor to enliven the shopping journey.
165. Auburn University is incorporating Microsoft Copilot to promote AI literacy, accessibility, and collaboration, with the aim to expand educational and economic opportunities for its entire academic community with AI-centric tools.
166. B3 launched an AI assistant using Azure OpenAI Service that aids 10,000 users a day to answer Brazilians’ questions about how to start investing.
167. Basecamp Research aims to build the world’s largest database of national biodiversity and apply AI and machine learning to advance bioscience.
168. Bayer is using Microsoft Copilot to contribute to feeding a growing global population and helping people lead healthier, disease-free lives.
169. Brembo leveraged Azure OpenAI Service to develop ALCHEMIX, a solution to generate innovative compounds for its brake pads, drastically reducing the development time of new compounds from days to mere minutes.
170. Canary Speech can now train new vocal models in as little as two months and handle millions of transactions per month with Azure. 
171. CapitaLand simplified internal processes increasing efficiency to more than 10,000 man-days saved per year and deployed Azure OpenAI Service to build the first AI hospitality chatbot for its lodging business.
172. Cassidy is using Azure OpenAI Service to enhance efficiency across various industries, supporting more than 10,000 companies.
173. Coca-Cola is implementing Azure OpenAI Service to develop innovative generative AI use cases across various business functions, including testing how Microsoft 365 Copilot could help improve workplace productivity.
174. Denso is developing “human-like” robots using Azure OpenAI Service as the brain to help robots and humans work together through dialogue.
175. eFishery is using Azure OpenAI for farmers to get the data and insights on fish and shrimp farming, including more precise feeding and water quality monitoring.
176. EY developed an application that automatically matches and clears incoming payments in SAP, resulting in an increase from 30% to 80% in automatically cleared payments and 95% matched payments, with estimated annual time savings of 230,000 hours globally.
177. FIDO is using Azure OpenAI Service to develop an AI tool that uses sound to pinpoint leaky pipes, saving precious drinking water. 
178. Georgia Tech is using Azure OpenAI Service to enhance the electric vehicle (EV) charging infrastructure, achieving rapid data classification and predictive modeling, highlighting the reliability of networked chargers over non-networked ones.
179. GigXR developed a solution to create the intelligence for specific AI patients using Azure OpenAI Service and other Azure services.
180. GoTo Group is significantly enhancing productivity and code quality across its engineering teams by adopting GitHub Copilot, saving over seven hours per week and achieved a 30% code acceptance rate.
181. GovTech used Azure OpenAI Service to create LaunchPad, sparking more than 400 ideas and 20 prototypes, laying the foundation for the government to harness the power of generative AI.
182. H&R Block is using Azure AI Studio and Azure OpenAI Service to build a new solution that provides real-time, reliable tax filing assistance.
183. Haut.AI provides skin care companies and retailers with customizable, AI-based skin diagnostic tools developed with the help of Microsoft AI.
184. Helfie is building a solution that caters to healthcare providers who can arm their patients with an application to more quickly and accurately access the care they need.
185. Hitachi will implement Azure Open AI Service, Microsoft 365 Copilot, and GitHub Copilot to create innovative solutions for the energy, mobility, and other industries.
186. Icertis is providing AI-based tools that will recognize contract language and then build algorithms to automatically choose the right approach based on the content of the contract.
187. ITOCHU is using Azure OpenAI Service and Azure AI Studio to evolve its data analytics dashboard into a service that provides immediate recommendations by automatically creating evidence-based product proposals.
188. IU International University of Applied Sciences (IU) is using the power of Azure OpenAI Service to develop Syntea, an AI avatar integrated into Microsoft Teams and Microsoft 365 Copilot, making learning more personalized, autonomous, and flexible.
189. Khan Academy has partnered with Microsoft to bring time-saving and lesson-enhancing AI tools to millions of educators.
190. Lufthansa Group developed an animated 3D avatar called Digital Hangar to help guide passengers from initial travel inspiration to flight booking through an exchange with an avatar in natural language.
191. Mitsubishi Heavy Industries is using Azure OpenAI Service to help accelerate digital innovation in power plants.
192. Molslinjen has created an AI analytics toolbox that has reduced fuel emissions, improved customer satisfaction, and brought in millions of additional revenue.
193. Novo Nordisk recently published initial results with predictive AI models for advanced risk detection in cardiovascular diseases, including an algorithm that can predict patients’ cardiovascular risk better than the best clinical standards. 
194. Paige.AI​ is using AI and Azure to accelerate cancer diagnoses with data from millions of images.
195. Pets at Home created an agent to help its retail fraud detection team investigate suspicious transactions.  
196. Plan Heal is using Microsoft AI to create solutions that enable patients to monitor and report health metrics so care providers can better serve them.
197. Pacific Northwest National Laboratory (PNNL) is testing a new battery material that was found in a matter of weeks, not years, as part of a collaboration with Microsoft.
198. Rijksmuseum is harnessing the power of Copilot to make art accessible at scale by joining forces with Microsoft to improve and expand the art experience for blind and low-vision community members.
199. Royal National Institute of Blind People is using Azure AI Services to develop an AI-based solution that quickly and accurately converts letters to braille, audio, and large print formats.
200. Schneider Electric provides productivity-enhancing and energy efficiency solutions and is using a whole suite of AI tools to hasten its own innovation and that of its customers.
201. SPAR ICS created an award-winning, AI-enabled demand forecasting system achieving 90% inventory prediction accuracy.
202. Suzuki Motor Corporation is adopting Azure OpenAI Service for data security, driving company-wide use with five multipurpose apps.
203. Tecnológico de Monterrey created a generative AI-powered ecosystem built on Azure OpenAI Service with the goal to personalize education based on the students’ needs, improve the learning process, boost teachers’ creativity and save time on tedious tasks.
204. TomTom is using Azure OpenAI Service, Azure Cosmos DB, and Azure Kubernetes Service to revolutionize the driver experience.
205. Unilever is partnering with Microsoft to identify new digital capabilities to drive product innovation forward, from unlocking the secrets of our skin’s microbiome to reducing the carbon footprint of a multibillion-dollar business.
206. Unity used Azure OpenAI Service to build Muse Chat, an AI assistant that can guide creators through common questions and help troubleshoot issues to make game development easier.
207. University of South Florida is using Microsoft 365 Copilot to alleviate the burden of repetitive, time-consuming tasks so faculty and staff can spend this time creatively solving problems, conducting critical research, establishing stronger relationships with peers and students, and using their expertise to forge new, innovative paths. 
208. Visma has developed new code with GitHub Copilot, Azure DevOps, and Microsoft Visual Studio, as much as 50% faster, contributing to increased customer retention, faster time to market, and increased revenue.
209. Wallenius Wilhelmsen is implementing Microsoft 365 Copilot and using Microsoft Viva to drive sustainable adoption, streamlining processes, empowering better decision making, and cultivating a culture of innovation and inclusion.
210. Wipro is committed to delivering value to customers faster and improving the outcomes across the business by investing $1 billion in AI and training 200,000 employees on generative AI principles with Microsoft Copilot.

