That’s the learning efficiency paradox. AI is meant to create greater efficiency and productivity, but employees have to be able to use it well. If they can’t, they may not make any gains and AI may even become a blocker. 

Businesses are not yet seeing the ROI on their AI investments, and this is why. Speed isn’t everything. AI works fast, but unless we reimagine work and learning, that speed comes at the cost of people, processes, and real innovation. Without guidance and intentionality along with it, people can become overwhelmed, processes can descend into chaos, and “innovation” is limited to whatever commoditized knowledge and ideas AI has to offer.

The tension between scale and substance, speed and depth, activity and impact, is reaching a fever pitch. It’s not enough to create and complete training quickly; people need to absorb and apply knowledge effectively.

It’s time to redefine efficiency in a way that’s sustainable for long-term business success. In most organizations, AI transformation initiatives are targeting speed and productivity above all else. But that can’t last because people won’t be able to keep up. 

Efficiency is not just about moving faster, it’s about doing things better. And it starts with people, not technology. 

The Efficiency Paradox and the Human Side of AI Transformation

Getting AI transformation right may seem like a technology problem, but it’s also a people problem. AI was supposed to increase efficiency, but many businesses aren’t seeing the results yet. In fact, nearly 95% of businesses saw zero return on in-house AI investments and only 15% of Gen AI users report their organizations see significant ROI from it.

Perhaps understandably, the tendency is to view the lack of progress as a technological issue, so companies are continually funneling money into AI initiatives. After 85% of leaders increased AI investments over the last year, nine out ten enterprise leaders still expect to spend more on Gen AI next year, according to Knowledge at Wharton (88%) and Deloitte (91%).

Yet, despite the sharp uptick in AI spending, The Federal Reserve Bank of St. Louis reported that in the last year, AI use at work has only risen from 33% (2024) to 37.5% (2025). Similarly, a global PwC report found that 14% of respondents are using Gen AI daily, compared to only 12% in 2024. The increases in use are not yet aligning with the massive spending on these initiatives.

The bottom line? To recognize the deep value AI promises, employees will need to upskill both faster and more effectively, as the number of skills they need and the speed at which they need them continue to grow. To do that, businesses need to invest in the human side of AI transformation. In the end of the day, AI initiatives need to be effective for the people who will use them to innovate, to find new ways of working, and to ultimately drive business growth.

AI’s Role In the Learning Efficiency Paradox

While AI is certainly driving the urgent change that businesses are grappling with, it’s also contributing to the solution. That’s the other piece of the paradox.

How? 

AI’s capabilities, when used correctly, open the door to untapped potential in enabling the fast and thorough skill development people need to keep pace with AI. You need learning efficiency. Static learning content libraries and self-service development won’t do the job any more. AI unlocks opportunities for personalization, interactivity, and innovation. 

Personalization

When your employees have access to the most relevant content possible, it means they don’t have to waste precious learning time looking for the right content. AI can use skill data and the foundations of learning science to ensure content is always relevant for the learner’s role and skill level. 

Interactivity

AI allows for more responsive content than has ever been possible before. This goes beyond personalization: You can practice real conversational scenarios, practice for key interactions, and get immediate feedback. This is an unprecedented way of learning that helps cement capability. 

Innovation

Innovation comes in many forms, and AI has a lot of potential to drive creative improvements to existing processes. According to McKinsey, half of AI high performers expect to use AI to transform their businesses, mostly through redesigning workflows. Reimagining traditional processes and procedures can be the key to greater efficiency, with human and AI capabilities operating in tandem. 

The learning efficiency paradox is both an opportunity and a new challenge. Take the opportunity to join in-depth, expert-led discussions on solving this efficiency paradox at Degreed LENS 2026 in Orlando, Florida. From an agenda filled with workshops, roundtables, and sessions rich with insights, you’ll learn from and network with the best in the business.

The post What Is the Learning Efficiency Paradox? appeared first on Degreed.

What Is Adaptive Learning?

Adaptive learning adjusts automatically to the needs of the individual based on their skills, role, goals, and proficiency level. It’s highly personalized, responsive, and interactive. It’s contextual, it’s dynamic, and most importantly, it cuts down on time wasted; no more content scavenging, no more time spent on content that’s irrelevant to experience level, and no more waiting for feedback. That way, every moment of development is useful. 

