This is where the frontier is forming. While copilots help individuals be more effective, agents act on behalf of people. They carry out tasks, orchestrate multi-step workflows, and operate across systems continuously. And they’re moving quickly from experimentation to mainstream use. An IDC InfoBrief, sponsored by Microsoft, shows that 37% of organizations surveyed use agentic AI, another 25% are experimenting with it, and 24% are planning to use it the next 24 months.¹ Organizations that have already invested in people, skills, and responsible practices may be better prepared to operationalize agents at scale—and convert AI’s promise into real business performance.

Five strategic moves for introducing agents responsibly

The new Agents in the Workforce Handbook builds on those earlier foundations. Where the first blog in this series focused on empowering your people, and the second explored how to pair human judgment with AI systems, this third chapter looks ahead: How do you introduce agents into your workforce responsibly and intentionally? Below are five strategic moves leaders should consider. These are high-level guideposts; the Handbook goes much deeper with templates, examples, and decision frameworks to support implementation.

1. Start with your most persistent pain points

When organizations begin exploring agentic AI, a common challenge is prioritization. Imagining use cases is easy. Choosing where to start is harder. Successful organizations don’t begin with futuristic ideas—they begin with the familiar, recurring friction points that quietly drain time and introduce risk.

These are often the workflows teams have learned to “live with”: manual triage, routine follow-up, coordination across systems, repeated reporting steps, or tasks with high error potential. Leaders should observe how work truly happens—shadowing teams, reviewing process maps, and asking simple but revealing questions:

• Where do we lose time?
• What gets done manually that shouldn’t be?
• What feels broken—but no one owns?

These pain points typically offer the clearest path to early value. Addressing them not only frees capacity but also demonstrates to teams how agents can meaningfully improve the day-to-day. The Agents in the Workforce Handbook includes a readiness assessment and real-world patterns to help leaders identify and sequence the right opportunities.

2. Define your AI goal—and lead the change yourself

Introducing agents isn’t only a technical shift—it’s a leadership shift. Frontier Firms choose to align their early agent initiatives around bold, measurable goals: reducing manual work, accelerating cycle times, improving customer responsiveness, or expanding sales capacity. These goals create alignment and momentum, helping teams understand why agents matter and what success looks like.

But goals alone don’t change culture—leaders do. The organizations that move fastest are those whose executives personally model new ways of working. They use agents in their own workflows, talk openly about learnings, and recognize early adopters who demonstrate impact. They also acknowledge that change requires habit‑building. Experimenting with agents for even 20 to 30 minutes a day can materially improve adoption and confidence.

Skilling plays a central role. As Jeana Jorgensen, Corporate Vice President of Global Skilling, notes:

We’re hearing from many of our customers and partners that they expect employees across different roles to spend about 15 to 20% of their week learning and integrating AI into their daily work.

The Handbook offers guidance for identifying the roles, skills, and operating rhythms needed to support agent adoption.

3. Measure what works—and double down where it does

As with any transformative technology, early wins with agents need to be measurable and repeatable. Leaders should ensure visibility into how agents behave, how frequently they’re used, and the outcomes they produce. This isn’t about policing technology—it’s about giving teams the insights needed to improve and scale what’s working.

Effective organizations treat agent adoption like an operational discipline:

• They log and monitor agent activity.
• They measure time saved and business impact generated.
• They expand agents that demonstrate clear value.
• They refine or retire agents that don’t.

These data-driven insights help organizations move from experimentation to a consistent, enterprise-wide model for agent development—one where new ideas become shared services rather than isolated automations. The Handbook goes deeper into measurement strategies, including examples of what high-performing organizations track.

4. As agents become teammates, optimize continuously

Once an organization begins deploying agents across teams, a new challenge emerges: coordination. Agents that start out as individual productivity tools often become shared digital teammates—relied upon by multiple people, processes, and business functions. With that shift comes the need for thoughtful ownership, governance, and communication.

Successful organizations establish clear roles and responsibilities:

• Who owns each agent?
• Who can modify or update it?
• How are changes communicated to the people who rely on it?
• What happens when an agent’s behavior needs tuning?

Agents also require continuous improvement. As they’re used, they encounter edge cases, nuanced team preferences, and shifting processes. Over time, agents become more capable, and employees naturally evolve into “AI managers”—guiding digital apprentices the way they onboard and develop human teammates.

The Handbook provides deeper recommendations for governance models, centers of excellence, and cross-team alignment mechanisms that help organizations scale responsibly.

5. Reinvest the time saved—and push into innovation

While early value often shows up as efficiency, the long-term impact of agentic AI is much bigger: it creates renewed capacity for innovation. Frontier Firms understand that the goal isn’t to simply do the same work faster—it’s to free teams to pursue higher-value ideas, explore new business models, and elevate customer experiences.

Across industries, leading organizations are already demonstrating what this reinvestment looks like:

• L’Oréal is using AI agents to deliver personalized, at-scale beauty guidance.
• AT&T accelerated customer care resolution by 33%, saving millions while improving experience.

These examples highlight a crucial point: agents are not just workflow optimizers. They’re catalysts for reimagining how organizations deliver value. And the companies that begin investing now are positioning themselves for meaningful advantage.

Treat agents like teammates, not tools

The organizations achieving the strongest results view agents not as automations but as digital collaborators—systems that require feedback, tuning, and iteration. They integrate agents into team rhythms, treat them like growing contributors, and help their people evolve into confident AI managers.