Next steps for AI transformation

Business Opportunity of AI

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As the technology continues to advance, new Microsoft AI agents unveiled over the past few weeks can help people every day with things like research, cybersecurity and more.

First things first: What is an AI agent? 

Imagine having a personal assistant that doesn’t just respond to commands but anticipates your needs, does complex tasks and keeps learning from every interaction — meaning it actually improves over time. 

AI agents analyze their environment, make decisions and take actions, tackling tasks with you or on your behalf based on your goals and guardrails. That means that instead of doing repetitive tasks, you can save time and focus on more creative and strategic work.

 Agents that use reasoning to help you do more 

Two new reasoning agents announced in late March for Microsoft 365 Copilot can help you be more productive in the office. Named Researcher and Analyst, both can securely analyze your work data — emails, meetings, files, chats and more — and the web to deliver highly skilled expertise on demand.

Researcher helps you tackle complex, multi-step research at work. It can build a detailed marketing strategy based on your work data and broader info from the web, identify opportunities for a new product based on emerging trends and internal data, or create a comprehensive quarterly report for a client review. It can also integrate data from external sources such as Salesforce, ServiceNow and Confluence directly into Microsoft 365 Copilot.

Researcher combines OpenAI’s deep research model with Microsoft 365 Copilot’s advanced orchestration and deep search capabilities.

Analyst, built on OpenAI’s o3-mini reasoning model, thinks like a virtual data scientist. It can take raw data scattered across multiple spreadsheets to do things like forecast how much demand there will be for a new product or build a visualization of customer purchasing patterns. 

Agents that help automate cybersecurity tasks

Other new agents can help organizations defend against cyberthreats, handling certain security tasks to help human teams be more efficient.

These agents, introduced March 24, are designed to autonomously assist with critical areas such as phishing, data security and identity management. 

For example, a new phishing triage agent in Microsoft Security Copilot can handle routine phishing alerts and cyberattacks, freeing up human cybersecurity teams to focus on more complex cyberthreats and proactive security measures.

And the new Alert Triage Agents in Microsoft Purview can triage data loss prevention and insider risk alerts, prioritize critical incidents and continuously improve accuracy based on administrator feedback.

Agents to help developers build and deploy AI securely

Agents are giving developers new options as well.

Two new ones are accessible in Azure AI Foundry — a platform where developers and organizations build, deploy and manage AI apps, providing the infrastructure developers need to create intelligent agents on a large scale. 

Microsoft Fabric data agents allow developers using Azure AI Agent Service in Azure AI Foundry to connect customized, conversational agents created in Microsoft Fabric. These data agents can reason over and unlock insights from various sources to make better data-driven decisions.

For example, NTT DATA, a Japanese IT and consulting company, is using data agents in Microsoft Fabric to have conversations with HR and back-office operations data to better understand what is happening in the organization.

And the new AI Red Teaming Agent, now in public preview, systematically probes AI models to uncover safety risks. It generates comprehensive reports and tracks improvements over time, creating an AI safety-testing ecosystem that evolves alongside your system.

Learn more about the latest in agents at Microsoft Build 2025 — registration is now open.

Image was created using Microsoft Designer, an AI-powered graphic design application.

The post 3 new ways AI agents can help you do even more appeared first on The Microsoft Cloud Blog.

The United Kingdom (UK) is on the brink of a half-a-trillion-pound opportunity, powered by AI and cloud technologies that are set to transform industries, boost productivity, and redefine the way we work. As Europe’s most advanced digital economy, home to 171 unicorns worth more than £800 billion, the UK has already proven its appetite for innovation, investing more than £20 billion in AI since 2016. But realizing AI’s full potential isn’t just about investment, it’s about action.

AI is no longer a distant concept. Businesses across every sector are already embedding AI-powered agents into their operations—automating workflows, streamlining decision-making, and eliminating digital drudgery to free employees for more impactful work. The rise of agentic AI—technology that doesn’t just respond to commands but takes action on our behalf—marks a major shift, poised to revolutionize everything from customer service to cybersecurity, driving efficiency, resilience, and innovation at scale.

And yet, a stark AI divide is emerging. More than half of UK organizations still lack a formal AI strategy, and 57% of business leaders report a growing gap in productivity between AI adopters and non-adopters. With employees and leaders already stretched thin, the demand for AI-powered solutions has never been more pressing.

The question is no longer whether AI will reshape the UK economy, but how quickly businesses will step up to seize the opportunity. Organizations that act decisively—building clear AI strategies and investing in the right capabilities—will be the ones that thrive. I highlighted several of these leading organizations during my AI Tour keynote, and I’m excited to share more of their journeys here. 

Pets at Home reimagines integrated pet care with AI

Pets at Home, the UK’s largest pet care company, is transforming its operations with AI agents powered by Microsoft Copilot Studio. The company, which includes 450 retail stores, an online platform, veterinary practices, and grooming services, initially operated in silos but underwent a digital transformation to unify the customer experience across all channels using Microsoft Azure.

With a centralized data platform in place, Pets at Home turned to AI to enhance efficiency. One of the first AI agents supported fraud detection, swiftly analyzing vast amounts of data to identify suspicious transactions, such as repeated use of the same image for fraudulent refund claims. This has significantly improved fraud investigation speed and accuracy.

AI is also powering personalized customer interactions. With 8 million loyalty program members and 10 million pets, the company uses machine learning to recommend tailored pet care solutions across its retail, veterinary, and grooming services. This ensures customers receive relevant, stage-specific pet care guidance.

The company’s veterinary practices are using AI to reduce administrative tasks, allowing clinicians to focus more on patient care. AI-powered transcription services assist during consultations and operations, while scheduling automation improves efficiency, enhancing clinical focus, and aligning with the company’s mission of better pet care.

By integrating AI agents, Pets at Home has enhanced fraud detection, improved personalization, and streamlined veterinary operations, driving innovation and efficiency across its ecosystem.

Amey embraces AI agents for a safer, more connected workforce

Amey, a UK-based engineering firm, plays a vital role in designing, maintaining, operating, and building the country’s infrastructure. With services impacting 75% of the UK population daily, ensuring safety and efficiency is a top priority.

Access to safety information has long been a challenge for frontline workers, who previously had to stop tasks and manually sift through folders full of paper documents for relevant details. Without regular access to laptops or computers, Amey opted to democratize information access for its workforce with mobile-friendly AI-powered agents.

Now, 99% of its 118 million files are stored on SharePoint, and AI allows employees to retrieve answers instantly through a chat interface. No more digging through folders—critical safety information is now just a few taps away, preventing issues and resolving others faster.

The AI system boosts efficiency and safety by providing instant access to essential information, real-time troubleshooting, and multilingual support while maintaining English documentation. By filling gaps where supervisors aren’t always available, it reduces risks and empowers employees to work more confidently and get home safely every day.

