Now you can get help with all of this and more by simply asking an AI agent to take care of it — while you drink a second cup of coffee and focus on your team’s long-term strategy.

An agent can tackle certain tasks with you or for you, from acting as a virtual project manager to handling more complex assignments like reconciling financial statements to close the books. Microsoft 365 Copilot is already a personal assistant that helps with everything from tedious daily duties to jumpstarting creative projects. Using it to interact with various agents brings a new world of possibilities for organizations to empower their employees, drive business and accomplish even more.

Agents can operate around the clock to review and approve customer returns or go over shipping invoices to help businesses avoid costly supply-chain errors. They can reason over reams of product information to give field technicians step-by-step instructions or use context and memory to open and close tickets for an IT help desk.

“Think of agents as the new apps for an AI-powered world,” says Jared Spataro, Microsoft’s chief marketing officer for AI at Work. “We’re rapidly adding new capabilities to tackle individuals’ biggest pain points at work and drive real business results.”

What are agents, anyway?

An agent takes the power of generative AI a step further, because instead of just assisting you, agents can work alongside you or even on your behalf. Agents can do a range of things, from responding to questions to more complicated or multistep assignments. What sets them apart from a personal assistant is that they can be tailored to have a particular expertise.

For example, you could create an agent to know everything about your company’s product catalog so it can draft detailed responses to customer questions or automatically compile product details for an upcoming presentation.

Other agents can do even more, acting on your behalf, like one that helps fulfill sales orders — freeing you up to focus on building new customer relationships. Having agents handle some of these routine needs can boost productivity across industries, from manufacturing and research to finance and retail, helping businesses save time and money.

You can use ready-made agents in Microsoft 365 and Dynamics 365, or build custom agents to help with more specific needs in Copilot Studio.

Imagine you’re a salesperson with big quarterly goals to meet. Copilot acts as your personal assistant, drafting emails, recapping a meeting you missed and helping you design a polished sales presentation. Meanwhile, an agent specialized in sales lead generation works autonomously in the background to find new prospects you can follow up with later in the week. Copilot partners on daily tasks, and your purpose-built agent uses its customized skills to help you meet your end-of-quarter goals.

AI agents are not only a way to get more value for people but are going to be a paradigm shift in terms of how work gets done.

Agents are not new. Microsoft has done extensive research in the area and even created a multi-agent library last year for developers around the world, work that helped shape what agents can do today.  They’re getting more attention now because recent advances in large language models (LLMs) help anyone — even outside the developer community — communicate with AI. That agent-LLM duo makes AI tools more tangibly useful.

“People expect AI to do things for them,” not to just generate language, says Ece Kamar, the managing director of Microsoft’s AI Frontiers Lab. “If you want to have a system that can really solve real world problems and help people, that system has to have a good understanding of the world we live in, and when something happens, that system has to perceive that change and take action accordingly.”

Agents are like layers on top of the language models that observe and collect information, provide input to the model and together generate an action plan and communicate that to the user — or even act on their own, if permitted. So both agents and models are equally important pieces of the puzzle, as far as generative AI tools go.

Agents will become more useful and able to have more autonomy with innovations in their three necessary elements: memory, entitlements and tools.

Memory helps provide continuity so that each time you ask for something, it isn’t like starting from scratch.

“To be autonomous you have to carry context through a bunch of actions, but the models are very disconnected and don’t have continuity the way we do, so every prompt is in a vacuum and it might pull the wrong memory out,” says Sam Schillace, Microsoft’s deputy chief technology officer. “It’s like you’re watching a stop-motion animation, one isolated frame after another, and your mind puts it into motion. The clay model doesn’t move on its own.”

To build up the memory infrastructure to address this, Schillace and his team are working on a process of chunking and chaining. That’s essentially what it sounds like: They’re experimenting with dividing up interactions in bits that can be stored and linked together by relevance for faster access, akin to a memory — like grouping conversations about a certain project so an agent can recall those details when you ask for a status update and not have to search through its entire database.

The work with entitlements and tools is making sure agents have secure access to, or are entitled to, information they need in order to accomplish things for you, with your permission — like who your boss is, for example — and to the computer programs they need to take action on your behalf, like Teams and PowerPoint.

How to use and build agents for work

You can already create and publish agents in Microsoft 365 Copilot that can help you in your daily work as easily as you’d create a spreadsheet or presentation — no coding skills required.

You don’t need to be a developer to build agents using Copilot Studio, either. Anyone can connect them to relevant business data such as emails, reports and customer management systems so they can perform tasks and provide insights.

And you’ll soon be able to enlist new agents in Microsoft 365 to help with common workflows and tasks. Interpreter in Teams will provide real-time speech-to-speech translation during meetings, for example, and you can opt to have it simulate your voice. The Employee Self-Service Agent will simplify human resource and IT help desk-related tasks like helping workers resolve a laptop issue or find out if they’ve maxed out certain benefits, and it can connect to company systems for further customization in Copilot Studio.

Microsoft Dynamics 365 will have agents as well for a range of common business workflows across sales, supply chain, finance and customer service functions.

And every SharePoint site will soon come equipped with an agent tailored to your organization’s content that allows employees to quickly tap into these vast knowledge bases and find exactly what they need in seconds, whether it’s project details buried in a workback schedule or a summary of a recent product memo.

Developers have even more options. With the new Azure AI Agent Service, you’ll be able to choose from small or large language models to orchestrate, develop and scale agent-powered apps to streamline and automate complex workflows like order processing and customer data synchronization. It provides a software development kit with tools for developing agents, allowing you to efficiently integrate agent capabilities using Visual Studio Code and GitHub.

One type of model, OpenAI’s recently announced o1 series, can bring more advanced reasoning capabilities to agents, allowing them to take on more complicated tasks by breaking them down into steps — like getting the information someone on an IT help desk would need to solve a problem, factoring in solutions they’ve tried and coming up with a plan.

You can also use the power of agents in LinkedIn; the platform’s first agent can help recruiters with hiring.

Assessing risk for autonomous action

There are extra safety considerations with agents that can act autonomously, and Microsoft is focused on making sure agents only access what you want them to, says Sarah Bird, the company’s chief product officer of Responsible AI.

“Agents certainly up the stakes from a responsible AI point of view,” Bird says. “So we have to have much, much lower error rates. And there’s many more nuanced ways in which something could be an error. This is the big challenge with agents.”

But the same responsible AI foundational playbook for other AI applications can be used to assess and mitigate risk with agents, she says.

The new Copilot Control System helps IT departments manage Copilot and agents with data access and governance, management and security controls, as well as measurement reports and tools to track adoption and business value.

Many agents, like those created for Microsoft 365 and Dynamics 365, include “human in the loop” approvals, where people are required to take the final step of reviewing and sending an email the Sales Order Agent wrote, for example. And for agents developed in Copilot Studio, authors can review the records to see which actions the agent took and why.

The key is to focus on testing and moderating to ensure accuracy, Bird says, and for organizations to choose the right starting point for their needs.

“We will of course make progress by building on the foundation we already have, so we’re starting the journey from a strong place,” Bird says.

Looking back — and into the future

Technologists have long been excited by the idea of autonomous systems working side-by-side with people to help them, says Kamar, who has been working on AI agents since 2005 and even wrote her Ph.D. thesis on the topic in 2010. The hurdle was that “we lacked that general problem-solving power” on the back end, she says.

With LLMs, “we finally have this missing component,” she says. “Now we can bring back a lot of the ideas from our decades of research.”

Going forward, Kamar envisions a new ecosystem or marketplace of agents, sort of like how apps empower people to do more with their smartphones.

Agents already have “the basic building blocks of what it takes to complete a task,” she says. “Like observing, ‘I can see your meeting is taking longer; I should delay the next meeting.’”

They’re getting more helpful as they gain autonomy through the innovations in memory and entitlements. They’re relieving pain points for employees by helping with things like expense reporting, project management and meeting facilitation. And they’re driving exponential impact for businesses by taking on duties like alerting supply chain managers to low inventory and then automatically reordering to help drive sales and keep customers satisfied.

Agents matter because they “open up a whole set of opportunities for working with people for getting tasks done, and that’s what we expect from AI systems,” Kamar says. “AI agents are not only a way to get more value for people but are going to be a paradigm shift in terms of how work gets done.”