This marks the natural third step in the Frontier journey: after empowering employees and strengthening the partnership between human expertise and AI (as explored in the first two blogs), organizations are now ready to bring digital teammates into the workflow in a structured, scalable way.

If your organization is ready to move from experimentation to scaled impact, the Agents in the Workforce Handbook offers the detailed guidance, examples, and templates to support your next phase of Frontier Transformation.

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

The post How to introduce agents into your workforce: 5 actions leaders can take appeared first on The Microsoft Cloud Blog.

Microsoft Global Skilling helps people and organizations build the skills they need to thrive in an AI‑powered world. Within Global Skilling, the Learning Lab is the innovation engine—a team focused on designing, testing, and evolving modern learning experiences to continuously improve how skills are developed, validated, and applied in the flow of work. 

AI is reshaping how organizations work. Teams aren’t just adopting new tools—they’re also figuring out how those tools fit into existing workflows, roles, and expectations, all while trying to keep pace with business demands in a rapidly changing landscape. It’s a heavy lift. As the leader of the Learning Lab team, I’m navigating these same pressures, along with my team members, as we balance day-to-day delivery with the need to evolve our processes in real time. That’s why we’re embedding AI assistants and agentic workflows into internal processes—using them not only to work differently but also to learn differently. Through experimentation, we’re uncovering new ways to streamline operations and improve the learner experience for our global audience.  

This blog highlights three of our team’s most impactful AI initiatives that could also benefit your organization. Inspired by these projects, we developed A Practical Guide for Bringing AI into Your Business Processes, featuring real-world examples and actionable ideas for integrating AI and human expertise across your organization. 

A Practical Guide for Bringing AI into Your Business Processes

Download the guide

3 impactful AI initiatives leading the way

1. Reducing time-intensive coordination to optimize research 

The challenge of coordinating teams for research  

Before any learning materials can be built, our team conducts extensive research to understand new technologies, identify required skills, and validate what learners need. This early-stage analysis requires input from multiple stakeholders and a deep review of internal documentation, product roadmaps, and existing training materials.  

How AI is helping accelerate our research tasks and optimize cross-team input 

One of the biggest bottlenecks for our research workflows has been the time it takes to synthesize information and align teams around what a course should achieve. To improve this, we began experimenting with Researcher in Microsoft 365 Copilot and persona-based agents to support our research and planning stages. Our new process looks like this: 

• Researcher synthesizes internal documentation, product roadmaps, and existing training materials to surface emerging themes and identify knowledge gaps. With the ability to process thousands of pages in minutes, it flags potential course objectives the team might have missed.
• In parallel, persona-based agents simulate the perspectives of stakeholders from varying teams to help validate ideas before bringing them to the key decision-makers.
• Throughout this process, our team members guide these AI tools through every step—providing the business context, analyzing AI outputs to identify gaps or inconsistencies, refining direction, and ensuring consideration of broader business objectives.  

In our experience with AI handling synthesis and early-stage validation, we’ve reduced the time required for core research processes from two weeks to just one day. This significant time savings extends to every course developed with this method, enabling us to redirect focus toward shaping stronger strategies, aligning content with business impact, and accelerating decision-making across teams.

Applying this approach in your organization 

AI-supported research and planning can help you make sense of complex information faster and build alignment earlier in your decision cycles. By using AI to synthesize documents, surface patterns, and validate assumptions, you can reduce the effort required to get teams on the same page. Your team members can then focus on refining strategy, confirming business priorities, and shaping higher-impact decisions. This combination improves speed and clarity throughout cross-functional work.  

Explore A Practical Guide for Bringing AI into Your Business Processes to learn more about how you can apply this in processes like: 

• Drafting onboarding plans that human resources (HR) leaders can tailor to company culture.
• Developing quarterly sales plays informed by shifting buyer behavior and competitor activity.
• Creating campaign briefs rooted in audience insights, market trends, and performance data.
• Developing forecasting assumptions by synthesizing inputs from sales, operations, and historical data. 

2. Transitioning from manual maintenance to continuous quality improvements 

The challenge of shorter content lifecycles  

We maintain thousands of courses and lab environments as part of our skilling initiatives for Microsoft technologies. With the fast pace of product evolution, it can be challenging to keep learning content accurate and functional.  

How GitHub Copilot became the maintenance partner for the team 

We recognized that the demands for maintaining learning content were increasing beyond our capacity to manage effectively. So we integrated GitHub Copilot into the content maintenance workflow like this: 

• GitHub Copilot tools analyze content repositories—flagging inconsistencies, identifying outdated examples, and recommending updates based on current documentation.
• Throughout this process, our team reviews and refines the AI-generated recommendations. When GitHub Copilot flags an issue, we evaluate how those changes might apply to other training courses. We also ensure that all revisions align with learning objectives and verify that security and accessibility standards are met.
• Then GitHub Copilot helps implement some of the suggested updates, like generating new code samples or suggesting environmental configurations that align with the latest product releases. 

As a result, our team has reduced the time we spend on routine content maintenance by up to 25%. And with these time savings, team members can shift from reactive updates to proactive innovation—evaluating emerging skills, shaping next-generation modules, and exploring how agents, simulations, and personalized learning could improve outcomes. 