With AI now embedded in everyday operations, Amey is setting new standards for workplace safety and efficiency, proving that technology is a powerful ally in protecting and empowering its workforce.

Nationwide streamlines operations and cuts response times with generative AI

Nationwide, the world’s largest building society, serves 17 million customers across more than 600 UK branches. After merging with around 250 smaller societies, it faced a tangled web of data. By applying Microsoft Azure, Azure Databricks, and Teradata’s VantageCloud, it streamlined everything into a powerful, centralized platform, empowering employees to access a complete view of customer needs in seconds, delivering faster, more personalized service with greater efficiency.

Nationwide has built upon that infrastructure by integrating GPT-4 within Azure OpenAI Service to augment various business functions. One of the most impactful applications has been in customer correspondence, where AI-generated letters have reduced response times from 45 minutes to approximately 10–15 minutes, a 66% improvement in efficiency. AI has also been deployed to automate routine back-office tasks, allowing employees to focus on addressing more complex customer inquiries and improving overall service quality, which reflects Nationwide’s philosophy of using AI as a “copilot” to assist employees rather than as an “autopilot” to replace them.

Nationwide has established an AI Centre of Expertise and an AI Council to oversee responsible AI use, ensuring transparency and responsible standards in collaboration with Microsoft. This framework builds customer trust while guiding the expansion of AI into contact center operations, credit risk assessment, economic crime monitoring, its virtual assistant Arti, and CO₂ emissions reporting.

Be My Eyes puts AI into the hands of blind and low-vision individuals

Be My Eyes has long connected blind and low-vision people with sighted volunteers and partner companies through live video assistance. Now, with AI, it’s radically improving accessibility. In collaboration with Microsoft, Be My Eyes is making AI models more inclusive for the 340 million people worldwide with no or low vision by integrating accessibility data to serve diverse needs better.

A key innovation is Be My AI, a tool that helps users independently navigate their digital world by providing AI-powered descriptions of on-screen content. Part of Be My Eyes for Windows, Be My AI makes it easier to browse websites, use applications, or read documents. It also provides descriptions of locally stored images, offering clarity on personal photos and saved graphics. Online images can be analyzed simply by copying them to the clipboard for a detailed text description. The tool even helps users prepare for video calls by checking if they are centered in the frame and describing their background before going live.

An interactive chatbot allows users to ask follow-up questions about descriptions for a more dynamic and personalized experience. While the app is still in beta, ongoing improvements and new features will continue to expand its capabilities, allowing Be My Eyes to improve accessibility and redefine independence for blind and low-vision people.

Virgin Money’s virtual assistant is “Redi” to transform customer service

Virgin Money, serving 6.6 million retail and business banking customers, sought to enhance digital customer experience by developing “Redi,” an award-winning virtual assistant. Built using Microsoft Copilot Studio and integrated with Dynamics 365 Customer Service, Redi bridges the gap between digital adoption and customer confidence.

Developed in close collaboration with frontline contact center staff and seamlessly integrated with the Dynamics 365 Knowledge Base, Redi features an intuitive digital journey that provides customers with timely and effective assistance. A core value to the company, the virtual assistant maintains Virgin Money’s distinctive brand voice, understanding colloquialisms and responding to informal language.

Virgin Money collaborated with compliance teams to ensure Redi’s interactions are clear and secure. The assistant introduces itself transparently and seamlessly transitions customers to human agents when handling complex issues, effectively triaging 90% of inquiries, boosting customer satisfaction ratings, and allowing contact center agents to focus on more complex tasks.

This strategic AI deployment exemplifies Virgin Money’s commitment to exceptional customer experience and recognition that the major role of agentic AI has in delivering that now and into the future.

AI for everyone in the UK: Decisive action

The UK’s AI journey has already been transformative, but the next era—powered by agentic AI—has the potential to be truly revolutionary. By and large, UK organizations recognize the competitive advantage AI has to offer, but have yet to fully unlock AI’s potential, citing barriers such as workforce readiness, strategic alignment, and regulatory uncertainty.

Overcoming these hurdles is challenging but certainly achievable. It requires investment not only in AI infrastructure but also in skills development. Microsoft has stepped in with full support for the UK economy, having made a multibillion-pound commitment to AI-enabled datacenters and bringing AI skills to an additional 1 million people by the end of this year, on top of the 1.5 million it has already given digital skills to.

This shared foundation is essential to putting the AI-powered economy within reach, but success will depend on how quickly and effectively businesses themselves take strategic steps to embrace AI. I posed these questions to those who attended the Microsoft AI Tour event in London, and I urge you to consider them as well: 

1. What are you trying to achieve in the next six months, and how can AI help you get there faster? 

2. How are you and your team set up to embrace the change, and what culture shifts are needed to ensure AI adoption is unencumbered? 
3. How can Microsoft and its partners be part of that journey? What do you need from us to accelerate your progress and deliver real outcomes? 

Together, we have the opportunity to shape an AI-powered future where businesses flourish, employees thrive, and the UK cements its position as a global leader in innovation. The time to act is now.

Find the resources to support your AI journey 

• Advance your AI transformation with AI business resources
• Microsoft Agents of Change
• ‘AI divide’ across UK organizations risks growth for many, new Microsoft research reveals

The post The UK’s opportunity to seize growth in the age of agentic AI appeared first on The Microsoft Cloud Blog.

Now, the focus is starting to shift. Productivity gains are just the beginning of a broader transformation—one that goes beyond efficiency to reshape industry processes, decision-making, and customer experiences.

ROI of AI

How can industry leaders increase ROI?

Watch the video series

True AI transformation requires an industry perspective

In our conversations with customers, many are asking about the next wave of AI. They’re ready to expand beyond general AI applications and invest in solutions tailored to their specific challenges. While organizations recognize AI’s value and potential, it must address industry-specific needs to deliver the biggest results. 

Take healthcare, for example, where engaging with patients requires sensitivity, data privacy, and personalized care. That’s very different from retail, where personalization is all about tailored shopping recommendations and seamless experiences.

The same contrast exists in manufacturing and transportation. Manufacturers focus on optimizing production lines for efficiency and quality, while fleet operations prioritize logistics, route optimization, and fuel costs.

These differences show why AI adoption is moving beyond general-purpose tools to industry-specific solutions that drive even greater impact. In our recent video series on the Return on Investment (ROI) of AI, we explore this trend, real-world use cases, and how AI is transforming industries like financial services and retail. These insights reflect what I’m seeing in conversations with customers about the changing AI landscape.

Where to invest in AI for maximum impact

Today’s leaders are looking beyond AI for productivity and asking a bigger question: Where should we invest next to drive business growth? The key is to align AI investments with mission-critical priorities.