The personalization is fed and enforced by the rich data and analytics that arises from the learning process. Adaptive learning provides more than just completion data: there’s real measurement of knowledge gain and skill growth. 

What Does Adaptive Learning Look Like in Practice?

Adaptive learning answers a longtime need in the learning industry: The ability to learn in the flow of work. For example, AI capabilities make it possible to produce topic-rich, accurate quizzes at scale to easily test knowledge retention. Conversations with AI can adapt in real time, allowing employees to practice challenging soft skills or presentations on complex topics. Adaptive learning makes it possible to provide customized, role-specific paths and instant feedback, so that it’s easier to benchmark performance and iterate. 

This level of flexibility and personalization means learning and work can entirely coexist and boost each others’ effectiveness Here are some example scenarios:

Example: Your team needs to quickly master complex new market regulations. Rather than having them complete a single, static training, AI-generated quizzes allow you to assess understanding.

Simply checking a “completed” box, doesn’t mean your team is actually prepared to apply their knowledge in the field. Any skill or knowledge gap can directly impact business outcomes and performance, so it’s essential to find out what your people actually know. Once you see where the gaps are, you can curate the right content to fill the gaps for each individual, rather than providing another blanket, one-size-fits-all training session for everyone that misses the mark after the first one.

Example: Your company is launching an important new product and your sales team needs to deliver the new pitch. You can provide them with an AI-powered coach that’s always available and gives real-time feedback.

This allows them to practice their pitch risk-free. They can iterate, apply feedback, and improve their approach before stepping in front of your potential customers. As they learn and practice, they are engaging in practical skill-building with real business impact.

Example: The launch of a new AI tool has direct application for your product team, and they need to build capabilities in an emerging industry skill. You are able to get them up to speed more quickly with AI-curated and expert-checked learning pathways.

As the skills needed constantly evolve, content pathways can now be generated at the same pace, which means your people can absorb relevant content faster. Degreed Open Library, for example, provides pathways on the most in-demand emerging skills in the market, and every pathway is automatically updated biannually to ensure content is fresh and accurate.

Use cases for adaptive learning are growing, as day-to-day work requires more interactive, dynamic, and diverse learning modalities to keep pace with the capabilities employees need.

How Do You Enable Adaptive Learning?

Context is the key. AI has opened the door for adaptive learning experiences, but to be successful, AI first needs the right context. Otherwise, the information it provides is no more tailored than a general LLM or AI assistant. 

To ensure AI is purpose-built for learning and upskilling your team, it needs a context in:

• Learning science
• Verifiable skill data
• Integration into systems
• Organizational context aligned to strategic goals

With that as the foundation, the AI is then set up to successfully adapt to the needs of the individual. 

What’s the Future of Adaptive Learning?

Tech capabilities are growing every day. We do not know what will be possible two years from now, but I assure you that learning at work will become a lot less like a static training session and a lot more like one-on-one coaching with a trusted expert. Learners will be laser focused on content that is actively growing their knowledge and skill set, and they will be putting their new knowledge and skills into practice in low-risk scenarios.

L&D is in the process of evolving from providing content that supports business objectives to delivering AI-native learning experiences that proactively progress business objectives. 

The post Adaptive Learning: What It Is and Why It Matters appeared first on Degreed.

Completion rates prove it got done, and compliments prove employee satisfaction, but they don’t prove learning effectiveness. Execs want tangible evidence that the investment paid off. You need to show that people retained the information and are ready to use it on the job. And if it didn’t work, you need to identify where more learning is needed. 

So, what’s the answer? Test it.

Quizzes, a new experience within Degreed Maestro, enable you to quickly create and deploy AI-generated quizzes to ensure knowledge retention and measure learning effectiveness. So, next time your execs ask if it worked, you have relevant data to support your answer.

The Old Way: Manual Quiz Creation

Seeing the value of quizzes? Easy. Executing them manually, accurately, and at scale? Difficult.