Applying this approach in your organization 

AI-assisted maintenance can help you keep large, fast-changing content ecosystems accurate and up to date without overwhelming your teams. By using AI to surface inconsistencies, flag outdated material, and recommend updates, you can dramatically reduce time spent on routine fixes. Your experts can then focus on reviewing changes for accuracy, regulatory needs, and strategic intent. This balance enables you to maintain quality at scale while freeing your teams to invest in higher-value innovation.  

Explore A Practical Guide for Bringing AI into Your Business Processes to learn more about how you can apply this in processes like: 

• Maintaining and updating sales enablement content as product and service offerings evolve.
• Keeping product messaging frameworks and campaign assets consistent and up to date.
• Updating help center articles and support workflows after feature releases.
• Updating contract templates and clause libraries to align with new regulatory guidance.

3. Delivering inclusive learning at scale through diverse content formats 

The challenge of content relevance and engagement  

Our learners span every continent, speak dozens of languages, and have their own preferred learning methods. Creating multimodal, accessible, and inclusive learning experiences while managing constant content updates was stretching the team thin.  

How AI helps scale and translate content for global learners  

To support different learning styles and languages, we’re piloting how to create immersive, inclusive learning through two experiments with AI: 

1. We’re using AI tools to turn a single source of training content, like a session transcript or recording, into multiple formats, such as videos, podcasts, and recap summaries. This multimodal output lets us update learning materials at the pace required by our global audience and helps ensure that we’re reaching learners in their preferred formats.
2. We’re piloting an AI-powered tool that not only translates content but also generates avatars that deliver multilingual voiceovers with more natural lip-sync, eliminating one of the most distracting elements of dubbed content. 

Early results show that we can now recover up to 15 hours per course we develop—time our team can spend on more nuanced work that AI can’t do, like adapting cultural references, verifying that tone and pacing match learning objectives, and maintaining brand voice. 

Applying this approach in your organization 

AI-powered localization can help you deliver content that feels native to every audience you service, no matter the language or market. By pairing AI’s speed in translation, voiceover, and prompt generation with your team’s expertise in cultural nuance and brand standards, you can scale global engagement without diluting quality. This combination lets you reach more learners, customers, and employees while keeping your message consistent and relevant across regions.  

Explore A Practical Guide for Bringing AI into Your Business Processes to learn more about how you can apply this in processes like: 

• Localizing campaign assets for regional markets across languages and cultural norms.
• Tailoring pitch decks and demos for industry-specific or region-specific buyers.
• Creating multilingual chatbot responses and support scripts for global customers.
• Adapting standard operating procedure and process documentation for different facilities or regional regulations. 

Building skills and strengthening our AI strategy

As AI becomes an extension to the Learning Lab, we’ve discovered that it’s much more than just implementing new tools—it’s also a journey of building technical and human skills across the team. Our experiments require every team member to stretch into new capabilities, from process optimization and innovation to strengthening collaboration and creative problem-solving. As a result, we’ve been able to spend less time on repetitive tasks and to dedicate more energy to the kind of creative, relationship-driven work that leads to exceptional learning experiences. 

Looking to build skills for you and your teams? Explore AI Skills Navigator, the agentic learning space that brings together AI-powered skilling experiences and credentials that help individuals build career skills and organizations worldwide accelerate their business.

The post How to bring human expertise and AI together: 3 impactful initiatives appeared first on The Microsoft Cloud Blog.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

1. Preparing for the integration of AI and agents.
2. Strengthening training so that everyone has the necessary skills. 
3. Fostering a culture that prioritizes cybersecurity. 

Preparing for the integration of AI and intelligent agents

Preparing for AI and agent integration calls for careful strategy, thoughtful business planning, and organization-wide adoption under solid governance, security, and management. Microsoft’s AI adoption model offers a step-by-step guide for businesses embarking on this journey and the guide offers actionable insights and solutions to manage AI risks.

Strengthening training so that everyone has the necessary skills

Technology alone isn’t enough. People are your strongest defense—and the foundation of trust. That’s why skilling emerged as a central theme throughout these past months and will continue beyond. Frontier Firms—those structured around on-demand intelligence and powered by “hybrid” teams of humans plus agents—lead by fostering a culture of continuous learning. Our blog “Building human-centric security skills for AI” offers insights and guidance you can apply in your organization.  

• Lean into your unique human strengths: Your team’s judgment, creativity, and experience are irreplaceable. Take time to invest in upskilling and reskilling them, so they can confidently guide and manage AI tools responsibly and securely. Explore Microsoft Learn for Organizations for resources to support your learning journey.
• Stay curious and agile through continuous learning: Building security resilience is an ongoing process. Regularly refresh your AI and security training, offer time and resources for employees to explore new skills, and create a supportive, engaging environment that motivates continuous growth. Find in AI Skills Navigator, our agentic learning space, AI and security training tailored to different roles.  

Investing in skilling doesn’t just reduce risk—it accelerates innovation by giving teams the confidence to explore new AI capabilities securely. 

Skilling is an ongoing practice that needs to constantly evolve alongside the business and technology landscape. Staying ahead requires an enterprise-wide strategy that aligns ever-changing business priorities with always-on skill-building. 