So, is the AI for industry buzz real, and is it worth the investment? The answer is yes—here’s why:

• Industry-specific AI solutions tackle complex challenges—such as regulatory compliance in financial services, seamless omnichannel shopping experiences in retail, and asset troubleshooting in manufacturing.  At Microsoft, we’ve worked with thousands of customers to identify industry use cases where AI delivers meaningful business results. Building on these insights, we offer customizable AI agents designed to accelerate time to value for our customers.
• Customizable AI agents in Microsoft Copilot Studio help businesses tailor AI to their needs. Agent Builder, a feature within Copilot Studio, simplifies customization with industry-specific knowledge and low-code tools. In addition, our customers have access to a wide range of adapted AI models to accurately and effectively address their unique needs.
• AI models, developed in collaboration with partners, and built for specific industries make adoption easier across every sector and region. These fine-tuned models are trained on industry data to support business-critical use cases.

To see industry-specific AI in action, let’s explore key use cases in financial services, retail, manufacturing, and healthcare.

Driving growth in financial services with AI

Financial services organizations are leading the way in AI adoption, and it’s paying off. They’re realizing a 4.2 times average ROI on generative AI initiatives¹—the highest across industries. Discover how PicPay uses Microsoft AI to answer product and service questions quickly and securely.

Key use cases for AI in finance industry include:

• Banking: AI enhances customer interactions, improves fraud detection, and streamlines meeting preparation.
• Insurance: AI speeds claims processing and resolution, identifies upsell opportunities, and improves customer engagement.
• Capital markets: AI personalizes client presentations, generates predictive insights, and accelerates research.

Watch the video to explore AI business transformation in financial services.

Retailers solve complex challenges with AI

Retailers are realizing a 3.6 times ROI on generative AI initiatives,² and some are tackling customer acquisition, profitability, supply chain reliability, and data complexity. Learn how ASOS, a British online fashion retailer, uses Azure AI Foundry to surprise and delight young fashion lovers with engaging, inspirational experiences.

Key use cases for AI in retail industry include:

• Personalized Shopping Agent engages in natural language conversations, delivering tailored recommendations and assisting with specific requests.
• Store Operations Agent integrates product search, inventory, orders, omnichannel pricing, and incident management into existing applications.
• AI-powered insights help retailers create targeted marketing campaigns that boost engagement and increase sales. See how Microsoft Cloud for Retail connects customers, employees, and data.

Watch the video to see why the retail industry is embracing AI.

How AI powers smarter manufacturing

Manufacturers are achieving a 3.4 times ROI on generative AI initiatives.³ They’re also using AI to speed time to market, streamline application lifecycle management, and simplify manufacturing processes. See how Schneider Electric addresses the company’s most pressing issues by innovating with Azure OpenAI Service.

Key use cases for AI in manufacturing industry include:

• AI-powered generative design accelerates product development by automating design processes, refining models in real time, and freeing teams to focus on manufacturability and compliance.
• AI-assisted coding helps developers write, debug, and optimize code faster, enhancing industrial software development and connected product functionality.
• AI-powered factory insights provide real-time data for root cause analysis, production loss reduction, and asset maintenance, boosting efficiency and safety.

Learn more about Microsoft technology in the manufacturing industry.

AI helps empower the healthcare workforce and enhance patient care

In healthcare, AI is transforming medical data management, personalizing clinician and patient experiences, and helping to improve patient outcomes—delivering a 3.3 times ROI on generative AI initiatives.⁴ See how AI innovation empowers healthcare teams to refocus on the clinician-patient connection at Northwestern Medicine, Overlake Medical Center & Clinics, and Atrium Health.

Key AI use cases for healthcare include:

• AI assistants help streamline clinical documentation, surface information, and automate tasks to improve efficiency, satisfaction, and patient care.
• Advanced healthcare AI models are designed to enhance disease detection, diagnostics, and treatment planning.
• Multimodal AI generates insights from unified healthcare data to identify care gaps faster for early intervention, develop more tailored care plans, improve the accuracy of diagnoses, and allocate hospital resources more effectively.

We’re here to help you drive AI success

Organizations that invest in industry-focused AI applications and stay current with AI industry trends are realizing the greatest ROI with AI. We’re here to help you take action now and position your business for innovation, efficiency, and competitive advantage.

Watch the ROI of AI video series to learn more about AI ROI.

^{1, 2, 3, 4} IDC InfoBrief: sponsored by Microsoft, 2024 Business Opportunity of AI, IDC #US52699124, November 2024.

The post Beyond productivity: How industry-specific AI fuels growth appeared first on The Microsoft Cloud Blog.

The skills gap is widening, and it is our collective responsibility to bridge it. Business leaders and professionals are exploring ways to build and enhance critical skills within their teams, and Microsoft is leading the charge. 

In addition to launching ambitious skill-building initiatives such as the upcoming Microsoft AI Skills Fest, we’re also eager to spotlight innovative organization like Founderz, a groundbreaking online learning platform that has gone from a bold idea to a leader in AI skilling in just a few years. Their story is worth sharing not only because of their emerging role in ensuring the workforce is prepared for the future, but because it’s a testament to the power of innovation, perseverance, and the impact of just one company believing in a vision.  

One “yes” can change everything 

Co-founders Anna Cejudo and Pau Garcia-Mila had a simple but powerful idea: what if online business education could capture the depth, collaboration, and networking of the world’s top business schools—but in a way that was scalable, accessible, and built for the AI-powered future? 

“We felt there is still a big gap between the experience we have when we go to an on-site business school—where you meet the best professors, the best content—and the way we learn online,” explained Pau Garcia-Mila, Co-Chief Executive Officer and Co-Founder.

They spent years building the technology behind Founderz, investing in AI-powered learning models that would make online education engaging, interactive, and deeply effective. But by 2023, they were at a breaking point. Funding had run out, and they needed a breakthrough.

In a final effort, they sent three emails to companies at the forefront of AI—hoping one of them would see what they saw: a future where AI education was truly transformative. Only Microsoft responded. 

Founderz was accepted into the Microsoft for Startups Founders Hub, which provided access to industry-leading AI services, expert guidance, and essential technology to supercharge their growth. Entering the Microsoft for Startups Founders Hub at Tier 4 also unlocked USD150,000 in Microsoft Azure credits, enabling the company to scale their platform, refine their AI-powered learning model, and start delivering high-quality AI education at scale. 

Today, Founderz itself is helping change lives.

“In 2024, we had roughly 10,000 users learning AI with Founderz,” recalled Anna Cejudo, co-CEO and co-founder. “By the end of the year, we were at 50,000. And now, by the beginning of March, we reached 100,000 users training in AI. The real revolution isn’t AI—it’s education,” added Anna, highlighting the fundamental role of learning in driving change. They’ve also become a Microsoft Training Services Partner, making the decision to offer training exclusively on Microsoft AI technology.  

AI skilling done differently 

Founderz is far from being just another online course provider. Pau, Anna, and their growing team are rethinking how AI is taught by blending structured learning with real-time collaboration, personalized AI-powered support, and a hands-on approach to applying AI in real-world scenarios. 

At the heart of the Founderz learning experience are high-quality, cinematic-style lectures. Unlike traditional online courses that rely on static, slide-based presentations, Founderz films its courses in a MasterClass-style format, featuring top AI experts from Microsoft and beyond. This approach allows learners to hear directly from the people shaping the future of AI. 