And this is just the beginning. Copilot is set to evolve with new capabilities like Copilot Actions, designed to handle routine tasks that can bog down employees like summarizing emails missed during time off, compiling agenda items and generating monthly reports. More capabilities like these are coming over the next year to lift the weight of work for employees and teams.

“Copilot will empower every employee to do their best work in less time, and focus on more meaningful tasks,” Spataro says. “And agents created in Copilot Studio will transform every business process, helping companies streamline operations, enhance collaboration and drive innovation at scale.”

Illustrations by Michał Bednarski / Makeshift Studios

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Germany stands at the forefront of a new era in AI, where strategic investments, public-private partnerships, and a focus on sustainable innovation converge to shape the future of industry and society. With significant governmental investment and growing adoption across key sectors, AI is poised to become a cornerstone of Germany’s economic transformation, ensuring global competitiveness and addressing critical labor shortages. 

The country’s rapidly advancing AI capabilities have been supported by significant investments and partnerships, with Microsoft playing a pivotal role. Earlier this year, Microsoft announced a €3.3 billion investment in Germany to expand its AI and cloud infrastructure over the next two years.¹ This initiative aims to double the AI infrastructure in the country and includes efforts to establish new datacenters in regions like North Rhine-Westphalia and Frankfurt, supporting key industries such as pharmaceuticals and energy through low-latency services. Microsoft is also focusing on sustainable operations, planning to power these facilities with renewable energy sources by 2025. 

In alignment with Germany’s broader national AI strategy, Microsoft has emphasized the importance of equipping workers with AI expertise, aiming to train up to 1.2 million people in new digital and AI capabilities by 2025.² This effort addresses labor gaps in sectors such as healthcare and manufacturing, which are adopting AI to increase efficiency and reduce operational costs. 

The recent Microsoft AI Tour event in Berlin, Germany, featured several innovative Germany organizations leveraging AI to advance to the cutting edge of their industries. Spanning from higher education to travel and manufacturing, these organizations present inspiring case studies and represent the tip of the iceberg in terms of what is possible at the intersection of German ingenuity and Microsoft AI technology.  

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IU International University of Applied Sciences (IU) prepares students for the future of work with AI-powered education  

IU International University of Applied Sciences (IU), Germany’s largest and fastest-growing university with more than 130,000 students, is using AI to advance its mission of democratizing higher education globally through a hybrid model of on-campus and online studies. By using the power of Microsoft Azure OpenAI Service, the university developed Syntea, an AI avatar integrated into Microsoft Teams and Microsoft 365 Copilot, making learning more personalized, autonomous, and flexible.   

Syntea’s impact has been profound, driving a 27% reduction in the time students need to complete online courses. In addition, IU is testing a new model within Syntea’s exam trainer function to improve grading while upholding its same high-quality standards and ensuring the solutions to be dependable. These innovations enhance the quality of education while making it more accessible and equitable. 

To further equip students for an AI-powered future, IU partnered with Microsoft to create the IU Copilot School featuring Microsoft. With the IU Copilot School, every student gains access to Microsoft 365 Copilot and in the future seamlessly to Syntea, fostering familiarity with AI tools that will shape tomorrow’s workforce. This initiative ensures AI is embedded across all study programs, preparing graduates to excel as knowledge workers in the evolving job market.   

Looking ahead, IU’s team of developers is exploring ways to extend the way of exam grading by leveraging the next generation of Syntea with advanced AI agents. IU’s Syntea Newskilling project leverages the power of AI-driven mentorship to redefine workplace learning and development by seamlessly integrating personalized upskilling and onboarding journeys directly within Microsoft Teams, empowering employees to achieve both individual and organizational success.

By seamlessly integrating AI into education and workforce preparation, International University of Applied Sciences (IU) is setting a bold precedent for how technology can redefine learning and unlock new opportunities for students and professionals alike. 

thyssenkrupp Automation Engineering alleviates labor shortage with Siemens Industrial Copilot 

Siemens and Microsoft have elevated the Siemens Industrial Copilot, now leveraging Azure OpenAI Service to meet rigorous manufacturing and automation demands at scale. The Industrial Copilot combines Siemens’ specialized industry expertise with advanced generative AI to address complex requirements, bringing new levels of efficiency and precision to industrial processes. 

thyssenkrupp Automation Engineering, a co-creation partner and one of more than 100 companies using the Siemens Industrial Copilot, plans to expand its use globally. The Industrial Copilot plays a critical role in thyssenkrupp’s response to the skilled labor shortage affecting Europe and the United States, enabling smoother operations even with less-experienced staff. 

A standout application is in thyssenkrupp’s battery quality systems, where the Industrial Copilot supports automated processes for battery assembly lines—key to the sustainable energy transition. For electric vehicle batteries, for example, the Industrial Copilot integrates sensors, cameras, and measurement systems to monitor quality at each production stage, detecting any issues that could affect reliability. By automating data management, sensor configuration, and stringent reporting requirements, the Industrial Copilot ensures precision in quality control, freeing engineers to focus on higher-value tasks. Additionally, the Industrial Copilot’s real-time problem-solving and documentation capabilities reduce downtime, while making machinery easier for early-career and unskilled workers to operate effectively.

Recognizing that technology oftentimes outpaces the machinery market, thyssenkrupp Automation Engineering is now the first to plan to use the Industrial Copilot globally, not only addressing labor challenges and advanced automation demands company-wide, but enabling their machines to keep pace with change into the future. 

Read more

• How AI is helping Siemens and thyssenkrupp bridge skilling gaps in manufacturing
• Siemens and Microsoft scale industrial AI

Ottobock revolutionizes prosthetics with AI for greater quality of life 

In pursuit of their mission to empower people with disabilities to move freely and independently, Ottobock is transforming individualized prosthetics and orthotics with the power of AI. For over a century, the company has faced a persistent challenge within the prosthetics and orthotics industry: achieving a perfect fit of body interfaces such as sockets or braces.   

With the help of the Microsoft Azure platform, Ottobock now analyzes detailed images of body parts to create customized body interfaces. This approach not only improves the precision and comfort of their devices, making high-quality solutions accessible to a broader range of patients, but also accelerates production while reducing costs. The streamlined process has further enabled less experienced technicians to deliver consistent, standardized products—helping alleviate the industry-wide shortage of skilled orthopedic technicians.   

Building on these successes, Ottobock is actively exploring additional AI applications to enhance the patient experience. With the potential of self-learning prosthetics on the horizon, Ottobock continues to elevate the quality of life for users by combining cutting-edge technology with compassionate care.

Lufthansa elevates customer experience and streamlines operations with AI-powered solutions  

Lufthansa Group continuously explores new ways to enhance premium travel experience of its passengers. This includes exploring possibilities of using generative AI. For example, in the Lufthansa Group Digital Hangar, an animated 3D avatar was developed as part of a test, guiding passengers from initial travel inspiration to flight booking through an exchange with an Avatar in natural language. Additionally, with the help of Microsoft’s generative AI, other applications were implemented, such as expanding the chat assistant, processing compensation claims, and automating website content creation.

Otto Group scales AI innovation, transforming e-commerce and healthcare 

Otto Group and its subsidiaries are harnessing the power of AI to accelerate innovation across industries. Group company OTTO has rolled out GitHub Copilot and the entire GitHub Platform for all software developers. This has enabled the teams to work numerous AI use cases simultaneously, which are used in e-commerce, live shopping, and by various subsidiaries of the Otto Group. One standout success is at Medgate, Otto Group’s leading telehealth subsidiary, which leverages AI-powered Copilot technology to address Germany’s healthcare challenges.   

Medgate developed a medical Copilot that transforms physician workflows and elevates patient care. Leveraging a custom-trained Azure speech and Azure OpenAI model, the Copilot summarizes consultations, supports triage, and provides real-time translations. In a medical chat powered by Azure OpenAI Service, physicians can enter keywords to generate follow-up questions and treatment recommendations. With this solution, Medgate reduces physicians’ administrative workload, giving doctors more time to focus on patient care—a critical advantage amid Germany’s shortage of 50,000 doctors and rising healthcare costs, which account for 12.8% of the nation’s GDP.   

The impact is measurable: case documentation times are cut by 10 to 20%, and AI-generated prompts reduce message drafting time by up to 40%. More than 60% of these AI-generated responses are utilized by doctors, demonstrating high acceptance and trust.