—Jeana Jorgensen, Corporate Vice President, Microsoft Learning

Fostering a culture that prioritizes security

As AI impacts everyone’s role, make security awareness and responsible AI practices shared priorities. Encourage your team to weave security thinking into their daily routines—creating a safer environment for all. As Vasu Jakkal, Corporate Vice President of Microsoft Security highlighted in her blog “Cybersecurity Awareness Month: Security starts with you,” it is critical that security become part of your organization’s culture and norms. 

Check out our new e-book, Skilling for Secure AI: How Frontier Firms Lead the Way for practical steps for leaders to upskill their workforce in identity management, data governance, and responsible AI practices.

From awareness to action

In the agentic AI era, people continue to be our most valuable resource. It’s essential to empower them with AI and equip them with the skills they need to use AI responsibly and securely. Cybersecurity awareness should go beyond designated months or campaigns; true awareness means taking meaningful action.   

Here are three actions you can take today to maximize your AI investments: 

1. Share the Be Cybersmart Kit with your employees. It includes tips for protecting yourself from fraud and deepfakes, guidance on safe AI usage, and key security best practices.
2. Invest in people: Focus on upskilling initiatives that support your AI transformation, cloud modernization, and security-first strategies.
3. Champion a security-first culture: Ensure cybersecurity is integral to every business discussion and woven into your overall strategy. 

Microsoft guide for securing the AI-powered enterprise

Download the guide

The post From awareness to action: Building a security-first culture for the agentic AI era appeared first on The Microsoft Cloud Blog.

Increasingly, Frontier Firms—those at the leading edge of innovation and productivity—are demonstrating how AI can unlock new levels of competitive advantage. However, realizing this potential goes beyond simply deploying tools and solutions; it requires a continuous, enterprise-wide strategy that aligns skill-building with broader business priorities. As these organizations continue to transform, new skills and capabilities will inevitably become essential. 

For Frontier Firms, AI skilling is a continuous investment, as well as an integral job requirement. In our conversations with customers, many have indicated they expect their employees from all disciplines to spend 10–20% of their work week on learning and integrating AI into their daily work to deliver the most impact.

At Microsoft, we’ve seen firsthand how creating a culture of continuous AI learning empowers employees, and we shared our insights in our previous blog, “Accelerate employee AI skilling: Insights from Microsoft.” Now, we’re shifting the spotlight to our Frontier Firm customers—drawing key takeaways from the skill-building strategies they’re using to turn ambition into adoption with an AI-ready workforce that drives innovation.

1. When leadership champions AI learning, the whole organization moves faster

Executive alignment plays a pivotal role in shaping how AI adoption takes hold. When leadership drives the learning agenda and anchors it in business strategy, it sets the stage for cultural change. One of the most effective ways to do this is through cross-functional collaboration that connects governance, priorities, and impact. We’ve seen this play out at organizations where leaders are shaping AI strategy through unified, cross-functional action. 

Customer highlight: Bupa APAC is driving smarter healthcare solutions with an AI-ready workforce and Microsoft Copilot 

With AI reshaping healthcare, Bupa APAC saw an opportunity to make customer experiences more seamless, proactive, and personalized—from automating claims processing to developing preventative care plans tailored for individual needs. Bupa created a Center of Enablement that aligned risk, legal, technology, and business teams to develop a unified approach to responsible AI use. This early collaboration ensured alignment between AI ambition and the needs of different functions, laying the foundation for a tailored, role-based skilling strategy supporting the business priorities. It developed an AI skilling strategy and created a structured environment for AI experimentation, using Microsoft 365 Copilot, GitHub Copilot, and other AI-powered tools to automate tasks, refine workflows, and improve efficiency. Bupa upskilled its workforce with Microsoft 365 Copilot and GitHub Copilot, generating more than 410,000 lines of AI-assisted code, initiating more than 30,000 Copilot chats, and accelerating more than100 AI use cases to improve care.

AI is a critical part of our transformation, but technology alone isn’t enough. Our focus has been on building the right skills and governance to make AI effective across the organization.

—Akhil Mittal, Cloud Platform and DevOps Manager, Bupa APAC

The Bupa APAC example reinforces how a top-down AI strategy that embraces a culture of learning creates clarity and a shared purpose across teams—equipping employees to not only understand but also act on AI goals. For leaders thinking through their own approach, explore Creating an AI Learning Culture: Five considerations to empower teams with AI skills that can guide you and inspire a skills-first mindset.

Creating an AI learning culture

Read the paper

2. Tailored learning builds confidence and drives adoption

No matter how you encourage workforce experimentation and AI learning, one principle remains essential: generic training rarely leads to real behavior change. A tailored approach targeted to individual skill levels and job requirements is essential. Employees are far more likely to adopt AI when they understand how it applies to their day-to-day work. This clarity doesn’t just drive individual confidence, it empowers employees to solve problems faster, service customers better, and contribute to outcomes that matter to the business. Leading organizations offer a compelling example of how connecting learning to everyday responsibilities can power transformation at scale. 

Customer highlight: Commonwealth Bank invests in AI skills and Microsoft Copilot to drive innovation 

As customer expectations rise, Commonwealth Bank of Australia (CommBank) seeks to harness AI to develop smarter, more secure, and highly customized banking experiences at scale. Recognizing that AI’s full potential depends on workforce readiness, CommBank launched a structured skilling initiative to equip employees with the knowledge and tools to apply AI effectively across the organization. CommBank embedded AI skilling across all levels of the organization through three structured learning paths: 

1. Leading with AI equips executives and senior leaders with the skills to guide AI adoption strategically, facilitating responsible implementation and alignment with business priorities. 