Creating and deploying quizzes at scale is traditionally manual and incredibly time-consuming. It often requires extensive input from busy subject matter experts (SMEs) to draft questions, which is an inefficient use of their high-value expertise and often delays deployment. 

Reliance on manual creation and SME availability makes it difficult to scale and maintain up-to-date quizzes. This is more true now than ever, given that the skills and knowledge employees need are constantly changing. 

The New Way: AI-Generated Quizzes

With Maestro quizzes, admins can create quizzes in minutes, drastically reducing the time and effort spent. Through a text-based conversation with Maestro, you can guide Maestro to create a custom quiz on any topic and adjust parameters, like the number of questions and difficulty level. It can also create quiz questions based on existing documentation. This is a simpler way to harness the knowledge of SMEs without having to involve them in manual question generation. 

After employees finish the quiz, in-app reports enable admins to gauge their level of knowledge retention. These reports help identify consistently incorrect answers and, therefore, knowledge gaps where more learning is needed.

The quizzes are directly connected to the Degreed platform, allowing you to manage workflows like assigning quizzes or reporting on results. That makes it easy to identify where more learning is required so you can create more effective experiences that close knowledge gaps, learning more across the business.

Create Business Value

Real-world Applications for Quizzes

Example: Preparing for a Product Launch

During a new product launch, your revenue teams are inundated with information: value props, product functionality, go-to-market strategies. It’s a lot to take in, and it’s difficult to gauge whether your people are ready. 

With Maestro quizzes, you can evaluate whether your people have a grasp on key components of your new product. You can even create different quizzes for different audiences, since the information your sales team needs to remember is different from what your implementation team needs to know. By using existing documentation, you can generate quizzes focused on these different audiences within minutes. 

Example: Checking Long-Term knowledge Retention for AI Transformation 

Many organizations have ambitious targets for adopting AI in the business. This knowledge likely doesn’t exist at scale within the business, so organizations need extensive training and upskilling. By embedding a quiz at the beginning and at the end of a pathway, you can measure how much the workforce learned about implementing AI, so you can tie learning back to strategic business initiatives.  

Example: New Customer Onboarding Process

Quizzes can reinforce process and procedure updates. If you’ve launched a new customer onboarding procedure, employees need to remember the correct process, what to do, and what not to do. You’ll have visibility into their readiness and procedural sticking points that may require extra training.

Quizzes As Part of a Larger Learning Journey

Quizzes are powerful by themselves, but are enhanced when combined with other learning initiatives, such as pathways or academies. By including quizzes at the end of these experiences, you can evaluate the effectiveness of those programs and identify where they may need new or different content. 

Embedding quizzes inside Degreed also improves the learner experience, providing a UI that is consistent across experiences. And it helps you consolidate tech, reducing cost and administrative load with fewer platforms to maintain.

The post Create AI-Generated Quizzes to Measure Learning Effectiveness appeared first on Degreed.

The first was the printing press, which codified and spread knowledge at a scale the world had never seen.

The second was the industrial school system, which was built to skill up entire generations for factory and office work.

The third was the internet, which unlocked access to knowledge for billions. It took learning beyond traditional classrooms—into the workforce, into your homes, across your lifetime.

Now, we’re entering the fourth moment: The rise of AI.

Efficiency Isn’t Everything

AI is already embedded in our meetings, documents, and systems. But just because AI is infused into the work, it doesn’t mean people are learning. If anything, so far, AI has made people more efficient, but not more capable. Yet.

That’s a problem. Because most organizations are using AI for one thing: efficiency. That’s great, but speed does not equal skills.

Infrastructure Still Matters

We’ve seen this pattern before. When YouTube arrived, it revolutionized content distribution. It made countless learning resources available everywhere.

But it didn’t solve organizational learning. It didn’t create more capability. It also didn’t solve organizations’ needs for managing employee learning.

Why? Because infrastructure still matters. We need systems, context, feedback, and outcomes. 

That applies to AI too. A chatbot on your company portal is not a learning strategy. A CoPilot that summarizes meetings and HR policy documents will not build your bench strength in those topics. Answers don’t build capabilities.