Otto Group’s successful integration of AI extends beyond Medgate, with the GitHub Cloud Platform enabling secure, scalable AI deployments across the Otto Group’s diverse operations. As Otto Group continues to lead in AI innovation, it exemplifies how technology can enhance both business performance and essential public services, driving meaningful impact across industries.

AI for everyone in Germany

As Germany cements its position as a global leader in AI, the ingenuity of its organizations continues to shape industries through transformative AI applications. From advancing education with AI-powered tools at IU International University of Applied Sciences to modernizing manufacturing at thyssenkrupp and enhancing healthcare services through Otto Group’s Medgate platform, these enterprises exemplify how AI can drive progress while addressing societal challenges.  

Microsoft’s investment in AI infrastructure and skilling reflects a long-term commitment to strengthening Germany’s digital capabilities and a shared goal to empower businesses and workers while fostering innovation that aligns with environmental sustainability and data security standards. Together, they are driving a future where AI not only serves as a tool for competitive advantage but also as a force for good—ensuring that Germany’s AI ecosystem becomes a model of innovation, resilience, and responsible development.

Find the resources to support your AI journey 

• Explore Microsoft’s AI solutions.
• Catch up on core concepts with AI Office Hours.
• Read the guide: An Introduction to Generative AI and Safety.

¹ The Federal Government, Investing in the digital future: Microsoft invests billions in Germany as an AI hub, February 15, 2024.

² Deutsche Welle, Germany: Microsoft to invest €3.3 billion in AI capacities, February 15, 2024.

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If you’ve read The AI Strategy Roadmap: Navigating the stages of value creation, you’re already familiar with the five drivers of AI value. This research paper and blog series explore what organizations need to succeed with AI, including establishing a clear strategy and securing senior leadership support. Our research found that AI success isn’t solely about technology—strategic, organizational, and cultural factors are equally critical.

We’ve heard from customers that it’s crucial to consider how prepared your organization is for this technological leap. In this blog post, we’ll share some learnings to help you gauge your AI readiness so you can plan how to move forward effectively.

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Assess your AI readiness

When I meet with customers, they often share that they’re not sure where to start when it comes to assessing their readiness for large-scale AI transformation. It requires a strategic approach to understand your current capabilities, identify areas for improvement, and align these efforts with your business priorities to focus on the areas that will deliver the highest value. We’ve created a new AI Readiness Wizard to help you get started in evaluating your preparedness. Use the assessment to:

• Evaluate your current state. The assessment includes questions that help you determine how well your AI objectives align with your business priorities and the effectiveness of your current data access and security measures. Understanding your starting point is essential for identifying the right next steps.
• Identify gaps. By scoring your responses in the assessment, you can identify focus areas that may need more attention, such as business strategy, AI governance principles, or team expertise. This step helps prepare you for formulating a clear path forward and addressing specific areas for improvement.
• Plan your next steps. Based on your scores, the assessment categorizes your readiness into one of five stages: exploring, planning, implementing, scaling, or realizing. Each stage represents a different level of AI maturity and preparedness, guiding you on where to focus your efforts:
  • Exploring—At this stage, focus on building your AI strategy and experience. You might want to learn about key AI concepts and explore how AI is transforming the business landscape.
  • Planning—Here, you’ll concentrate on formalizing your business strategy. Look at the ways other organizations are driving value with AI and develop an informed plan for prioritizing AI projects.
  • Implementing—This stage involves focusing on leadership support and scaling AI expertise. Ensure you have the necessary resources and expertise to execute your AI initiatives effectively.
  • Scaling—At this level, you’ll aim to create an organization and culture of innovation. Scale your AI initiatives and begin analyzing the impact of AI in your organization.
  • Realizing—Focus on fostering continuous innovation within every team and the organization. Aim to embed AI technology in your operations and culture for sustained value creation.

Assessing your AI readiness requires a strategic approach to understand your current capabilities and identify areas for improvement.”

This assessment offers a structured way to reflect on your current practices and identify key areas to focus on as you develop your strategy for the future. You’ll also find resources for each stage to help you advance.

How AI is reshaping industries

Financial services

We’re seeing the financial services sector make rapid advancements in AI readiness, with 40% of organizations currently in the “implementing” stage. According to recent research, 70% of financial services organizations are using big data analytics in their operations, and 27% have piloted AI applications or AI-assisted solutions.

Additionally, more than half are allocating budgets for AI projects, providing AI-specific training, and fostering internal knowledge sharing. This commitment has enabled 27% of firms to reach the “scaling” and “realizing” stages, surpassing the 25% industry benchmark.

Healthcare

The healthcare industry shows a diverse mix of AI readiness, with 28% of organizations in the “scaling” and “realizing” stages, according to one study. Notably, 44% are actively laying the groundwork in the “exploring” and “planning” stages, focusing on learning and developing their AI strategies. The sector leads in overall maturity, but 14% of organizations report receiving no discernible value from AI, highlighting challenges in measuring the impact of AI investments within their broader business strategies.

Manufacturing

With 38% of organizations in the manufacturing industry still in the “exploring” and “planning” stages, many are focused on learning and developing AI strategies. Research shows that manufacturers actively deploy AI across operations, research and development (R&D), and supply chain management to address key business challenges. 25% believe they achieve significant value from AI implementation.

Manufacturing organizations also have a greater likelihood of appointing AI leadership, which we’re learning enables them to excel in fostering the operational and cultural factors that support value creation, resulting in more firms reaching the “realizing” and “scaling” stages.

Retail

We’ve seen a wide range of AI readiness in the retail sector. While some retailers use AI to enhance customer relationships and drive revenue, research shows that 43% are still in the “exploring” and “planning” stages. This divide is evident between those who adopted cloud technology early—about 25%—and those who have yet to embrace it, with 8% still not using cloud services. Notably, 21% of retailers have a chief AI officer, highlighting commitment among leadership to embed AI into their operations.

Map your AI journey

After assessing your readiness and gathering insights, you’ll want to outline a plan to address gaps and advance through the stages of AI maturity. Our findings at Microsoft have shown that crafting a strategic plan outlining how AI technology will fit into your organizational framework is a great place to start. The AI Strategy Roadmap: Navigating the stages of value creation is a valuable resource designed to guide you through this process.

As you define your AI strategy and roadmap, you might find our e-book, Building a Foundation for AI Success: A Leader’s Guide, helpful in identifying key focus areas for AI implementation.

The post A strategic approach to assessing your AI readiness appeared first on The Microsoft Cloud Blog.

As various industries and different markets continue to adopt AI, its impact at the local level is also increasingly evident. Recently, the Microsoft AI Tour event in Mexico City highlighted the variety of ways in which AI is enabling Mexico to become a premier innovation hub.

Last year, Microsoft unveiled our vision for AI transformation, and we are already witnessing how AI is revolutionizing businesses and delivering tangible outcomes. As we continue to embrace AI transformation, our mission to empower every person and organization on the planet to achieve more is clear and attainable.

Chairman and CEO Satya Nadella announced that Microsoft Corporation is reaffirming its commitment to Mexico with a new investment of $1.3 billion over the next three years. This investment aims to enhance AI infrastructure and promote digital and AI skills through initiatives like the Artificial Intelligence National Skills program, which seeks to democratize access to AI skills and reach 5 million people. The investment will also focus on improving connectivity and encouraging AI adoption by small- and medium-sized businesses to accelerate their digital transformation and business operations within the country.

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Mexico is poised to become a regional leader in leveraging AI solutions as key drivers of business innovation across sectors. The potential seen in the country is further showcased by the recent availability of a new datacenter region built in Querétaro. Through the joint work of Microsoft, its partners, and cloud-using customers, it’s expected to create more than 300,000 jobs over the next four years.¹Microsoft, celebrating its 38-year presence in Mexico, recognizes AI’s role as a catalyst for social and economic growth. The company is expanding its AI infrastructure in Mexico, involving a significant investment to increase local computing capacity and encourage innovation.

Cemex leverages AI to enhance operations, productivity, and customer experiences

As a global leader in building materials, Cemex continues to focus on developing innovative and sustainable construction solutions. Partnering with Microsoft, Cemex initiated a journey to leverage AI capabilities that enhance productivity and reinvent customer experiences.