2. Working with AI provides employees across departments with practical training to use AI-powered tools like Microsoft 365 Copilot to improve productivity and assist decision-making. 

3. Building with AI develops technical expertise among engineers, data scientists, and developers—offering specialized learning with tools like GitHub Copilot and Microsoft Power BI to create AI-powered solutions. 

AI skilling has equipped employees to adopt AI effectively, with 84% of 10,000 Copilot users reporting they wouldn’t go back to working without it and approximately 30% of GitHub Copilot code suggestions adopted—driving efficiency and smarter decision-making. 

With Microsoft 365 Copilot, early adopters reported saving 16% of their time by reducing repetitive tasks, allowing them to focus on more meaningful work and bring their best selves to what they do.

—Dan Jermyn, Chief Decision Scientist, CommBank

As the CommBank story shows, when AI learning is tailored to specific skillsets and the day-to-day realities of work, it becomes a catalyst for impact. From the frontlines to leadership, employees gain the confidence to use AI in ways that enhance productivity and customer value. For organizations looking to jumpstart team training and close skills gaps with tailored learning, we recommend the Microsoft Learn for Organizations. 

3. Generating organizational momentum is possible through peer-led learning communities

Pairing learning programs with peer-driven communities helps amplify early wins, reinforces skills, scales momentum, and transforms individual learning into collective progress. These communities thrive when employees have space to share real use cases, ask questions, and learn alongside trusted peers. It’s a model that brings learning to life, and one that is gaining traction with organizations around the globe. 

Customer highlight: AI and the human advantage: Adecco Group’s AI skilling strategy fuels productivity with Microsoft Copilot

Recognizing AI’s evolution and its impact on work prompted Adecco to provide AI skills to employees and job seekers. To stay competitive, it aimed to embed AI into operations while ensuring its workforce had the expertise to use it effectively. 

The company embedded AI across operations to automate tasks and improve decision-making. Through an internal AI operations team, training, microlearning, and Copilot, Adecco is equipping its employees with skills to apply AI effectively in daily work and client interactions. 

To support internal enablement, The Adecco Group created the AI Influencer Community, where employees engage with AI experts, share use cases, and explore best practices. In parallel, the company collaborated with Microsoft and worked closely with its Akkodis Tech Academy (a Microsoft Training Services Partner) on AI upskilling programs. These efforts have been deployed in 12 countries, training more than 12,000 employees in AI fundamentals, data analytics, and other critical digital skills, helping teams work more efficiently, support evolving client needs, and contribute to solution development. 

Skilling is really important for us because people are at the heart of our organization. We have a responsibility to ensure our people have the skills to engage with AI, use new tools, and embrace new ways of thinking.

—Caroline Basyn, Chief Digital and Information Officer, The Adecco Group

What stands out from Addeco’s experience is that scaling AI fluency didn’t hinge on formal programs alone—it grew from within. By allowing employees to learn from each other and explore AI together, you can create a more sustainable, community-powered model for adoption. This is a reminder that the most powerful adoption strategies empower connection and shared curiosity.

Bringing it all together to build an AI-ready workforce 

When considering these examples, a pattern emerges. Organizations leading in AI fluency aren’t simply adopting tools, they’re building the conditions for their people to thrive with them. While every organization requires its own unique approach, learning from current successes and adapting for your specific goals and workforce is key to achieving results. 

To help you advance your organization’s AI skilling efforts, we’ve created the AI Skills Strategy: The Starter Guide, a reflection tool to plan strategic conversations around AI skill-building. This guide is designed for the earliest stages of AI skilling strategy development before a formal plan is in place. It helps you clarify your skilling purpose, identify key stakeholders for all learning initiatives, and begin uncovering where skilling efforts can deliver the most value. By working through these high-level questions, you and your team can align shared goals and lay the groundwork for a tailored, adoptable AI skilling approach that can help you accelerate your organization’s AI growth and reach your business goals. 

¹ IDC InfoBrief, Sponsored by Microsoft, Business Opportunity of AI, IDC #US52019124, November 2024 

The post Discover three skilling insights that set Frontier Firms apart appeared first on The Microsoft Cloud Blog.

Organizations around the world are starting to see generative AI as a real game-changer. To stay ahead, many are already aligning their investments toward new AI-powered tools, platforms, and infrastructure. But despite the prospect of big returns, these businesses face a myriad of challenges when it comes to adoption.

One of the biggest hurdles? A recent IDC study, Business Opportunity of AI, suggests that it’s the AI skills gap. Many business leaders feel that their teams have yet to develop the strategic knowledge and technical skills necessary to know how to use the advanced tools they’ve been given.

The takeaway is clear: real AI transformation can only occur when your people are prepared for it. That’s where we come in.

Preparing your workforce for the future 

In a world of constant flux, your organization is only as agile as your people—and the skills they bring to the table. That’s why most learning and talent development professionals agree that continuous learning, paired with career development, is the key to keeping up with evolving business needs. The 2025 LinkedIn Workplace Learning Report shows how organizations that prioritize career development outpace others on key indicators of business success, especially when it comes to AI adoption.