What separates serious, successful AI learning systems isn’t going to be the model, it’s going to be the infrastructure behind it. It’s going to be the foundation that the AI is based on, including:

• Learning science
• Verifiable skill data
• Integration into systems
• Organizational context aligned to strategic goals

If your AI tools don’t have that, they will not be optimized for learning. That structure is what makes the difference. That’s what will determine the learning impact of this moment.

The Challenge to Upskill Better and Faster at Work

Let me be direct: According to WEF and Accenture, 60% of the world’s workforce need to upskill in the next five years. That’s an increase of 10 percentage points from 2020. And only about 40% of C-suite leaders say they are prepared, which is down 10 percentage points from 2020. 

We knew this skill gap was coming five years ago, and leaders are even less prepared for it now. This means that more people need learning and more skills, quicker, now than ever before in history. 

The concept of “just-in-time learning” was built in the third wave, the internet wave, and it was all about connecting people to content when they need it. But now, work itself is changing. Tasks are being automated. Roles are more fluid. Knowledge has become cheap, yet judgment, adaptability, and creativity are not.

We need a new model for learning. One that matches the pace of change and the reality of today’s AI world. That future looks something like this:

• Adaptive learning skips what people already know and targets the exact skills they’re missing.
• Real-time skills intelligence lets you close gaps before they slow you down. 
• AI helps people get smarter and better at their work, not just faster.

And that future? It’s here.

The post Why AI Infrastructure is a Learning Differentiator appeared first on Degreed.

A few weeks after launching Degreed Open Library, one of our clients, a leading global tech company, told us exactly what happens:  

“Usage is already higher than LinkedIn Learning.”

They didn’t promote it heavily. They didn’t roll out flashy campaigns. Instead of offering employees a sea of content to wade through, they launched a set of targeted, AI-curated learning pathways tied directly to the skills their people needed to succeed.

What is Degreed Open Library?

Degreed Open Library is an AI-curated, ready-to-deploy content library of structured learning pathways designed to help people build in-demand skills faster, with less friction, less noise, and more relevance.

With skill-based learning pathways, Degreed Open Library gives you a smarter way to activate your content. And because each pathway is bite-sized and easy to launch, learners stay engaged, without needing a roadmap or a long list of prerequisites.

The problem: Traditional content libraries are expensive and high maintenance

Large content libraries promise more–more variety, more access, more engagement. But what learners often experience is the opposite: more friction, more confusion, and less actual learning.

As L&D and IT teams juggle growing responsibilities, they need a smarter solution, one that gets people learning faster, with content that’s relevant and purposeful.

The solution: AI-curated learning pathways 

Degreed launched Open Library in April 2025 with 100 curated learning pathways focused on the most in-demand skills. In July, we expanded that offering with 100 more “Language Bundles” in Portuguese, Spanish, French, and German, removing barriers for learners in global teams.

And we’re just getting started.

Coming this October, Degreed will release 150 new pathways aligned to high-growth industries, including:

• Consumer Retail
• Healthcare
• Manufacturing
• Customer Experience
• Finance
• Media & Telecom
• Professional Services

That’s 350+ AI-curated pathways, included with every Degreed Learning instance—no extra license required.

These ready-to-go pathways are designed to give employees a strong starting point, covering the foundational skills your workforce needs now. But every business is different. That’s why we also offer AI-curated pathway services as an add-on: to help you create highly targeted learning aligned to your unique goals, roles, and workflows.

Our AI-curated pathway services can help you create role-specific learning experiences aligned to your workflows and strategic goals. We’ll handle the heavy lifting. You get a smarter, faster way to deliver value.

From confusion to clarity: the power of curation in your content library

Degreed Open Library isn’t just another content library. It’s built to reduce friction and guide learners to exactly what they need, when they need it.

Instead of endless search results or generic playlists, AI curates the best content into structured pathways made up of articles, podcasts, videos, and courses. These pathways are always up-to-date, aligned to in-demand skills, and relevant to real roles and workflows.

Here’s what that unlocks:

1. Faster time to value

Instead of spending months designing programs, you can deploy ready-to-go pathways in minutes. Employees start learning immediately, without needing a map.