Cemex joined the Microsoft 365 Copilot Early Access Program, which integrated generative AI into their operations, allowing employees from different areas and roles to increase their productivity and efficiency. Additionally, Cemex’s developers have further immersed themselves into AI by utilizing GitHub Copilot to extend the possibilities the technology brings to different business areas through specific applications. This vision is reflected in Cemex Go, the company’s End- to End commercial platform which consolidates commercial processes and order tracking to enable more agile and intelligent order and purchase management. Customers can navigate the company’s solutions catalog in a more intuitive manner through an optimized user experience. 

Cemex also introduced Technical Xpert, a generative AI-powered tool built internally using Microsoft Azure OpenAI Service, as one of a series of knowledge assistants to revolutionize its sales process. Technical Xpert provides sales agents with instant access to comprehensive product and customer solution information, significantly reducing search time by 80%.  

Grupo Bimbo embraces AI with “Copilot for All” strategy

Recognizing the potential of AI to enhance productivity and operational efficiency, Grupo Bimbo—the world’s largest baking company (in Spanish)—has partnered with Microsoft to integrate advanced AI solutions into its operations.

Grupo Bimbo’s initial AI strategy, branded “Copilot for All,” empowers 3,500 corporate associates across various departments, including human resources (HR), sales, and procurement, to leverage AI. By utilizing Microsoft 365 Copilot, they improved efficiency in tasks such as content creation and process management. Leveraging Microsoft Copilot Studio, they created two unique Copilots to address specific business areas. The Internal Control & Risk Management Copilot consolidates nearly 200 internal policies. This tool promotes compliance with Grupo Bimbo’s policies which apply to all Bimbo collaborators across the 34 countries where the company operates.

They also developed the Procurement Copilot, which extracts data from various sources to provide answers without users having to perform the analysis themselves. This further consolidates operations by automating data extraction and policy management.

Simultaneously, Grupo Bimbo is deploying Microsoft’s industrial AI technologies to modernize its manufacturing processes. This includes implementing AI assistants at key facilities in the US and Mexico to optimize production and reduce downtime. The collaboration aims to enhance asset reliability and worker safety while establishing a unified, data-driven framework across factories.

The integration of Microsoft’s cutting-edge AI services is expected to drive significant cost savings, improve operational efficiency, and empower global innovation.

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Capgemini accelerates Mexico’s AI transformation

Capgemini Mexico is part of the global Capgemini Group, a worldwide leader in consulting and digital transformation that employs more than 340,000 professionals. In Mexico, the company has responded to rising IT service demands by integrating advanced technologies like cloud computing, data analytics, AI, and digital engineering.

At Capgemini Mexico, developers have embraced and integrated GitHub Copilot throughout the software development lifecycle to significantly accelerate the development process—from planning and coding, to testing and development. By taking this approach, they ensure high-quality, customizable software solutions. The use of generative AI addresses some of the major challenges in software engineering by speeding up development phases, enhancing product quality, and reducing time to market.

Capgemini Mexico has been impressed with GitHub Copilot’s ability to support scalable AI implementations, which has led to improved customer experiences and increased efficiency. Their north star is to have all software engineers leverage Generative AI, which offers new opportunities for Capgemini’s partner ecosystem, and drives growth and innovation in the software engineering field. You can read more on their use of generative AI for software engineering.

APEC uses AI to advance Retinopathy of Prematurity diagnostics

Retinopathy of Prematurity (RoP) is a serious eye condition and the leading cause of blindness in newborns in Mexico. Microsoft Mexico, in collaboration with Business Data Evolution and the Asociación Para Evitar la Ceguera (Association to Prevent Blindness-APEC), a leading institution in ophthalmology in Mexico dedicated to the prevention and treatment of visual diseases, are tackling this medical condition through a groundbreaking AI-powered diagnostic tool.

Leveraging Microsoft Azure cloud and deep neural network algorithms based on machine learning, APEC developed an app that enables healthcare providers to capture retinal images or videos of a baby’s eye using a smartphone camera. Azure AI uses the collected images to train the algorithm to recognize common patterns among affected eyes and identify signs of RoP. The app has significantly increased the accuracy of identifying the condition to 90%—well beyond the human capability of 60%.

This mobile app also means greater access to advanced diagnostics in rural areas where ophthalmologists are scarce. It also provides a platform for training future specialists to help reduce blindness rates and enhance the overall efficiency and reach of medical care in Mexico. The goal is to offer a free service accessible globally, which can positively impact you. You can watch a video on the solution here: APEC in Mexico creates algorithms based on Microsoft Azure AI to prevent blindness in newborns.

Tecnológico de Monterrey’s empowers educators and students with AI-powered resources

Founded in 1943, Tecnológico de Monterrey is a leading private institution in Latin America with more than 60 campuses and a student body of 90,000.

The institution launched TECbot, a virtual assistant which provides all day support for its educational offerings. Recognizing the need for more advanced capabilities, they then created TECgpt, a marketplace for AI-powered tools that enables educators and students to access tailored resources, from library assistance to physics tutoring. By integrating the solution with Skills Studio, it can also generate educational content and problem-solving examples. The implementation was developed utilizing Microsoft’s Azure platform and generative AI technologies.

TECgpt continues to expand Tecnológico de Monterrey’s IT capabilities. They’ve enhanced operational efficiency to enrich the teaching-learning process, and improved feedback quality with an eye on the next generation of scholars. You can learn more about this case here: Discover TECgpt.

AI for everyone in Mexico

AI is enabling companies and individuals to transform their activities by reshaping processes and opening new paths towards development. From students to health professionals, and across diverse industries, it has been inspiring to see the creativity and ingenuity that Mexico’s organizations showcase in harnessing AI and cloud solutions to tackle real-world challenges and open new opportunities. These initiatives are only a few examples of Microsoft’s commitment to empower Mexican organizations through the latest technological solutions. I am eager to see how they will continue to leverage the limitless potential of AI and enable their own success.

Find the resources to support your AI journey

• Explore Microsoft’s AI solutions

• Download the AI readiness worksheet

• Continue your AI learning journey
• Read An Introduction to Generative AI and Safety

¹Microsoft launches its first hyper-scale cloud datacenter region in Mexico – News Center Latinoamérica.

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At the heart of this initiative are industry prompts in Copilot Lab and industry templates in Microsoft Copilot Studio—two platforms tailored to meet the unique demands of various businesses. These platforms are not just about providing tools; they’re about delivering a seamless experience that aligns with our customers’ operational workflows, enhancing productivity and fostering creativity.

Copilot Lab serves as a portal for innovation, offering diverse industry prompts that cater to the specific needs of job functions and industries. Getting up to speed on AI prompts can be challenging from both a technical and practical standpoint. If AI prompts are vague or lack necessary details, AI models can produce off-target responses. Copilot Lab provides a repository of prompts that resonate with industry professionals, enabling them to generate meaningful outcomes with Microsoft Copilot’s assistance.

Copilot Studio includes industry copilot templates that can simplify the adoption process for businesses. These templates incorporate industry-specific business logic and custom prompts that streamline operations and decision-making processes. These templates, available in the Copilot Studio Gallery, represent fully working copilots that often only require configuration or integration for an organization to adopt them.

As we continue to build and co-create, our vision is to not only enhance the capabilities of Microsoft Industry Clouds but also to help redefine the way industries operate. By providing accelerators that drive mainstream adoption and co-building with industry partners, we’re setting a new standard for industry solutions.

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Industry AI prompts in Copilot Lab

In our continuous pursuit of empowering organizations across various industries, Microsoft has introduced a suite of industry-specific prompts within Copilot Lab. These prompts are a culmination of our efforts to provide a more context-aware AI experience that leverages users’ domain expertise to drive better outcomes. Our new industry prompts help customers quickly get started using Copilot for sector, job, and role-specific scenarios and can be customized with domain-specific details, best practices, and industry context to reduce trial and error and ensure high-quality output. These prompts can create an interactive experience for sector-, job-, and role-specific users, which can enhance prompts and deliver tailored responses, continually improving based on user interactions.

The genesis of these prompts was a collaborative effort, drawing on insights from industry professionals to ensure quality and relevance. The initiative begins with the financial services, retail, and manufacturing industries, introducing 24 industry-specific prompts within Copilot Lab, marking the start of a broader vision to integrate industry-specific intelligence into business operations.

These prompts are readily accessible in Copilot Lab, where users can select prompts that resonate with their professional needs. They are designed to help users ask relevant and specific questions, enabling Copilot to generate insights from data that are finely tuned to their industry’s nuances.