Business leaders are getting the message—a skilled workforce is a key part of AI readiness—and now, they’re taking action. According to the 2025 Work Trend Index Annual Report, nearly half (around 47%) say their top workforce strategy over the next 12 to 18 months is to train the people they already have.

There’s a big mindset shift in how leadership is thinking about AI adoption and the future. It’s not just about leading the business anymore; it’s about leading the business with AI. Nearly three times as many C-suite executives have added AI skills to their LinkedIn profiles compared to just two years ago.

Lead by learning with curated AI resources  

Building AI skills has never been more vital. This is why hundreds of thousands of people of all levels, ages, and geographies joined the Microsoft AI Skills Fest 2025 to grow their skills. Thanks to our community of committed AI learners, on April 8, 2025, we earned a GUINNESS WORLD RECORDS™ title for the most users to take an online multi-level AI lesson in 24 hours.

The Microsoft AI Skills Fest 2025 may have wrapped up, but the learning doesn’t stop there. Here at Microsoft, we believe that everyone—students, tech workers, business professionals, and decision-makers across all disciplines—should be given the opportunity to develop the AI skills they need to build confidence, establish fluency, and thrive in the new AI economy. That’s why we’ve pulled together some of the best resources from this milestone event to help you and your team take the next step on your AI journey—no matter what your role is.

Check out our most popular training resources for business leaders and professionals, now available on demand.

You’ll find easy access to training content, including:

• Unlock productivity at work 
  Get a quick and practical introduction to AI in one 50-minute video. Learn what AI really is, how it’s being used in the real world, and how it can help you streamline tasks and reduce errors. You’ll even get hands-on practice with prompt writing, so you can start working smarter right away.
• Use AI for everyday tasks 
  Want to get more done with less effort? Explore this training module to see how AI can support your daily workflow, from simplifying repetitive tasks to sparking innovation. You’ll leave with a solid understanding of AI, as well as examples of use cases and tips for writing effective prompts. 

It’s time to start empowering your team to learn, grow, and innovate—so your organization can thrive in the AI economy.

Advance your teams’ career with learning paths from Microsoft and LinkedIn 

We know that everyone learns at their own pace, in their own way. That’s why we’ve teamed up with LinkedIn Learning, a trusted partner for millions of learners and organizations, to help your workforce build the AI skills they need by accessing training content on platforms they already know and use.   

Discover AI Skill Pathways, a comprehensive resource featuring over 150 pathways across 24 languages designed to help organizations build AI skills across a variety of roles. These learning paths and role-based credentials help learners of all levels develop, practice, and validate AI skills.

Here’s what you’ll find:

• Understanding AI: Great for leaders, managers, and professionals looking to build foundational knowledge in generative and responsible AI practices.
• Applying AI: Perfect for leaders, managers, and professionals looking to incorporate AI into their day-to-day role.
• Building AI: Ideal for AI power users working with low-code or no-code tools, as well as seasoned developers building custom generative pre-trained transformers (GPTs).
• Training and maintaining AI: Designed for tech professionals and AI and machine learning engineers who need more specialized training in managing AI models.
• Deep specialization in AI: For your most technical teams, including DevOps, data scientists, and research and development (R&D) professionals, ready to dive into advanced topics like AI for IT operations (AIOps), machine learning operations (MLOps), large language model operations (LLMOps), AI security, and AI cloud infrastructure. 

Take advantage of this select AI training content at no cost. But don’t wait—this opportunity ends on July 31, 2025. After that, the LinkedIn Learning content will no longer be available for free.

Now’s the time to start building strong talent pipelines by equipping your people with mission-critical, future-ready skills—guided by LinkedIn’s unique workforce insights and Microsoft’s AI expertise. 

Accelerating AI readiness 

Having the right skills in place is key to scaling AI across your business. Leaders who know this are better positioned to prepare their teams and stay ahead of the competition. 

We know this firsthand. At Microsoft, we’re on our own AI learning journey, putting AI to work in all facets of our business and regularly exploring how to train our own teams so they can lead in an AI-powered world. This journey is transforming how we market, sell, build, and innovate, allowing us to deliver value to our customers while building a foundation for the future. It’s also how we’ve developed a series of best practices and resources that now guide our employee AI skill-building initiatives.

As you embark on your own AI journey, we hope these insights help you chart a path forward. There’s no one-size-fits-all approach to long-term AI success, but with access to the right tools and the right guidance, your workforce—and your organization—can be poised to grow, transform, and lead.

10 best practices to accelerate your employees’ AI skills

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The post Empower your teams to grow their AI skills and boost adoption appeared first on The Microsoft Cloud Blog.

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

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

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

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

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

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

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

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

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

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

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

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

How to think about modernization

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

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

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

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

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

Understanding the state of your IT estate

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

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

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

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

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

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

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

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

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

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

Modernize for AI Innovation

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

Learn more

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

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

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

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

One “yes” can change everything 

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

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

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

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

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

Today, Founderz itself is helping change lives.

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

AI skilling done differently 

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

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

Expert content in student’s native language 

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

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

Small group collaboration  

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

Multilingual student support around the clock 

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

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

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

Education means opportunity

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

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

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

Unlock the future—Join the Microsoft AI Skills Fest 

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

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

Let’s make history together.

AI Skills Navigator

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

The post Founderz: Transforming AI education to unlock opportunity appeared first on The Microsoft Cloud Blog.