2. Less friction, less time, more focus

Employees don’t want to browse an endless catalog, they want to build skills. When learning is buried in lengthy search results or buried under generic playlists, they tune out.

AI-curated pathways remove that friction. Learners get clear, role-aligned recommendations that feel immediately relevant. They know exactly why it matters, how it connects to their job, and what comes next. That clarity leads to higher engagement, faster completion, and better on-the-job application. 

Degreed Open Library offers bite-sized learning within each pathway making learning more achievable during natural downtimes like lunch breaks or between meetings. This flexibility boosts engagement, accelerates completions, and enables quicker on-the-job application.

3. Smarter content spend

With targeted, curated content that people actually use, organizations can reduce their reliance on expensive library subscriptions and stretch their L&D budget further.

In fact, some of our customers are already exploring ways to eliminate or reduce their content subscriptions. The excitement is palpable as they explore how to redistribute their L&D budgets to higher value technologies or programs.

“My team will explore the library of resources to assess if we can match the learning content we get from [a leading content provider]. If Open Library is good enough for our learning needs, we might consider unplugging [a leading content provider] or at least reducing our number of licenses.” 

Takeaway: Stop paying for content people don’t use

L&D and IT leaders don’t need more content. They need more impact.

Degreed Open Library helps you deliver that with:

• High-quality, relevant content curated from trusted sources
• AI-powered pathways built for your business and your people
• Clearer learning journeys, higher engagement, and measurable results

The post The Content Library Hack Every Learning Leader Needs appeared first on Degreed.

Traditional learning systems aren’t built for this complexity. But Degreed is. With Degreed Maestro, we’ve built AI that is purpose-built for learning and that amplifies workforce development. Degreed Maestro helps organizations pinpoint skill needs, personalize development, and measure change, so you’re always building the right capabilities at the right time no matter how fast or unexpected the change.

Using Degreed AI to pinpoint needs: clarity in the chaos

Knowing your destination is critical, but so is understanding where you’re starting from. Fragmented data, outdated taxonomies, and a lack of standards make it nearly impossible to identify workforce skills with confidence. And that’s a major risk when talent is your most valuable asset.

Degreed Maestro’s Skill Review Coach provides a conversational method to validate individual skills in a consistent, unbiased way. The result? A dynamic, data-rich map of your organization’s skill landscape that makes strategic planning finally feel well-informed.

Degreed also helps untangle chaotic skill data. With skill level and label normalization, Degreed standardizes skill data across systems, providers, and languages by removing duplicates, correcting inconsistencies, and enabling a single, usable view of workforce capability.

From there, role-to-skill inference uses AI to identify the skills each job requires and maps them to your people. This is complemented by inferred skills for content, which tags every piece of learning content with the relevant skills it builds, making it easier to find relevant content for your role and goals.

Using Degreed AI to personalize development: At scale at last

Personalizing learning has always been the gold standard, but it’s notoriously hard to do at scale. Most organizations are stuck delivering generic training that doesn’t match employee roles, goals, or readiness. The result? Wasted learning, disengaged employees, and minimal business impact.

Degreed Maestro changes the game. Its suite of AI-powered experiences, including a Leadership Coach, Career Coach, and intelligent pathway curation, guides every employee with just-right resources for their unique goals, skills, and challenges. Employees don’t have to hunt for the right content. It finds them.

Meanwhile, Degreed Maestro’s AI-assisted pathway curation builds structured, targeted development journeys in minutes, saving time and driving deeper engagement.

Need something even more tailored? With Maestro Studio, you can build custom AI-native learning experiences—from onboarding bots to role-plays—purpose-built for your workforce. Now every employee can have a coach in their corner, and your L&D team can finally scale personalization at a fraction of previous cost.

Using Degreed AI to measure change: Making progress visible

Many organizations invest heavily in development, yet struggle to answer a simple question: Is it working? Traditional learning metrics (completions, hours logged) can be helpful but don’t show whether people are actually building the skills the business needs. And without clear measurement, it’s impossible to prove ROI or adjust strategies.

Degreed bridges that gap. We suggest using the Degreed Maestro Skill Review Coach again after learning completion to identify improvements in skill level that came from learning.  This helps teams validate what people know, not just what they’ve clicked.