The introduction of these prompts is part of our broader vision to bring industry-specific intelligence to the forefront of business operations. By providing these tailored tools, we aim to enhance productivity and foster innovation within the Microsoft 365 environment.

Accessing these prompts is simple. Within Copilot Lab, a collection of pre-built prompts categorized by industry. Users can select the one that fits their role, and let Copilot do the rest. Users can further customize the prompts with domain-specific details and best practices.

Industry copilot templates in Copilot Studio

Industry copilot templates in Copilot Studio help users streamline the adoption of AI solutions across various sectors, providing pre-built dialogs, intents, entities, prompts, and actions that can be easily customized and extended according to the user’s needs using a low-code/no-code experience.

The templates offer a quick and efficient way to get started with AI, with configurations and rollout typically taking only a few hours. They include publicly accessible and customizable data sources, allowing customers to change the default data source with their own to get the copilot ready for business. This feature is particularly beneficial for industries that require rapid deployment and flexibility, such as retail and sustainability.

For instance, the sustainability insights template in Microsoft Copilot Studio empowers users with easy access to data and insights regarding a company’s sustainability goals and progress, while the Copilot template for store operations is designed to enhance the efficiency of retail frontline workers by providing easy access to store procedures and policies. These templates were part of the Microsoft Copilot template gallery unveiled at Microsoft Build 2024 and represent Microsoft’s commitment to empowering users with AI tools that are both powerful and adaptable to their specific industry needs.

Copilot Studio is available worldwide, across 22 datacenters, and supports multi-lingual experiences, making it a versatile tool for global enterprises. The studio’s capabilities are continually expanding, with support for 23 languages and growing, helping to ensure that users can build solutions and respond in their preferred language.

For more detailed information on how to utilize these new features and to stay updated on future releases, users can refer to the resources provided by Microsoft Copilot Studio.

Learn more about industry-specific AI tools

Microsoft remains dedicated to empowering customers through innovation. Our latest offerings in Copilot Lab and Copilot Studio reflect our commitment to providing industry-specific AI tools that are not only powerful but also intuitive and accessible. By continually investing in these technologies, we aim to help ensure that organizations, regardless of size or sector, can harness the full potential of AI to drive efficiency, creativity, and growth.

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Get started by exploring detailed guides and information on our industry prompts and templates at Copilot Lab and Copilot Studio. Learn more and stay informed about Microsoft’s advancements in AI by exploring Copilot for Microsoft 365 Tech Community Blog and the Microsoft Industry Blog for insightful articles, or discover more at Copilot learning hub. Together, let’s shape the future of industry innovation with AI.

The post Innovating at the speed of AI: Microsoft’s industry Copilot solutions appeared first on The Microsoft Cloud Blog.

1. Amplify human ingenuity with a copilot for everyone: Offering built-in and extensible AI capabilities in Microsoft Copilot to help people be more productive, creative, and efficient.
2. Deliver transformational experiences with build-your-own intelligent apps: Making it easy for customers and partners to build their own copilot solutions using the same stack and AI services Microsoft used to build its own copilots.
3. Safeguard business and data with a trusted AI platform: Microsoft has demonstrated leadership and delivered powerful tooling to help build safety and responsibility into AI solutions from the start—this includes guidance and best practices around responsible AI as well as secure AI principles that empower organizations with an end-to-end cyber risk approach that reinforces human control.

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Part of enabling customers to adopt AI and deploy copilots includes empowering partners. Microsoft helps partners benefit from its unified data estate platform to create personalized, role-specific AI that can empower customers with meaningful and relevant experiences. Copilots can enhance development capabilities and allow partners to share the value of their domain experience with customers, reinforcing their commitment to innovation and excellence. Partners can extend and customize existing copilots from Microsoft or modify how copilots assist with core business functions, such as human resources, sales, or customer service interactions.

Building with partners

Partners play a crucial role in extending Microsoft’s offerings to customers with their domain expertise. When tailored to specific roles, copilots can personalize generative AI experiences, offering access to relevant business flows and data, when and where users need it.

The partners featured here have created copilots and AI platforms that support a wide range of industries and lines of business:

• TomTom has created its Digital Cockpit to turn cars into conversational companions.
• Modern Requirements has created an AI work item and requirements management assistant for healthcare, finance, automotive, aerospace, government, and defense industries.
• Dynatrace has developed Davis® AI which empowers countless use cases, supporting Microsoft Azure customers in areas like observability and security.
• Intellect Design has developed generative AI-powered copilot which allows a relationship manager to generate valuable insights from ISO 20022 payments repository data thereby helping corporations manage their funds better.
• Datamatics has created a partner onboarding copilot to help streamline and reduce the time spent on the onboarding process for vendors, partners, and more.
• MiHCM has developed an AI-powered human resources (HR) copilot called MiHCM SmartAssist.

TomTom

The TomTom Digital Cockpit is an open, modular in-vehicle infotainment platform. Their new AI-powered voice assistant enables users to engage in natural conversation with their cars and tackle complex driving requests. The voice assistant can handle follow-up questions and maintain contextual understanding, which means users can engage in multi-turn conversations and get relevant responses.

Key features include:

• AI-powered voice interaction: The digital cockpit enables natural voice communication with the vehicle, allowing drivers to control navigation, infotainment systems, and vehicle settings through voice commands.
• Integration with Microsoft Azure: TomTom utilizes Microsoft Azure OpenAI Service, Azure Cosmos DB, and Azure Kubernetes Service to provide a robust and scalable infrastructure, supporting advanced data handling and AI capabilities that enhance responsiveness and personalization.
• Customizable user interface: Automotive manufacturers can customize the digital cockpit to match their brand’s aesthetics and functionalities, making it adaptable to different vehicle models and consumer preferences.
• Cost efficiency: The system offers a cost-effective solution that reduces development expenses by up to 80%, providing a sustainable and economically viable option for car manufacturers.

Modern Requirements

Copilot4DevOps Plus is an AI-powered work item and requirements management assistant, which can be utilized by multiple industries such as healthcare and medical devices, finance, automotive, services and technology, aerospace, government, and defense. This tool, seamlessly integrated with Azure DevOps, optimizes requirement workflows with an easy-to-use interface and improves the requirements management process by enabling several key functions:

• Efficiency and productivity: It allows teams to focus on meaningful work by automating repetitive tasks and improving collaboration. In addition to powerful AI elicitation, analysis, conversion, and summarization, it gives teams cutting-edge features like pseudocode generation, dynamic prompts, and test script creation.
• Enhanced quality and security: Copilot4DevOps improves the quality of requirements by analyzing and refining them according to best practices in technical writing. It also incorporates Microsoft and OpenAI’s latest security features to help ensure data security.
• User control and customization: Users have the final say over the AI-generated content, with options to pick, edit, and refine outputs as per their specific needs.

Copilot4DevOps Plus is available as an add-on with Modern Requirements4DevOps or as a standalone in the Azure and Visual Studio Marketplaces.

Dynatrace

The Dynatrace platform delivers AI-enhanced cloud observability, security, and overall operational efficiency for global enterprises across all industries. With Davis® AI copilot, Dynatrace combined its predictive and causal capabilities and generative AI, built with Azure OpenAI, to bring Dynatrace Davis® hypermodal AI to market. This boosts the technical capabilities of IT teams by simplifying complex processes, enabling businesses to focus more on innovation and less on operational management.

Key features include:

• Davis® AI Engine: This core component leverages predictive, causal, and generative AI to provide deep insights and actionable recommendations. It automates tasks like anomaly detection, root cause analysis, and workflow automation, significantly reducing the manual effort required in managing complex IT environments.
• Predictive operations: The platform predicts potential issues before they impact operations using AI to forecast and automate responses, thereby ensuring reliability and proactive management of IT systems.
• Intelligent observability: Dynatrace uses AI to analyze real-time data across applications, services, and infrastructure. This helps in pinpointing issues quickly and accurately, which is crucial for maintaining optimal operational performance.
• Automation and integration: The platform’s automation capabilities extend to auto-discovery, auto-instrumentation, and auto-baselining, ensuring comprehensive coverage and real-time, dynamic responses to changes within the IT landscape.
• Azure native software as a service (SaaS): Azure Native Dynatrace Service seamlessly provides deep cloud observability, advanced AI for IT operations (AIOps), and continuous runtime application security capabilities native to all Azure customers empowered with Azure OpenAI generative capabilities.