Although every organization’s AI transformation is unique and blueprints are scarce, we’ve learned that having the right skills across the organization is key. By implementing skill-building initiatives throughout the company, we’re reimagining how we work at Microsoft and aligning those initiatives to the functions that are critical to how we do business.

Through this process, we’re constantly uncovering valuable insights on how to lead by learning—often developing the playbooks from scratch. By applying these insights, we advance our AI transformation and benefit our workforce, customers, and partners around the world. We’re glad to share our findings with you to help your teams skill up to make the most of AI for innovation, growth, and opportunities.

Grow your AI skills with specialized training programs

Organizational transformation now requires AI-first skills; yet it can be challenging to plan modern and effective skill-building programs.

We understand the importance of providing our employees—both technical and non-technical—with the AI skills to grow and evolve with the business and the technology, along with the ability to apply these skills every day. Teams across Microsoft have established innovative and effective AI training programs that cater to specific roles in marketing, sales, engineering, and beyond.

Although there’s no one-size-fits-all approach to AI training, our experience has yielded some widely applicable takeaways which can be helpful to organizations that want to build AI skills. Our new e-book, 10 Best Practices to Accelerate Your Employees’ AI Skills: Lessons and experiences from Microsoft’s skilling initiatives, highlights some of the vital lessons we’ve learned that can help support you in implementing skill-building programs crucial to your AI transformation.

Power your AI transformation with our AI learning highlights

The e-book explores many of the lessons we’ve learned in our ongoing AI evolution. Our experiences can help inspire and inform your path forward, too, as you and your teams get skilled up and ready to power AI transformation with the Microsoft Cloud. In particular, the e-book showcases stories from AI skill-building initiatives implemented by four Microsoft teams:

• Microsoft Marketing, a diverse collective of professionals, ranging from creative roles to business strategists and technical experts.
• MCAPS Academy, the team responsible for training sellers globally within the Microsoft Customer and Partner Solutions (MCAPS) organization.
• Worldwide Learning Engineering, the team tasked with architecting and building apps and platforms that support MCAPS and some of the Microsoft skill-building offerings for customers and partners.
• The Microsoft Garage, an innovation platform that enables collaboration and experimentation through hackathons, workshops, talks, training sessions, and more.

Here’s what we learned.

10 best practices to improve employee AI skills

1. Give space for exploration

Encourage a culture of learning by providing employees with the time and tools to explore AI.

Our Worldwide Learning Engineering team has dedicated time to delve into AI, and this fosters an environment where curiosity and innovation can thrive. Additionally, The Garage’s experiments, such as the SkillUp AI Challenge, provide employees with a sandbox for practical AI applications, encouraging both personal and professional growth.

2. Make learning fun

Create a low-pressure, engaging environment where employees can learn at their own pace.

The Garage’s SkillUp AI Challenge incorporates fun, interactive exercises that make AI relatable and enjoyable for all skill levels. Similarly, the Marketing AI practitioner hub offers gamified learning paths that enable marketers to integrate AI into their daily workflows in an entertaining way.

3. Provide clear, structured learning paths

Simplify the learning experience with structured paths tailored to different skill levels and roles.

MCAPS Academy Flight Plans offer role-specific learning paths, helping to ensure that technical and non-technical sales teams alike have clear directions for their AI learning. Moreover, the Marketing Learning team has developed a curriculum that supports marketers in becoming regular AI practitioners through well-defined learning stages.

4. Make it role specific

Adapt AI training programs to the unique needs of each role within the organization.

The Worldwide Learning Engineering team focuses on providing engineers with opportunities for deep technical engagement through dedicated learning time and advanced AI tools. At the same time, the MCAPS Academy addresses the specific needs of a different job role—sales—by blending foundational knowledge with real-world applications to enhance AI fluency.

5. Start with foundations

Begin AI training with foundational knowledge to help ensure that all employees have a solid understanding of AI basics.

The Marketing Learning team introduces marketers to AI through simple, foundational concepts before progressing to more complex applications. Likewise, the MCAPS Academy provides basic AI training to new hires before guiding them through more advanced, role-specific learning paths.

6. Have a plan to update the content regularly

Maintain the relevance of AI training programs by regularly updating content.

The Worldwide Learning Engineering team continuously refreshes its training materials to keep up with the latest advancements in AI technology. Meanwhile, The Garage schedules regular updates for its skill-building exercises to help ensure that they remain engaging and current.

7. Drive awareness and continued adoption

Promote ongoing AI learning and adoption through awareness campaigns and reinforcement.

The Marketing AI practitioner hub provides regular touchpoints to encourage consistent AI practice among marketers. Similarly, the MCAPS Academy uses newsletters and internal communications to keep the sales force informed and engaged in AI learning.

8. Set clear guidelines for responsible use

Establish and communicate guidelines for the responsible use of AI to maintain standards.

The Marketing Learning team’s curriculum emphasizes the importance of responsible AI use, providing clear guidelines and best practices. The Worldwide Learning Engineering team also integrates responsible AI principles into its training sessions, highlighting the significance of these considerations in AI development.

9. Let employees learn from each other

Facilitate peer-to-peer learning opportunities to enhance AI skills through collaboration.

The Garage hosts show-and-tell sessions where employees share their AI projects and insights. For engineers, the Worldwide Learning Engineering team organizes knowledge-sharing workshops to promote collaborative learning.