Paired with profile skill suggestions, which recommend relevant skills based on a person’s role, learning activity, and aspirations, organizations can continuously calibrate and update each individual’s skill profile. This ensures data stays current and actionable.

Together, these tools create a live snapshot of your workforce’s capabilities, so you can track improvement, close gaps faster, and align development with strategy.

Smarter workforce development with AI for learning

AI is changing everything about the way we work, and now it’s changing how we learn. Degreed puts that power in your hands, helping you identify critical skill needs, deliver development that matters, and measure progress with clarity. Whether it’s through Degreed Maestro’s guided coaching or dynamic skill inference, AI for learning gives you the tools to lead workforce transformation. By connecting skill data to learning and business needs, it helps you solve the problems that matter.

Because in the end, it’s not just about training. It’s about building capabilities that fuel transformation. If you’re ready to connect learning to outcomes with intelligent precision, get a demo and see what Degreed can do for your business.

The post Pinpoint, Personalize, Prove: Degreed AI for Learning appeared first on Degreed.

The global consulting and technology services firm has long recognized that new managers need support. This has proven especially true in a learning climate marked by digital fatigue,  and what some have casually described as “death by pathway.”

At a time when the Capgemini business is scaling rapidly and client demands are growing more complex, the organization understands the importance of supporting its first time managers, to set them up for success right from the get-go.

Yet, traditional leadership programs are hard to scale, difficult to maintain, and often disconnected from the pace and priorities of the business. Learning delivery teams spend too much time managing training logistics, emails, and manual processes. And Learning teams want something more coherent, modern, and impactful.

To meet these challenges, Capgemini has launched an Emerging Leaders program—a guided, cohort-based experience built on Degreed Academies. The result? A 26% jump in skills proficiency, a big drop in attrition, and a 4.6 out of 5 learner satisfaction rating—proof that Capgemini first-time managers aren’t just trained, they are equipped to lead. 

Leadership Development That Starts Strong and Scales Fast

Co-created with business leaders and learning partners, Emerging Leaders follows a complete learning cycle. It’s more than a content playlist. It’s a full development journey designed to embed growth into everyday work, supported by nudges, mentors, reflections, and social accountability.

To build the journey, learning teams worked closely with HR and business leaders to define success, select content, and ensure the program reflected the company’s Leadership Vision—a set of guiding leadership principles that the company believes every employee should develop.

The result is an experience designed to match the expectations of a digitally fluent, ambitious audience. Employees progress through a six-week cycle, combining curated digital content, real-world projects, mentoring, reflection, and guided practice—all within a single Degreed-powered environment.

How Degreed Academies Makes It Possible

Degreed Academies gives Capgemini the infrastructure to deliver a holistic, guided leadership journey within a single, unified experience. From onboarding and nudges to live events and reflections, everything is centralized—no more spreadsheets, scattered tools, or siloed communications. And, with Microsoft Teams integration and built-in calendar functionality, participants stay on track while balancing their day-to-day responsibilities.

Capgemini uses Degreed Academies to structure monthly cohorts in a fully guided, week-by-week experience—layering content, leadership simulations, mentoring prompts, and reflection points in a clearly defined journey. Employees always know what to do next and why it matters. Automated nudges and personalized messaging help maintain momentum and accountability, without overloading delivery teams. By streamlining what were previously resource-heavy, manual tasks like scheduling, communications, and tracking, Degreed gives L&D professionals more time to focus on content quality, learner engagement, and business alignment.

Because everything runs through Degreed, Capgemini can access real-time insights on progress, engagement, and outcomes. This allows learning leaders to tweak delivery based on cohort behavior, and to identify bottlenecks early. With Degreed Academies, Capgemini isn’t just delivering training—it’s running a scalable, data-backed leadership product.

Features like live events, embedded reflections, and automated reminders help create a sense of connection and momentum.

Completion rates have peaked at 81%, with learner satisfaction scores averaging 4.6 out of 5.

More Than Engagement. Measurable Growth.

In 2024 alone, nearly 4,000 employees across 39 countries completed the program. Capgemini is on track to scale cohorts of 2,000 people per month in 2025. Attrition of managers who completed the program dropped to 6.5%, versus a much higher company average among the same target population.