Intellect Design

The iGTB Copilot helps banking professionals generate insights and provide cross-sell assistance in commercial and corporate banking. It leverages generative AI to streamline operations and client interactions, allowing relationship managers to spend less time on manual data analysis and more on strategic client engagement. Here are the key functionalities:

• Comprehensive payment analysis: It enables users to perform detailed analyses of historical payment data, helping to identify trends and patterns without the need for any programming skills. It also helps in identifying delayed payments.
• Visual data summarization: The iGTB Copilot can automatically transform complex data into easily understandable visual graphics and provide insights and suggested actions.
• The iGTB Copilot, composed on the Purple fabric of eMACH.ai, is powered by Azure OpenAI, GPT-4 Turbo model, and other Azure infrastructure services.

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Datamatics

Datamatics Copilot for Partner Onboarding is integrated with Microsoft Teams and leverages Microsoft Copilot, Microsoft Teams bot framework, and Azure OpenAI technologies. The application is designed to streamline the onboarding of vendors, business partners, freight forwarders, and employees across different geographies, making what is traditionally a complex and tedious process much more efficient.

Key functionalities include:

• Natural language querying: Users can query the status of onboarding processes and receive updates using conversational language.
• Automation and integration: The Copilot automates the creation of partner records and integrates seamlessly with other business systems for efficient data management.
• Real-time updates and communication: Enables prompt communication with partners about their onboarding status, including rejections, directly from Teams.
• Document management: Maintains and enforces compliance by specifying required documents for each country, ensuring partners submit the correct documents.

MiHCM

MiHCM SmartAssist is an AI-powered HR copilot designed to streamline HR processes. This tool is part of the MiHCM platform and offers a range of functionalities and customizations that simplify various HR tasks.

Key features include:

• Document generation: SmartAssist, built on top of Azure with services, including Azure OpenAI, Azure AI Search, Azure App Service, and Azure SQL Database, and leveraging Microsoft’s Copilot framework, can quickly generate employee letters with just a few keystrokes. It ensures that these documents are personalized by dynamically incorporating employee data.
• Job description creation: It automatically generates job descriptions that reflect the company’s unique voice and tone, including key performance indicators (KPIs), qualifications, and experience requirements.
• Customization capabilities: Users can easily adjust the content generated by SmartAssist, ensuring the output meets their specific needs.
• Data analysis and reporting: SmartAssist leverages employee data to analyze and calculate statistics, generate reports, and provide information at high speeds, enabling business leaders to make informed decisions quickly. This tool can answer high-level questions, going beyond mere facts and figures to provide valuable insight quickly. Information that would take days to gather can now be analyzed and provided in seconds.

Next steps to adopt AI and deploy copilots

• Check out our digital session at Microsoft Build 2024, that discusses enabling independent software vendors (ISVs) to transform industries in the age of copilots.
• Assess the drivers of AI success so you can realize meaningful business impact with AI.
• Learn how to power your AI transformation with Microsoft.
• Learn more about creating generative AI experiences with Microsoft Cloud across many Microsoft solutions.
• Envision boosted creativity and work productivity with Copilot for Microsoft 365 and learn how to extend it.
• Start using GitHub Copilot and Microsoft Copilot for Sales, now generally available.
• Learn how to build safety and responsibility into your AI journey from the start.
• Learn more about the featured ISVs: TomTom, Modern Requirements, Dynatrace, Intellect Design, Datamatics, and MiHCM.

The post Building AI solutions with partners: Empowering transformation with copilots appeared first on The Microsoft Cloud Blog.

We’re already seeing how Microsoft Copilot can help turn “I can’t” into “watch me” for people around the world in their everyday lives. But for business leaders, Microsoft Copilot is just the start—there are so many additional ways you can bring this transformative technology into your organization. Understanding your options—and the business scenarios best suited for each—is critical. Read on to learn how you can approach making these decisions for your organization.

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Establish your business objectives

Before you think about how you’ll deploy AI solutions, you have to start with why. Aligning your AI investments with a clear business strategy is imperative, as my colleague Susan Etlinger explores in this blog post.

With specific goals in mind, you can prioritize use cases based on their potential for impact and scope your solution based on data and infrastructure requirements. This will help you make decisions aligned with your business objectives and drive your company forward.

Once you’ve identified your why, there are a few common pathways we’re seeing for how to apply AI to reach those goals—from buying off-the-shelf software as a service (SaaS) solutions to building a custom solution that meets your specific needs. Let’s explore the options.

Use Microsoft Copilot to boost employee productivity

If your priority is employee productivity across your business, Microsoft Copilot should be one of the first solutions you consider. If you’re already using Microsoft Entra for identity management, your employees can sign in using their work or school account and get commercial data protection for free—which means chat data isn’t saved, Microsoft has no eyes-on access, and your data isn’t used to train the models.

Copilot helps your people to get the answers and time-saving assistance they need from powerful AI models without putting your company data at risk. But that’s just the start.

Copilot for Microsoft 365 is our best Copilot experience for organizations. It gives you priority access to the very latest models—starting with OpenAI’s GPT-4 Turbo. You get Copilot in Word, Excel, PowerPoint, Outlook, OneNote, and Microsoft Teams—combined with your universe of data in the Microsoft Graph, including data you bring in from external sources through Microsoft Graph connectors. Copilot for Microsoft 365 has enterprise-grade data protection, which means it inherits your existing Microsoft 365 security, privacy, identity, and compliance policies. It also includes Copilot Studio to customize Copilot for Microsoft 365 and build standalone copilots—more on this in a minute.

Built on Microsoft’s comprehensive approach to security, compliance, privacy, and responsible AI, Copilot for Microsoft 365 is designed to be enterprise-ready, helping employees in every part of your business unlock productivity and unleash creativity.

And with Copilot for Sales, Copilot for Service, and Copilot for Finance, we’ve added role-specific workflow automation, guided actions, and content generation to the applications professionals use the most. With built-in integration across business systems—whether Dynamics 365 or a third-party customer relationship management (CRM), enterprise resource planning (ERP), or contact center applications—sellers, service agents, and financial professionals can be more effective and efficient as they work, guided by Copilot. 

When you’re thinking about boosting employee productivity in common business scenarios, an out-of-the-box solution like these can deliver incredible impact. But a solution like this may not be the right fit—so let’s look at the next pathway.

Customize Microsoft Copilot to serve the unique needs of your business

No two organizations are alike, and neither are the apps, data, and workflows that drive your business. Microsoft Copilot can help boost employee productivity in the usual functions of every business, but you may also need solutions customized for your own business processes. With Microsoft Copilot Studio, a low-code tool, you can tailor and extend Copilot for Microsoft 365 or build standalone copilots specific to your needs.

For example, within Copilot for Microsoft 365, you may be looking to add specific plugins to address nuanced topics like legal, finance, or human resources (HR). You may want to create and call new workflows within Copilot or connect Copilot with data that lives outside the Microsoft Graph. These customization capabilities are included with Copilot for Microsoft 365.

Create your own copilots to deliver transformational experiences

Now let’s take this a step further. Instead of building on the foundation of Microsoft Copilot, you may be looking to bring copilot experiences into your own applications with other data sources. The new copilot category is not limited to internal productivity and employee-facing applications, but can extend into external, customer-facing experiences that differentiate your business and drive growth.

With your customized copilot solution, you can bring generative AI to your own unique business processes like supply chain management, manufacturing line operations, or quality control. You can engage customers and users with more personalized experiences and recommendations. The potential for new innovation is limited only by your imagination—and with Microsoft’s range of development tools, you can build generative AI-powered experiences exactly where you want them.

To quickly and securely build your own copilots, you can start in a low-code environment with Copilot Studio, going beyond the extensibility capabilities we already covered. With Azure OpenAI Service behind the scenes, Copilot Studio is a fully managed, hosted SaaS service, with built-in analytics as well as security and governance controls. You also maintain control over dialog management and conversational orchestration, and you can deploy custom copilots built with Copilot Studio to many channels across web, apps, social channels, and Microsoft Teams.

You can also take your custom copilot a step further with a pro-code approach giving developers full control in an end-to-end application development platform—Azure AI Studio.