Expert content in student’s native language 

But Founderz goes beyond delivering engaging content—it’s about accessibility. A core mission is to provide top-tier AI education in students’ native languages. Next-generation lip-syncing technology ensures that learners experience AI-powered content seamlessly, without language barriers.

“I can watch a Responsible AI class from Microsoft’s Mihaela Vorvoreanu in my language,” says Pau Garcia-Mila. “She speaks in first person, saying, ‘When we built this Responsible AI model at Microsoft.’ I’d love to be able to learn from the source in my mother tongue.”

Small group collaboration  

While putting “thousands of people in a virtual room” enables Founderz to pay the best professors at a lower per-student cost, the company also sought to build a platform that supported meaningful collaboration. AI-powered tools match students into small, diverse learning circles, where they tackle real-world AI challenges, share insights, and build lasting professional networks. 

Multilingual student support around the clock 

To further support its rapidly growing user base, Founderz’ team of AI-powered teaching assistants or “Fellows” provide real-time multilingual support, allowing learners to receive help in their native language while keeping operations efficient for the human support team.  

As Pau Garcia-Mila explained, “The Fellows are speaking any language in the world, but our human team sees everything in English,” ensuring seamless interaction across different languages. 

These AI-powered teaching assistants provide real-time feedback, analyze student interactions, and escalate complex questions to human instructors when needed. Whether a learner is a complete beginner or an experienced professional, Founderz ensures they receive the support they need to succeed. 

Education means opportunity

Founderz’ journey from a bold idea to an emerging AI skilling leader is proof that AI education is more than just accessing information—it’s about unlocking potential. Its pioneering efforts continue to inspire countless organizations to embrace AI education and drive meaningful transformation worldwide.

As Anna Cejudo puts it, “Education means opportunity, and if we can deliver high-quality education to as many people as possible, we’re giving them the chance to change their lives and control their futures.” 

At Microsoft, we couldn’t agree more. Microsoft’s mission has always been about creating technology that empowers others to innovate and solve real-world problems. This holds true in the age of AI. Our commitment to skilling is not just about technology adoption, it’s about people development. Over the past year, Microsoft has trained and certified over 23 million people across more than 200 countries in digital skills, with the goal of ensuring that everyone has the opportunity to succeed in a world where AI will be commonplace and a natural extension of everything we do.  

Unlock the future—Join the Microsoft AI Skills Fest 

As part of our ongoing investment in global skilling, Microsoft is bringing AI skilling to everyone with the Microsoft AI Skills Fest—a global event designed to bring together customers and partners, tech and business professionals, and AI enthusiasts to help build the skills we all need to thrive in the AI economy.  

Beginning April 8, 2025, we’re kicking off the fun with an attempt to set a GUINNESS WORLD RECORDS™ title for the most users to take an online multi-level artificial intelligence lesson in 24 hours. After that, we’re inviting everyone to continue building their skills with 50 days to explore Microsoft’s AI apps and services.  

Let’s make history together.

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¹IDC InfoBrief: sponsored by Microsoft, 2024 Business Opportunity of AI, IDC# US52699124, November 2024.

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In a recent playbook, Accelerating sustainability with AI: Innovations for a better future, we outlined our five plays to advance sustainability, providing insight into our work at Microsoft and how business leaders around the world are creating a new path forward.

The reason to choose AI for this work? It has three unique abilities that can help organizations overcome key bottlenecks. AI can: (1) measure, predict, and optimize complex systems, (2) accelerate the development of sustainability solutions, and (3), empower the sustainability workforce. These capabilities make AI a critical enabler of progress.

Accelerate sustainability with AI

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How can business leaders harness AI to accelerate resilience, efficiency, and sustainability in their organization?

I recently met with Lindsay Myers, Vice President, Commercial Cross Solutions at Microsoft, who leads our Commercial Sustainability business, to talk more about this guidance and how business leaders can harness AI to accelerate resilience, efficiency, and sustainability in their organizations.

Toby: Hi Lindsay, before we dive into the playbook, can you share your thoughts on how organizations are adopting AI to address these interconnected goals of resilience, efficiency, and sustainability?

Lindsay: It’s important to highlight how interconnected these goals are in many organizations today. We often see initiatives started by sustainability teams result in significant cost savings for organizations. This might be efficiency gains for existing operations, or entirely new approaches like digital twins that enable rapid iteration before initial prototypes are built. When companies choose an approach like digital twins, it can reduce the materials needed for physical models—saving time and costs—while improving resilience through agility.

Explore customer and partner examples of AI innovation

Toby: Can you give me some examples of customers and partners who are doing this work today?

Lindsay: AI is making a real difference in helping organizations prepare for climate risks, innovate for maximum efficiency, and solve complex challenges. For example, in Germany, where urban flooding is a major concern, cities are searching for innovative ways to mitigate the impacts of heavy rainfall and its impact on communities and infrastructure. Esri, a global leader in geographic information system (GIS) software is helping cities unlock the power of digital twins driven by geospatial data and AI. This solution helped the City of Stuttgart cut its reality mapping time from five months to 24 hours, enabling local government and public safety staff to understand potential impacts and make decisions faster.

Stadtwerke München (SWM), the municipal utilities company serving Munich, has made it its mission to drive every aspect of the city’s energy, heating, and mobility transition forward. To accomplish this, it needed maximum-efficiency processes, such as predictive infrastructure maintenance and optimized operations planning. It has turned to Microsoft Azure and Azure IoT to efficiently provide power to its public transport fleet of 100% electrified vehicles.

Unlock new possibilities with data and AI

Toby: Those are inspiring examples; they give a real sense of AI’s potential. The playbook outlines 5 plays, or ways that organizations can unlock this potential. Could you describe some of these?

Lindsay: Let’s talk first about the first two plays and how they work together.

Investing in AI solutions to measure, predict, and optimize complex systems can drive both innovation and efficiency, helping companies focus on the most strategic priorities for business resilience.

For example, Mitiga Solutions, a global leader in climate risk intelligence and a Microsoft Climate Innovation Fund investment leverages AI, high-performance computing, and advanced climate models to predict the impact of physical climate hazards on any asset, anywhere in the world, from now until the end of the century. This helps infrastructure, commercial real estate, insurers, and companies across industries comply with climate disclosure regulations while proactively strengthening their resilience.

 With AI-powered solutions, businesses can swiftly tackle complex challenges across their own supply chains and for their customers. This not only positions companies as leaders in sustainability but can also unlock new market opportunities and enhance their competitive advantage.

It’s crucial to build a strong digital and data infrastructure to maximize AI’s potential—your AI is only as good as the data it relies on. That’s why having high-quality, representative data and the right processing infrastructure is essential. It enables teams to make informed decisions and provides accurate input for AI applications.

For many of our customers and partners, these two plays are closely linked. The foundational work involves bringing all the necessary data together in one place, like in Microsoft Fabric. What’s amazing about Fabric is it lets you reason over both internal and external data, which is incredibly helpful for things like regulatory reporting.