And employee feedback has been resoundingly positive. Participants consistently call out the program’s relevance, structure, and challenge.

“The Emerging Leaders program was unforgettable among the other trainings I’ve taken,” said one employee.

“One of the most practical, useful, and challenging programs I’ve participated in,” said another.

Employees show a 26% average increase in skills proficiency from pre-program assessments to post-program outcomes. And more than 90% of those surveyed said they’d apply what they learned in their current roles.

A Model for Strategic Leadership Growth

Capgemini hasn’t just improved leadership development—the company has reimagined how it should operate. Instead of a fragmented or manual model, Emerging Leaders is now a repeatable, data-driven experience that’s aligned with the long-term Capgemini leadership strategy.

For enterprise learning teams facing similar challenges, the takeaway is clear: When leadership development meets thoughtful design and scalable technology, impact multiplies.

With momentum building and demand accelerating, Capgemini continues to refine and expand the program—proving that with the right model, early leadership development can be both high-impact and high-scale.

Learn more.

Build a scalable leadership program like this one. Let’s talk about how Degreed Academies can support workforce development at scale at your organization.

The post Innovative Leadership: Capgemini’s Approach to Emerging Leaders appeared first on Degreed.

For years, compliance ruled as a top corporate training priority.

Not anymore.

For the first time, upskilling and reskilling are ascendant, according to Fosway Group.

But even with that momentum, there remains a lot of head scratching happening among learning and business leaders over how to make skills work.

What does it mean for organizations trying to build agile, skills-first learning strategies?

“That’s still an ongoing conversation,” says Fiona Leteney, Senior Analyst at Fosway Group.

In the final episode of our three-part podcast series, Leteney and Degreed Co-CEO Max Wessel unpack the shift, explore the 2025 Fosway 9-Grid for Learning Systems research, and discuss how buyers can thoughtfully work with learning tech vendors.

Where Skills Strategy Breaks Down

While enthusiasm for skills is growing, execution remains complex. Organizations are grappling with granularity—”Are we managing 50 skills or 50,000?”—along with data exchange challenges and systems that don’t talk to each other.

Too often, talent and learning data are still siloed—leaving teams without a clear view of employee capabilities or opportunities to reskill for open roles. Forward-thinking business leaders understand that systems need to integrate and scale with minimal friction and quickly deliver measurable outcomes.

Leteney frames it like this: “Interoperability and the integration of systems within an ecosystem is one of the most important things. ”

Interoperability vs. Consolidation

In some cases, employees have to log into three separate platforms just to access one course. That’s inefficient and unsustainable.

The pressure to consolidate tech stacks and cut costs is real. But when decisions are made without input from learning teams, critical capabilities can get lost.

Advice for Learning Leaders

When asked how organizations can rise to the skills challenge, Leteney is clear: “Partner with your vendors… We saw in all the research, often it’s the partnerships where the value is, so that you can be part of the conversation as a buyer, you can influence the roadmap and you can influence the direction of travel—and also give the reality checks to the vendors.

“The devil’s always in the details, and every organization’s different, and it’s finding those vendors that you can actually have that conversation with.”

That kind of collaboration is exactly what Degreed was designed to support.

We power connected ecosystems that make skill development work—from granular data insights to automated and AI-enhanced experiences that adapt in real time.

Whether you’re launching a new strategy or rethinking your entire learning tech stack, Degreed can help you make it seamless—and scalable.

Let’s talk about how Degreed can help you future-proof your learning ecosystem.

The post New Podcast: Is Your Learning Tech Ready for the Skills Era? appeared first on Degreed.

Recent research suggests adoption might not be as deep as the marketing suggests.

“We ended up doing a bit of digging to find out why that was the case,” says Fiona Leteney, Senior Analyst at Fosway Group.

This perspective comes as Leteney reunites with Degreed Co-CEO Max Wessel in a podcast conversation on The AI Dilemma in Learning Systems, exploring the 2025 Fosway 9-Grid for Learning Systems research.