Azure AI Studio is a generative AI environment for developing intelligent applications from end-to-end, including custom copilots. For skilled development teams that need to benchmark models, mix and match models, fine tune, evaluate, and continuously monitor their solutions, this is the place. Azure AI Studio enables developers to build new AI applications or augment existing apps with AI capabilities. Developers can identify the best models for a custom copilot, create multimodal capabilities beyond text alone, design and evaluate prompts, build extensions with custom AI search, mitigate risk with robust content safety tools, deploy at scale, and continue to monitor applications in production.

Use the right tool—or tools—for the job

Though we’ve outlined a few different options for how you can use AI to help reach your business goals, these pathways are by no means mutually exclusive—you can and should use more than one approach to meet your needs. And with the Microsoft Cloud, you can easily work across approaches, and shift gears as your needs change.

You can start with Copilot for Microsoft 365 and use Copilot Studio to quickly build a workflow that serves a specific business function, then as you uncover more advanced applications for that workflow, Copilot Studio also works with Azure AI Studio and additional Azure services. This connected, end-to-end AI toolchain allows your developers to use the right tool for the job at hand, spanning low-code and pro-code capabilities as their needs change.

And keep in mind that AI safety and responsibility should be top of mind from the very beginning. Make sure you’re considering the principles, corporate standards, tools, and governance that you’ll need to ensure your AI experiences are built on trust. The Responsible AI Standard is a great place to start.

Next steps

I hope you take the time to explore the breadth of Microsoft’s AI innovation, and dig deeper into the various AI approaches I’ve outlined here. Remember—no matter what your business priorities, or where you’re starting from, Microsoft is ready to help empower your AI transformation.

The post Build, buy, or both? How to choose the right approach for your AI transformation appeared first on The Microsoft Cloud Blog.

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

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

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

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

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

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

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

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

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

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

Microsoft and the Pacific Northwest National Laboratory (PNNL) in Richland, Washington, are collaborating to demonstrate how this acceleration can benefit chemistry and materials science – two scientific fields pivotal to finding energy solutions that the world needs.

Scientists at PNNL are testing a new battery material that was found in a matter of weeks, not years, as part of the collaboration with Microsoft to use to advanced AI and high-performance computing (HPC), a type of cloud-based computing that combines large numbers of computers to solve complex scientific and mathematical tasks.

PNNL materials scientist Shannon Lee mixes raw materials to synthesize a new solid electrolyte, one of the promising candidates predicted using AI and HPC tools in the Azure Quantum Elements service. Photo by Dan DeLong for Microsoft.
As part of this effort, the Microsoft Quantum team used AI to identify around 500,000 stable materials in the space of a few days.

The new battery material came out of a collaboration using Microsoft’s Azure Quantum Elements to winnow 32 million potential inorganic materials to 18 promising candidates that could be used in battery development in just 80 hours. Most importantly, this work breaks ground for a new way of speeding up solutions for urgent sustainability, pharmaceutical and other challenges while giving a glimpse of the advances that will become possible with quantum computing.

“We think there’s an opportunity to do this across a number of scientific fields,” says Brian Abrahamson, the chief digital officer at PNNL. “Recent technology advancements have opened up the opportunity to accelerate scientific discovery.”

PNNL is a U.S. Department of Energy laboratory doing research in several areas, including chemistry and materials science, and its objectives include energy security and sustainability. That made it the ideal collaborator with Microsoft to leverage advanced AI models to discover new battery material candidates.

“The development of novel batteries is an incredibly important global challenge,” Abrahamson says. “It has been a labor-intensive process. Synthesizing and testing materials at a human scale is fundamentally limiting.”

Learning through trial and error
The traditional first step of materials synthesis is to read all the published studies of other materials and hypothesize how different approaches might work out. “But one of the main challenges is that people publish their success stories, not their failure stories,” says Vijay Murugesan, materials sciences group lead at PNNL. That means scientists rarely benefit from learning from each other’s failures.

The next traditional scientific step is testing the hypotheses, typically a long, iterative process. “If it’s a failure, we go back to the drawing board again,” Murugesan says. One of his previous projects at PNNL, a vanadium redox flow battery technology, required several years to solve a problem and design a new material.

Vijay Murugesan, material sciences group lead at PNNL, says the Microsoft AI and HPC tools allow scientists to eliminate the time-consuming trial-and-error discovery steps and focus on the best candidates for testing. Photo by Andrea Starr for PNNL.
The traditional method requires looking at how to improve on what has been done in the past. Another approach would be to take all the possibilities and, through elimination, find something new. Designing new materials requires a lot of calculations, and chemistry is likely to be among the first applications of quantum computing. Azure Quantum Elements offers a cloud computing system designed for chemistry and materials science research with an eye toward eventual quantum computing, and is already working on these kinds of models, tools and workflows. These models will be improved for future quantum computers, but they are already proving useful for advancing scientific discovery using traditional computers.

To evaluate its progress in the real world, the Microsoft Quantum team focused on something ubiquitous in our lives – materials for batteries.

Teaching materials science to AI
Microsoft first trained different AI systems to do sophisticated evaluations of all the workable elements and to suggest combinations. The algorithm proposed 32 million candidates – like finding a needle in a haystack. Next, the AI system found all the materials that were stable. Another AI tool filtered out candidate molecules based on their reactivity, and another based on their potential to conduct energy.

The idea isn’t to find every single possible needle in the hypothetical haystack, but to find most of the good ones. Microsoft’s AI technology whittled the 32 million candidates down to about 500,000 mostly new stable materials, then down to 800.

“At every step of the simulation where I had to run a quantum chemistry calculation, instead I’m calling the machine learning model. So I still get the insight and the detailed observations that come from running the simulation, but the simulation can be up to half a million times faster,” says Nathan Baker, Product Leader for Azure Quantum Elements.

AI may be fast, but it isn’t perfectly accurate. The next set of filters used HPC, which provides high accuracy but uses a lot of computing power. That makes it a good tool for a smaller set of candidate materials. The first HPC verification used density functional theory to calculate the energy of each material relative to all the other states it could be in. Then came molecular dynamics simulations that combined AI and HPC to analyze the movements of atoms and molecules inside each material.

This process culled the list to 150 candidates. Finally, Microsoft scientists used HPC to evaluate the practicality of each material – availability, cost and such – to trim the list to 23 – five of which were already known.

Thanks to this AI-HPC combination, discovering the most promising material candidates took just 80 hours.

The HPC portion accounted for 10 percent of the time spent computing – and that was on an already-targeted set of molecules. This intense computing is the bottleneck, even at universities and research institutions that have supercomputers, which not only are not tailored to a specific domain but also are shared, so researchers may have to wait their turn. Microsoft’s cloud-based AI tools relieve this situation.

Broad applications and accessibility
Microsoft scientists used AI to do the vast majority of the winnowing, accounting for about 90 percent of the computational time spent. PNNL materials scientists then vetted the short list down to half a dozen candidate materials. Because Microsoft’s AI tools are trained for chemistry, not just battery systems, they can be used for any kind of materials research, and the cloud is always accessible.

“We think the cloud is a tremendous resource in improving the accessibility to research communities,” Abrahamson says.

Brian Abrahamson, chief digital officer at PNNL. Photo by Andrea Starr for PNNL.
Today, Microsoft supports a chemistry-specific copilot and AI tools that together act like a magnet that pulls possible needles out of the haystack, trimming the number of candidates for further exploration so scientists know where to focus. “The vision we are working toward is generative materials where I can ask for list of new battery compounds with my desired attributes,” Baker says.

The hands-on stage is where the project stands now. The material has been successfully synthesized and turned into prototype batteries that are functional and will undergo multiple tests in the lab. Making the material at this point, before it’s commercialized, is artisanal. One of the first steps is to take solid precursors of the materials and to grind them by hand with a mortar and pestle, explains Shannon Lee, a PNNL materials scientist. She then uses a hydraulic press to compact the material into a dime-shaped pellet. It goes into a vacuum tube and is heated to 450 to 650 degrees Celsius (842 to 1202 degrees Fahrenheit), transferred to a box to keep it away from oxygen or water, and then ground into a powder for analysis.

For this material, the 10-or-more-hour process is “relatively quick,” Lee says. “Sometimes it takes a week or two weeks to make a single material.”