Once your data is set up properly, your team can use solutions such as Microsoft Copilot to ask questions of their data, generate reports, and learn from industry best practices. Copilot streamlines these tasks, reducing manual work and enabling practitioners to focus their time on new strategic initiatives.

Minimize resource use in AI design and operations

Toby: When I talk to organizations looking to adopt AI, customers and partners often want to learn more about what Microsoft is doing to reduce the environmental impact of AI. Could we talk a bit about that?

Lindsay: Absolutely. Let’s talk about play 3 and how that relates to our work at Microsoft.

AI has its own energy and water demands, so it’s crucial to minimize resource use and move toward powering AI systems with carbon-free energy. In addition, since AI infrastructure is often concentrated in specific regions, it is essential to support the local communities where datacenters are located. At Microsoft, we’re innovating across three critical areas to continue to advance the sustainability of cloud and AI services:

1. Optimizing datacenter energy, water, and waste efficiency while protecting ecosystems.
2. Advancing low-carbon materials and creating global markets to promote industry-wide sustainability.
3. Enhancing the energy efficiency of AI and cloud services.

Many of our customers and partners want to know not only what we’re doing, but also what they can do to manage resource use. Our Well-Architected Framework sustainability guidance provides a great starting point, as well as small language models that perform specific tasks using fewer resources than larger models.

Build workforce capacity to use AI for sustainability

Toby: The pace of innovation in this domain is incredible. Is there anything more you’d like to add in terms of how your team helps leaders move their ideas from concept to implementation?

Lindsay: The way forward on this journey is through people working together, and this is an area where we can help customers and partners make progress. Let’s talk about the final play first:

For companies to be able to put AI’s three game-changing capabilities to work, they must have skills to use AI effectively. Microsoft has training programs focused on building AI fluency, supporting nonprofits, businesses, and governments in advancing workforce AI technical skills and promoting safe and responsible AI development.

Microsoft’s AI learning hub can empower customers on their AI transformation journey, and customers can also use Copilot to connect with their data in Microsoft Cloud for Sustainability and sustainability data solutions in Microsoft Fabric. With these tools, employees can quickly gain insights, understand gaps, and identify what’s needed to move initiatives forward.

Toby: Thank you, Lindsay!

Transform business using generative AI

For business leaders wanting to put these plays in action and guide their organizations through effective AI adoption, we’ve published the 2025 AI Decision Brief: Insights from Microsoft and AI leaders on navigating the generative AI platform shift. This report is packed with perspectives from top Microsoft leaders and insights from AI innovators, along with stories of companies across industries that have transformed their businesses using generative AI.

2025 AI Decision Brief

Advance AI and drive consistent AI value in your org

Get the full report

The post Harnessing AI for resilience, efficiency, and sustainability appeared first on The Microsoft Cloud Blog.

It leverages the world’s first topoconductor, a breakthrough type of material which can observe and control Majorana particles to produce more reliable and scalable qubits, which are the building blocks for quantum computers.

In the same way that the invention of semiconductors made today’s smartphones, computers and electronics possible, topoconductors and the new type of chip they enable offer a path to developing quantum systems that can scale to a million qubits and are capable of tackling the most complex industrial and societal problems, Microsoft said.

“We took a step back and said ‘OK, let’s invent the transistor for the quantum age. What properties does it need to have?’” said Chetan Nayak, Microsoft technical fellow. “And that’s really how we got here – it’s the particular combination, the quality and the important details in our new materials stack that have enabled a new kind of qubit and ultimately our entire architecture.”

This new architecture used to develop the Majorana 1 processor offers a clear path to fit a million qubits on a single chip that can fit in the palm of one’s hand, Microsoft said. This is a needed threshold for quantum computers to deliver transformative, real-world solutions – such as breaking down microplastics into harmless byproducts or inventing self-healing materials for construction, manufacturing or healthcare. All the world’s current computers operating together can’t do what a one-million-qubit quantum computer will be able to do. 

“Whatever you’re doing in the quantum space needs to have a path to a million qubits. If it doesn’t, you’re going to hit a wall before you get to the scale at which you can solve the really important problems that motivate us,” Nayak said.  “We have actually worked out a path to a million.”

The topoconductor, or topological superconductor, is a special category of material that can create an entirely new state of matter – not a solid, liquid or gas but a topological state. This is harnessed to produce a more stable qubit that is fast, small and can be digitally controlled, without the tradeoffs required by current alternatives. A new paper published Wednesday in Nature outlines how Microsoft researchers were able to create the topological qubit’s exotic quantum properties and also accurately measure them, an essential step for practical computing.

This breakthrough required developing an entirely new materials stack made of indium arsenide and aluminum, much of which Microsoft designed and fabricated atom by atom. The goal was to coax new quantum particles called Majoranas into existence and take advantage of their unique properties to reach the next horizon of quantum computing, Microsoft said.  

The world’s first Topological Core powering the Majorana 1 is reliable by design, incorporating error resistance at the hardware level making it more stable.

Commercially important applications will also require trillions of operations on a million qubits, which would be prohibitive with current approaches that rely on fine-tuned analog control of each qubit. The Microsoft team’s new measurement approach enables qubits to be controlled digitally, redefining and vastly simplifying how quantum computing works.

This progress validates Microsoft’s choice years ago to pursue a topological qubit design – a high risk, high reward scientific and engineering challenge that is now paying off. Today, the company has placed eight topological qubits on a chip designed to scale to one million.

“From the start we wanted to make a quantum computer for commercial impact, not just thought leadership,” said Matthias Troyer, Microsoft technical fellow. “We knew we needed a new qubit. We knew we had to scale.”

That approach led the Defense Advanced Research Projects Agency (DARPA), a federal agency that invests in breakthrough technologies that are important to national security, to include Microsoft in a rigorous program to evaluate whether innovative quantum computing technologies could build commercially relevant quantum systems faster than conventionally believed possible.  

Microsoft is now one of two companies to be invited to move to the final phase of DARPA’s Underexplored Systems for Utility-Scale Quantum Computing (US2QC) program – one of the programs that makes up DARPA’s larger Quantum Benchmarking Initiative – which aims to deliver the industry’s first utility-scale fault-tolerant quantum computer, or one whose computational value exceeds its costs. 

‘It just gives you the answer’

In addition to making its own quantum hardware, Microsoft has partnered with Quantinuum and Atom Computing to reach scientific and engineering breakthroughs with today’s qubits, including the announcement last year of the industry’s first reliable quantum computer.

These types of machines offer important opportunities to develop quantum skills, build hybrid applications and drive new discovery, particularly as AI is combined with new quantum systems that will be powered by larger numbers of reliable qubits. Today, Azure Quantum offers a suite of integrated solutions allowing customers to leverage these leading AI, high performance computing and quantum platforms in Azure to advance scientific discovery.