In this second episode of our three-part series—catch up on episode No. 1 here—Leteney and Wessel explore the gap between bold AI hype promises and current delivery, what’s holding companies back from more significant AI adoption, and what forward-thinking learning and business leaders can keep in mind as they shop vendors.

AI Hype vs. AI Help

Leteney spent more than 18 months interviewing vendors and corporate buyers for the Fosway research. While vendors touted AI on roadmaps and in demos, buyers were skeptical. Corporate users in the Fosway network consistently reported underwhelming functionality and lagging adoption.

Why? The hesitation comes from:

• Internal politics
• Security concerns
• Governance barriers
• The unknowns of ROI

In some cases, IT teams are pushing back. In others, people are simply waiting to see who makes the first move.

Where AI is Working

Some promising uses of AI? The ones you almost don’t notice. Like intelligent assistants in authoring tools or agentic features that automate complex reports with a simple prompt.

That “quiet AI” has massive potential—especially in areas learning systems have historically struggled with, like personalization and reporting. If the system can simply do the thing without users realizing it’s AI, adoption will follow.

Leteney calls out analytics use cases as particularly impactful: If AI can answer, for example, “How compliant is this region?” and generate a report—without an admin needing to run significant queries—that’s potentially indispensable.

AI Hype Advice for Learning Leaders

For those wondering how to navigate the AI maze, Leteney offers this: “Go looking…  Learn as much as you can, because this is coming almost as a tsunami, and making the best of this is going to improve your role in your company. And if you don’t, then that’s going to be holding you back. So I think, absolutely, embrace this massively.”

And remember, AI doesn’t have to be flashy to be powerful.

What matters most now is value—not novelty.

Degreed is built for this moment. We believe AI should be embedded in workflows, not layered on top. That’s why we’re building features that deliver real impact, quietly and powerfully—from AI-assisted content curation and skills analysis to personalized learning journeys and automated nudges.

Find out more.

Cut through the AI hype. Let Degreed help you scale what works, with real impact.

The post New Podcast: Is the AI Hype in Learning Tech Justified? appeared first on Degreed.

Now, with budgets tightening and expectations rising, a new question looms: Are those investments really delivering?

“Everybody needed to get a learning system,” says Fiona Leteney, Senior Analyst at Fosway Group. “But the sugar rush is over.”

This insight comes as Leteney joins Degreed Co-CEO Max Wessel in a podcast conversation on The State of Learning Systems in 2025, exploring the 2025 Fosway 9-Grid for Learning Systems research. Their discussion homes in on three things impacting the learning systems market today: The economic climate, artificial intelligence, and skills.

From Urgency to Accountability

Some learning teams bought a solution during the Covid pandemic out of short-term urgency, and perhaps didn’t fully understand the job they were acquiring it to do. “Do you think there’s more maturity now… in terms of that thoughtfulness?” Max asks Leteney.

Leteney’s answer reveals a split landscape:

At Smaller Organizations

Many purchases were made quickly, with minimal due diligence. “You only really get to know a system when you are using it,” she says, highlighting that many teams are now realizing limitations and reassessing.

At Larger Enterprises

The challenge is different. Many already had systems in place, but are now questioning if those systems are truly being used to full advantage—especially in new contexts like global programmatic delivery. For them, upcoming renewal decisions are about maximizing ROI and ensuring tech stacks support evolving business needs.

As renewal discussions surface, CFOs and CIOs are asking hard questions about value. Learning leaders are expected to demonstrate ROI, not just activity. And the bar for impact is high.

Recalibrating for What’s Next

Making change isn’t about regret. It’s about realignment. What worked in a crisis may not work in today’s complex, budget-conscious, and outcome-driven environment.

Degreed is built for this moment.

Degreed empowers you to:

• Pinpoint skills your people need now
• Personalize development at scale using AI and automations
• Integrate with your existing tech stack
• Measure and communicate impact across the business

You’re not stuck with decisions made in urgency. You have the opportunity to evolve your strategy—and your stack—to deliver real value.

Find out more.

Let’s talk about how Degreed can help you scale learning for impact. Schedule a demo today.

The post New Podcast: Is Your Learning Tech Still Worth It? appeared first on Degreed.