Then hundreds of working batteries must be tested, over thousands of different charging cycles and other conditions, and later different battery shapes and sizes to realize commercial use. Murugesan dreams of the development of a digital twin for chemistry or materials, “so you don’t need to go to a lab and put this material together and make a battery and test it. You can say, ‘this is my anode and this is my cathode and that’s the electrolyte and this is how much voltage I’m going to apply,’ and then it can predict how everything will work together. Even details like, after 10,000 cycles and five years of usage, the material performance will be like this.”

Microsoft is already working on digital tools to speed up the other parts of the scientific process.

The lengthy traditional process is illustrated by lithium-ion batteries. Lithium got attention as a battery component in the early 1900s, but rechargeable lithium-ion batteries didn’t hit the market until the 1990s.

Today, lithium-ion batteries increasingly run our world, from phones to medical devices to electric vehicles to satellites. Lithium demand is expected to rise five to ten times by 2030, according to the U.S. Department of Energy. Lithium is already relatively scarce, and thus expensive. Mining it is environmentally and geopolitically problematic. Traditional lithium-ion batteries also pose safety issues, with the potential to catch fire or explode.

Many researchers are looking for alternatives, both for lithium and for the materials used as electrolytes. Solid-state electrolytes show promise for their stability and safety.

Surprising results
The newly discovered material PNNL scientists are currently testing uses both lithium and sodium, as well as some other elements, thus reducing the lithium content considerably – possibly by as much as 70 percent. It is still early in the process – the exact chemistry is subject to optimization and might not work out when tested at larger scale, Abrahamson cautions. He points out that the story here is not about this particular battery material, but rather the speed at which a material was identified. The scientists say the exercise itself is immensely valuable, and it has revealed some surprises.

The AI-derived material is a solid-state electrolyte. Ions shuttle back and forth through the electrolyte, between the cathode and the anode, ideally with minimal resistance.

Test tubes contain samples of the new material, which looks like fine white salt.
Samples of the new solid electrolyte discovered by Microsoft AI and HPC tools. Solid-state electrolytes are safer than liquid ones. Photo by Dan DeLong for Microsoft.
It was thought that sodium ions and lithium ions couldn’t be used together in a solid-state electrolyte system because they are similarly charged but have different sizes. It was assumed that the structural framework of a solid-state electrolyte material couldn’t support the movement of two different ions. But after testing, Murugesan says, “we found that the sodium and lithium ions seem to help each other.”

The new material has a bonus, Baker says, because its molecular structure naturally has built-in channels that help both ions move through the electrolyte.

Work on the new material is in early stages but “irrespective of whether it’s a viable battery in the long run, the speed at which we found a workable battery chemistry is pretty compelling,” Abrahamson says.

Additional discoveries are still possible. Murugesan and his team have yet to make and test most of the other new material candidates that the Microsoft models suggested. The collaboration continues, with PNNL computational chemists learning to use the new tools, including a copilot trained on chemistry and other scientific publications.

“With Microsoft and PNNL, this is an enduring collaboration to accelerate scientific discovery, bringing the power of these computational paradigm shifts to bear, with the chemistry and material science that are a hallmark strength of the Pacific Northwest National Laboratory,” Abrahamson says.

“We’re sitting on the precipice of this maturation of the artificial intelligence models, the computational power needed to train and make them useful, and the ability to train them on specific scientific domains with specific intelligence,” he adds. “That, we believe, is going to usher in a new era of acceleration. That is exciting, because these problems matter to the world.”

Related links:

Read Unlocking a new era for scientific discovery with AI: How Microsoft’s AI screened over 32 million candidates to find a better battery
Read Azure Quantum Elements aims to compress 250 years of chemistry into the next 25
Learn more about Azure Quantum Elements
Read: PNNL-Microsoft Collaboration: Accelerating Scientific Discovery
Read the PNNL press release: Energy Storage, Materials Discovery Kick-Off Three-Year Collaboration with Microsoft
Top image: Dan Thien Nguyen, a PNNL materials scientist, assembles a coin cell with the synthesized solid electrolyte. With AI tools guiding researchers, synthesis and testing can be focused in the right direction toward better materials for particular applications. Photo by Dan DeLong for Microsoft.

The post Discoveries in weeks, not years: How AI and high-performance computing are speeding up scientific discovery appeared first on The Microsoft Cloud Blog.

It’s important to understand the potential of AI and learn how to make informed decisions about AI adoption and implementation. The benefits of AI in business are more compelling every day. A recent global study by IDC confirms that businesses are eager to adopt AI technology, with 71% of respondents currently using AI tools in their organizations.¹

Even with this momentum, business leaders face challenges when it comes to implementation. Where should you start your organization’s AI transformation?

Transform your business with AI

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Learn from Microsoft leaders how to transform your organization with AI

We’ve brought together our AI and industry leaders at Microsoft to share how they think about AI transformation in our video series, Transform Your Business with AI. More importantly, they provide success stories and guidance on how others can align AI technology with their business goals.

To start learning about how AI can transform your business, I recommend you begin by thinking about where your business is today and where it is you want to go. Jessica Hawk, Corporate Vice President, Data, AI, and Digital Applications Product Marketing at Microsoft, will walk you through the key drivers of AI success. She will also provide guidance as you examine what characteristics foster an AI-ready culture.

Whether you lead a healthcare organization or a retail business, the next two topics are top of mind.

1. Responsible AI: Natasha Crampton, Chief Responsible AI Officer, shares principles and procedures followed at Microsoft and how leaders can develop their own AI strategy.
2. Sustainability: Melanie Nakagawa, Chief Sustainability Officer, shares the Microsoft approach to sustainability in the era of AI.

Explore how Microsoft and customers are implementing AI within retail, manufacturing, financial services, and healthcare with our industry-focused videos.

• Retail: Learn how AI is impacting the retail industry with Shelley Bransten, Corporate Vice President of Global Retail, Consumer Goods, and Gaming Industries at Microsoft.
• Manufacturing: Kathleen Mitford, Corporate Vice President of Global Industry Marketing at Microsoft, shares how AI will change the manufacturing industry and how you can partner with Microsoft to prepare your business.
• Financial Services: Bill Borden, Corporate Vice President of Worldwide Financial Services at Microsoft, takes you through some of the biggest obstacles facing the financial services industry and shows how AI can help you drive differentiated outcomes for your business.
• Healthcare: Rob Dahdah, Corporate Vice President of Industry and Partner Sales for the Health and Life Sciences at Microsoft, dives into how AI can make a significant impact on the world of healthcare, from more personalized healthcare to more efficient drug development.

Discover the knowledge and resources to adopt AI in your organization

To complement this video series, we’ve released a full training course on our free learning platform, Microsoft Learn.

Here’s what you’ll learn in this course:

1. What is AI and how is it used in business?

You’ll learn the difference between generative AI, machine learning, and deep learning. Plus, you’ll understand how AI works through examples specific to sales, supply chain, human resources, finance, marketing, commerce, customer service, and project management.

2. How can I be sure AI is adding value to my business?

AI technologies can drive substantial value to organizations. Defining an AI strategy specific to your business is so critical. We’ll walk through how to define your strategy, and we’ll examine what characteristics foster an AI-ready culture.

3. How do I know if my business is using AI responsibly?

At Microsoft, we believe that as organizations and society take steps toward responsible AI, we need to continually evolve to reflect new innovations and lessons from both our mistakes and accomplishments. You’ll learn the six guiding principles to develop and use AI responsibly so you can move confidently in your AI transformation.

4. What steps do I take to implement AI in my organization?

Starting with your AI strategy, this module in the training covers assigning responsibilities and empowering workers and subject matter experts to use AI themselves. You’ll also learn to evaluate and prioritize AI investments and establish AI-related roles and responsibilities.

By the end of the course, you’ll have a solid understanding about the practicalities of AI, how you can use it in your business, and how to evaluate it against the principles of responsibility.

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At Microsoft, our mission is to empower every person and organization on the planet to achieve more. The rapid rise of advancements in AI and cloud computing make access to technical skills an even more vital part of that mission. Developing proficiency in Microsoft AI technologies empowers you to innovate and accomplish far more than you previously thought possible.  

Today, it’s more important than ever to empower your team to gain the right skills, prove their expertise, and showcase their abilities so you can accelerate implementing AI at scale.

Learn more about generative AI in this training from Microsoft Learn.

¹IDC Infographic, sponsored by Microsoft, The Business Opportunity of AI, IDC #US51315823, November 2023.

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