But reaching the next horizon of quantum computing will require a quantum architecture that can provide a million qubits or more and reach trillions of fast and reliable operations. Today’s announcement puts that horizon within years, not decades, Microsoft said.

Because they can use quantum mechanics to mathematically map how nature behaves with incredible precision – from chemical reactions to molecular interactions and enzyme energies – million-qubit machines should be able to solve certain types of problems in chemistry, materials science and other industries that are impossible for today’s classical computers to accurately calculate.

• For instance, they could help solve the difficult chemistry question of why materials suffer corrosion or cracks. This could lead to self-healing materials that repair cracks in bridges or airplane parts, shattered phone screens or scratched car doors.
• Because there are so many types of plastics, it isn’t currently possible to find a one-size-fits-all catalyst that can break them down – especially important for cleaning up microplastics or tackling carbon pollution. Quantum computing could calculate the properties of such catalysts to break down pollutants into valuable byproducts or develop non-toxic alternatives in the first place.
• Enzymes, a kind of biological catalyst, could be harnessed more effectively in healthcare and agriculture, thanks to accurate calculations about their behavior that only quantum computing can provide. This could lead to breakthroughs helping to eradicate global hunger: boosting soil fertility to increase yields or promoting sustainable growth of foods in harsh climates.

Most of all, quantum computing could allow engineers, scientists, companies and others to simply design things right the first time – which would be transformative for everything from healthcare to product development. The power of quantum computing, combined with AI tools, would allow someone to describe what kind of new material or molecule they want to create in plain language and get an answer that works straightaway – no guesswork or years of trial and error.  

“Any company that makes anything could just design it perfectly the first time out. It would just give you the answer,” Troyer said. “The quantum computer teaches the AI the language of nature so the AI can just tell you the recipe for what you want to make.”

Rethinking quantum computing at scale

The quantum world operates according to the laws of quantum mechanics, which are not the same laws of physics that govern the world we see. The particles are called qubits, or quantum bits, analogous to the bits, or ones and zeros, that computers now use.

Qubits are finicky and highly susceptible to perturbations and errors that come from their environment, which cause them to fall apart and information to be lost. Their state can also be affected by measurement – a problem because measuring is essential for computing. An inherent challenge is developing a qubit that can be measured and controlled, while offering protection from environmental noise that corrupts them.

Qubits can be created in different ways, each with advantages and disadvantages. Nearly 20 years ago, Microsoft decided to pursue a unique approach: developing topological qubits, which it believed would offer more stable qubits requiring less error correction, thereby unlocking speed, size and controllability advantages. The approach posed a steep learning curve, requiring uncharted scientific and engineering breakthroughs, but also the most promising path to creating scalable and controllable qubits capable of doing commercially valuable work.

https://youtube.com/watch?v=wSHmygPQukQ%3Ffeature%3Doembed%26enablejsapi%3D1%26origin%3Dhttps%253A%252F%252Fnews.microsoft.com

The disadvantage is – or was – that until recently the exotic particles Microsoft sought to use, called Majoranas, had never been seen or made. They don’t exist in nature and can only be coaxed into existence with magnetic fields and superconductors. The difficulty of developing the right materials to create the exotic particles and their associated topological state of matter is why most quantum efforts have focused on other kinds of qubits.

The Nature paper marks peer-reviewed confirmation that Microsoft has not only been able to create Majorana particles, which help protect quantum information from random disturbance, but can also reliably measure that information from them using microwaves.

Majoranas hide quantum information, making it more robust, but also harder to measure. The Microsoft team’s new measurement approach is so precise it can detect the difference between one billion and one billion and one electrons in a superconducting wire – which tells the computer what state the qubit is in and forms the basis for quantum computation.

The measurements can be turned on and off with voltage pulses, like flicking a light switch, rather than finetuning dials for each individual qubit. This simpler measurement approach that enables digital control simplifies the quantum computing process and the physical requirements to build a scalable machine.

Microsoft’s topological qubit also has an advantage over other qubits because of its size. Even for something that tiny, there’s a “Goldilocks” zone, where a too-small qubit is hard to run control lines to, but a too-big qubit requires a huge machine, Troyer said. Adding the individualized control technology for those types of qubits would require building an impractical computer the size of an airplane hangar or football field.

Majorana 1, Microsoft’s quantum chip that contains both qubits as well as surrounding control electronics, can be held in the palm of one’s hand and fits neatly into a quantum computer that can be easily deployed inside Azure datacenters.

“It’s one thing to discover a new state of matter,” Nayak said. “It’s another to take advantage of it to rethink quantum computing at scale.”

Designing quantum materials atom by atom

Microsoft’s topological qubit architecture has aluminum nanowires joined together to form an H. Each H has four controllable Majoranas and makes one qubit. These Hs can be connected, too, and laid out across the chip like so many tiles.

“It’s complex in that we had to show a new state of matter to get there, but after that, it’s fairly simple. It tiles out. You have this much simpler architecture that promises a much faster path to scale,” said Krysta Svore, Microsoft technical fellow.

The quantum chip doesn’t work alone. It exists in an ecosystem with control logic, a dilution refrigerator that keeps qubits at temperatures much colder than outer space and a software stack that can integrate with AI and classical computers. All those pieces exist, built or modified entirely in-house, she said.

To be clear, continuing to refine those processes and getting all the elements to work together at accelerated scale will require more years of engineering work. But many difficult scientific and engineering challenges have now been met, Microsoft said.

Getting the materials stack right to produce a topological state of matter was one of the hardest parts, Svore added. Instead of silicon, Microsoft’s topoconductor is made of indium arsenide, a material currently used in such applications as infrared detectors and which has special properties. The semiconductor is married with superconductivity, thanks to extreme cold, to make a hybrid.

“We are literally spraying atom by atom. Those materials have to line up perfectly. If there are too many defects in the material stack, it just kills your qubit,” Svore said.

“Ironically, it’s also why we need a quantum computer – because understanding these materials is incredibly hard. With a scaled quantum computer, we will be able to predict materials with even better properties for building the next generation of quantum computers beyond scale,” she said.

Related links:

Learn more: Introducing Microsoft Majorana 1

Read more: Microsoft unveils Majorana 1, the world’s first quantum processor powered by topological qubits

Learn more: Microsoft’s Quantum Ready program

Learn more: Azure Quantum Solutions  

Read more: In a historic milestone, Azure Quantum demonstrates formerly elusive physics needed to build scalable topological qubits

Read more: Nature: Interferometric Single-Shot Parity Measurement in InAs-Al Hybrid Devices

Read more: arXiv: Roadmap to fault tolerant quantum computation using topological qubit arrays

Top image: Majorana 1, the first quantum chip powered by a Topological Core based on a revolutionary new class of materials developed by Microsoft. Photo by John Brecher for Microsoft. 

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Enter retrieval augmented generation (RAG)—an innovative approach that seamlessly integrates information retrieval with text generation. This powerful combination of retrieval and generation has the potential to revolutionize applications from customer service chatbots to intelligent research assistants.