10. Leverage existing resources

Take advantage of available resources to support AI skill-building initiatives.

The MCAPS Academy makes the most of existing training platforms and materials, integrating them into its AI learning paths. And The Garage draws on external AI tools and resources to complement its interactive learning programs.

AI learning hub on Microsoft Learn

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Build value and accelerate growth with AI skills

Our experiences as customer zero for AI training have been transformative—and we’re just getting started. By empowering our teams with the right skills, we’re not only driving innovation within our organization but also setting a strong foundation for the future, supporting our employees and customers, creating business value and growth, and fostering innovation.

As organizations around the world look to build AI skills and to scale this powerful technology throughout their business, we’re glad to share these insights to support your AI transformation. Together, we can lead in the AI-powered world and unlock new levels of value for our workforce, customers, and partners—today, tomorrow, and beyond.

The post Accelerate employee AI skilling: Insights from Microsoft appeared first on The Microsoft Cloud Blog.

When Microsoft released Copilot in March 2023, our customers had questions. They wanted to know how they could use Copilot to be more productive at work and in their personal lives. They were curious how to use Copilot within Microsoft 365 applications, like Word, PowerPoint, Outlook, and Teams, and how to leverage Copilot for developers, data scientists, and security professionals.

To answer these questions and more, we created the Copilot learning hub in May 2024. I recently asked Dona Sarkar and Dan Wahlin, Microsoft Principal Cloud Advocates—and members of the learning hub team—to share some of their stories about creating this powerful resource.

The Copilot learning hub is “designed to meet learners wherever they are along their learning and adoption journey,” said Dona, “from understanding and using copilots, to customizing them with their own data, and, finally, building their own copilot.” The learning hub caters to technical audiences and ensures that each learner accesses content that is tailored to their learning goals. These resources augment the content available on the AI learning hub, which is designed for both technical and non-technical learners.

These goals are grouped into four task-based Microsoft Learn Official Collections—understand, adopt, extend, and build – providing content specific to each stage of the learning journey. Each collection contains a variety of training modules, documentation, and videos. Learners can even access content that is applicable to specific tech roles, such as administrators, data analysts, and developers.

One learner favorite on the hub is the video library, which provides Copilot instructional content and customer use cases. According to Dan Wahlin: “People love to see what’s possible and the benefits from using a copilot, so our videos focus on that angle. We show how a copilot makes both personal and work life easier and more productive, how creativity is enhanced, and how people can get started and immediately experience these benefits themselves.”

Dona adds that the videos demonstrate the diverse applications of Copilot across Microsoft products and services. “People share their favorite Copilot use cases and how they leverage Copilot in various scenarios,” she said. “This approach makes the content more relatable and engaging by featuring stories from a wide range of professionals.”

Check out this video to learn how cultural shifts and human factors play a crucial role in the successful implementation of AI technology like Copilot.

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Dona shared her own story about how learning a new programming language has changed now that she can rely on Copilot to assist her with her learning. Recently, she used GitHub Copilot as a coding coach to learn Python after working in C# for 20 years. Dona recalls it took her a full year to learn JavaScript years ago, but only one month to learn Python using Copilot. “That’s a real game changer. Imagine how Copilot can help expert and novice programmers alike gain new skills and do their jobs better,” she said. This is the true promise of the Copilot learning hub—putting expert content to work for you so you can excel using Copilot.

With all the excitement around Copilot, we continue to provide new resources for learners. “We’ve received great feedback on the Copilot learning hub from learners. They’ve expressed how they appreciate the comprehensive resources and real-world examples available,” Dan said. “They’ve also provided us with great feedback that we’re consistently applying to continue to take the Copilot learning hub to the next level.”

Erica Woods, Director of Contractor Programs & Philanthropy and Principal at Apex Systems in Tampa, FL, has completed several modules and videos showcased on the learning hub. “I appreciate several things in the Copilot learning hub,” Erica said, “including insights on different ways to apply the technology that are easy to build directly into my day-to-day, the bite-sized chunks the training segments are delivered in, demo-style learning, the fun and conversational style of the videos, and the variety of topics included.” 

So, what’s next? These are some new resources you can expect to see in the coming months, each designed to further streamline your workflow and enhance your Copilot experience:

• In the weeks leading up to Microsoft Ignite, you’ll see new content on the “agentification” of Copilot. What are agents? They are copilots that can act independently, triggered by events—not just conversation—enabling you to automate and orchestrate complex, long-running business processes with less human intervention. For example, an “order taker” copilot can handle the end-to-end order fulfillment process—from taking the order, to processing the order and making intelligent recommendations and substitutions for out-of-stock items, to shipping to the customer.
• We are also working on stories showcasing how Microsoft customers and partners are helping their customers use Copilot, particularly in specialized industries like finance, manufacturing, and others.

Coming up: Get AI ready: Discover AI skill-building with Microsoft Training Services Partners

In our next Get AI ready blog, discover how Microsoft Training Services Partners (TSPs) are helping organizations worldwide build AI skills and stay competitive. Learn about the benefits of AI-powered tools and services, and how TSPs provide customized training plans to ensure your teams are AI-ready. Read inspiring stories from Sulava, Skillsoft, and Koenig Solutions, and find out how they are transforming businesses with AI. Don’t miss out on this opportunity to upskill your workforce and drive innovation.

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