Let’s briefly uncover the future of AI-powered language understanding and generation through the lens of retrieval augmented generation.

Key features and benefits of RAG

Here are five key features and benefits that will help you understand RAG better.

1. Current and up-to-date knowledge

RAG models rely on external knowledge bases to retrieve real-time and relevant information before generating responses. LLMs were trained at a specific time and on a specific set of data. RAG allows for responses to be grounded on current and additional data rather than solely depending on the model’s training set.

Benefit: RAG-based systems are particularly effective when the data required is constantly changing and being updated. By incorporating real-time data, RAG patterns expand the breadth of what can be accomplished with an application, including live customer support, travel planning, or claims processing.

For example, in a customer support scenario, a RAG-enabled system can quickly retrieve relevant and accurate product specifications, troubleshooting guides, or customer’s purchase history, allowing users to resolve their issues efficiently. This capability is crucial in customer-support applications—where accuracy is paramount—because it not only enhances the user experience and fosters trust but also encourages the continued use of the AI system, helping to increase customer loyalty and retention.

2. Contextual relevance

RAG excels in providing contextually rich responses by retrieving data that is specifically relevant to the user’s query. This is achieved through sophisticated retrieval algorithms that identify the most pertinent documents or data snippets from a vast, disparate data set.¹

Benefit: By leveraging contextual information, RAG enables AI systems to generate responses that are tailored to the specific needs and preferences of users. RAG also enables organizations to maintain data privacy, versus retraining a model owned by a separate entity, allowing data to remain where it lives. This is beneficial in scenarios such as legal advice or technical support.

For example, if an employee asks about their company’s policy on remote work, RAG can pull the latest internal documents that outline those policies, ensuring that the response is not only accurate but is also directly applicable to the employee’s context. This level of contextual awareness enhances the user experience, making interactions with AI systems more meaningful and effective.

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3. Reduction of hallucinations

RAG allows for controlled information flow, finely tuning the balance between retrieved facts and generated content to maintain coherence while minimizing fabrications. Many RAG implementations offer transparent source attribution—citing references for retrieved information and adding accountability—which are both crucial for responsible AI practices. This auditability not only improves user confidence but also aligns with regulatory requirements in many industries, where accountability and traceability are essential.

Benefit: RAG boosts trust levels and significantly improves the accuracy and reliability of AI-generated content, thus helping to reduce risks in high-stakes domains like legal, healthcare, and finance. This leads to increased efficiency in information retrieval and decision-making processes, as users spend less time fact-checking or correcting AI outputs.²

For example, consider a financial advisor research assistant powered by RAG technology. When asked about recent Security and Exchange Commission filings regarding a publicly traded company in the United States from EDGAR, the commission’s online database, the AI system retrieves information from the latest annual reports, proxy statements, foreign investment disclosures, and other relevant documents filed by the corporation. The RAG model then generates a comprehensive summary, citing specific documents and their publication dates. This not only provides the researcher with current, accurate information they can trust, but also offers clear references for further investigation—significantly accelerating the research process while maintaining high standards of accuracy.

4. Cost effectiveness

RAG allows organizations to use existing data and knowledge bases without extensive retraining of LLMs. This is achieved by augmenting the input to the model with relevant retrieved data rather than requiring the model to learn from scratch.

Benefit: This approach significantly reduces the costs associated with developing and maintaining AI systems. Organizations can deploy RAG-enabled applications more quickly and efficiently, as they do not need to invest heavily in training large models on proprietary data.³

For example, consider a small-but-rapidly growing e-commerce company specializing in eco-friendly garden supplies. As they grow, they face the challenge of efficiently managing and utilizing their expanding knowledge base without increasing operational costs. If a customer inquires about the best fertilizer for a specific plant, the RAG system can quickly retrieve and synthesize information from product descriptions, usage guidelines, plant zone specifications, and customer reviews to provide a tailored response.

In this way, RAG technology allows the business to leverage its existing product documentation, customer FAQs, and a scalable internal knowledge base where the RAG system expands with the business, without the cost or need for extensive AI model training or constant updates. By providing accurate and contextually sensitive responses, the RAG system reduces customer frustration and potential returns—indirectly saving costs associated with customer churn and product returns.

5. User productivity

RAG helps boost user productivity by enabling users to access precise, contextually relevant data quickly by effectively combining information retrieval with generative AI.⁴

Benefit: This streamlined approach reduces the time spent on data gathering and analysis, allowing decision-makers to focus on actionable insights and teams to automate time-consuming tasks.

For example, KPMG built ComplyAI, a compliance checker, wherein employees submit client documents and request that the application review them. The app reviews the documents and flags any legal standards or compliance requirements, then sends the analysis to the user who originally set up the task. The app handles the review and analysis, saving the requestor time and effort. Thus, the app allows the user to ramp up on the topic or issue in question much faster without requiring them to be a legal expert.

As a result, users are more likely to perceive the AI application as a helpful and integral part of their daily tasks, whether in a professional or personal context.

Get started using RAG to enhance LLMs

In summary, by leveraging the vast knowledge stored in external sources, RAG enhances the capabilities of LLMs, including improved accuracy, contextual relevance, reduced hallucinations, cost-effectiveness, and improved auditability. These features collectively contribute to the development of more reliable and efficient AI applications across various sectors. RAG-enhanced systems also help empower smaller-sized businesses to compete effectively with larger competitors while managing their growth in a cost-effective manner, without the need to hire additional staff or for substantial AI model updates and retraining.

To get started, use the following resources to start building RAG applications with Azure AI Foundry and use them with agents built using Microsoft Copilot Studio.

• Build a RAG application with Azure OpenAI Service and Azure AI Search.
• Watch our videos:
  • Retrieval Augmented Generation with Azure AI Search
  • OpenAI creates retrieval augmented generation features with Azure AI Search

• Read about retrieval augmented generation (RAG) in Azure AI Search.
• Read about enhancing responses from agents built using Copilot Studio with your index built in Azure AI Search.

Our commitment to Trustworthy AI

Organizations across industries are leveraging Azure AI and Microsoft Copilot capabilities to drive growth, increase productivity, and create value-added experiences.

We’re committed to helping organizations use and build AI that is trustworthy, meaning it is secure, private, and safe. We bring best practices and learnings from decades of researching and building AI products at scale to provide industry-leading commitments and capabilities that span our three pillars of security, privacy, and safety. Trustworthy AI is only possible when you combine our commitments, such as our Secure Future Initiative and our Responsible AI principles, with our product capabilities to unlock AI transformation with confidence. 

¹DataCamp, How to Improve RAG Performance: 5 Key Techniques with Examples, 2024.

² Lewis, P., Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, 2020.

³ Castro, P., Announcing cost-effective RAG at scale with Azure AI Search, Microsoft, 2024.

⁴ Hikov, A. and Murphy, L., Information retrieval from textual data: Harnessing large language models, retrieval augmented generation and prompt engineering, Ingenta Connect, Spring 2024.

The post 5 key features and benefits of retrieval augmented generation (RAG) 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.

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