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.

That is how Degreed Founder and CEO David Blake set the scene for Vision 2025, our annual, product-focused event. And it’s true. This rapid tech evolution doesn’t just change the way we work and live, it changes the way we learn now and in the future. 

To adjust to the scope of the AI transformation at hand, learning needs to become as adaptive as your people and your technology. It needs to be personalized and relevant to maximize skill-building. It has to be responsive to the needs of your people and your business at scale. That learning and adaptive resilience is going to be critical for the AI era. 

“As we navigate the shift, there are going to be consequences—winners and losers—and we want to make sure that we all end up on the winning side,” Blake said.

What is Adaptive Learning?

Adaptive learning is highly personalized and responsive. It’s customized with learner-specific paths and real-time feedback, making it highly interactive and tailored to individual work.

“[Adaptive learning] is learning that adjusts automatically to the needs of the individual based on their skills, their role, their level of proficiency, and their goals,” says Nicole Helmer, Chief Product Officer at Degreed. “It’s contextual, it’s dynamic, and most importantly, it eliminates waste. So every moment of development is useful.”

Here’s what we’re doing inside Degreed to make that happen:

Automatic Quiz Generation

Skill-building in the age of AI can’t only be about efficiency, it also has to be about effectiveness. It’s no longer just about content completion, it’s about content comprehension.

Are your people really learning and able to apply new skills? Where are the gaps? Now, Degreed Maestro will be able to automatically generate quizzes so learners can test their knowledge. 

With quiz results, admins and leaders can also see summaries of the results to pinpoint, then target, critical skill gaps.

Skill Proficiency Tagging and Role-to-Skill Mapping 

For personalized learning to be effective, it needs to consider skill proficiency, not just what skills are on an employee’s profile. 

That’s why we’ve enabled bulk skill proficiency tagging, which lets users automatically tag a large volume of content with specific skills and proficiency levels. AI will analyze content titles, descriptions, and metadata, then combine it with your company’s skill taxonomy to ensure tagging accuracy.

From there, the new role-to-skill workflow will come into play. It offers a simple, scalable way to define role expectations and suss out skill gaps. It provides a structured, easy way to map skills and target proficiency levels for every role, and then it uses that data to guide employees toward targeted learning.

Model Context Protocol (MCP) 

AI that’s operating without context is about as useful as your favorite maps app without the GPS. In a learning system, it’s the context (e.g., skill data, organizational goals, role details) that will take AI from offering generic information retrieval to providing personalized learning experiences.

Model Context Protocol (MCP) gives AI a consistent, governed way to tap into the right context from Degreed and connected systems wherever those AI models live, whatever platform they’re built on (yes, including other MCP-enabled tools like Gemini and Copilot). Through MCP, AI has access to the skill data, roles, learning history, and guardrails that matter. That way, it can better personalize development and guide your people to what’s next.

Experimental Innovation

In the face of AI, learning will continue to evolve rapidly and the Degreed AI Experiments Lab is already prototyping the development of the future. 

Among these experiments are several multi-step, AI-native learning experiences, including mini coaching moments, AI scoring on learner practice projects, and even smart questions and feedback loops that are woven into learning and aggregate response data.

On top of that, we continue to refine Maestro for real, in-the-flow-of-work learning experiences. We’re also growing Degreed Open Library, our repository of learning pathways on the most in-demand skills in the market. These pathways come at no extra cost to Degreed Learning clients. 

All of this is only the beginning of an era of dynamic and responsive learning that’s personalized like never before. You can lean into these adaptive learning experiences to prepare your workforce for the AI transformation and beyond. 

The post The First Steps to Dynamic, Adaptive Learning at Work 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.

This course isn’t Econ 101 or the History of Western Civ, but it is learning. We’re digging into how corporate learning has changed more in the last decade than in the previous few combined and why the syllabus looks nothing like it used to.

Corporate learning has changed more in this decade than it has in the previous few decades combined. And the pace of change accelerates daily. Even just a few months ago, “personalization” in training meant surface-level recommendations from an algorithm that suggests courses based on your department or job title. Helpful, but often generic.

With AI, personalization has finally caught up to its promise. Modern platforms can understand an employee’s current skills, career goals, and even how they like to learn, then adapt in real time as those needs evolve. It’s not just matching people to content anymore. It’s building truly individualized and adaptive learning journeys that grow with them. 

Class is officially in session; let’s dive into the first lesson.

Lesson 1: AI-Powered personalization is more efficient.

The shift isn’t just theoretical, it’s already transforming businesses. Companies using AI-powered learning platforms report a 57% jump in training efficiency, with employees completing courses faster, retaining more knowledge, and applying it more effectively on the job.

Personalized training speeds up AI transformation and compliance requirements, fosters behavior change, and ramps up leaders in record time. For leaders, this is a game-changer. Learning is no longer a “nice to have.” It’s a direct lever for performance, agility, and retention in the face of AI. 

Lesson 2: The new way to personalize is nothing like the old way.

Here’s how AI redefines personalized learning compared to traditional approaches:

AI is now woven into nearly every business function–78% of companies report using AI somewhere in their operations, according to McKinsey. Training and development shouldn’t be the exception.

Lesson 3: There are a lot of places you can weave AI into learning strategy.

For this lesson, we’ve brought in our learning strategy expert, Stephen Elrod, SVP of Global Delivery. According to Stephen, the question is no longer if you should adopt AI for learning, but how. Here are small, tangible steps you can start with today:

1. Audit your learning stack: Invest in platforms that go beyond content delivery. Look for systems that adapt to individual needs and build capabilities, not just information sharing.
2. Pilot AI-driven pathways: Start with one skill area (e.g., compliance, leadership, or digital skills) and test with a small group.
3. Integrate learning into workflows: Add micro-learning resources where people already work.
4. Raise AI literacy: Run a short workshop to help employees understand AI in learning.
5. Protect trust: Establish a clear data and ethics policy so employees know how their information is being used.
6. Secure executive sponsorship: Share one business case (like improved retention or reduced training costs) with leaders to get buy-in. 

Lesson 4: AI can be the new 24/7 workforce coach.

AI isn’t replacing human learning, it’s enhancing it. It’s giving every employee the equivalent of a personal coach, surfacing opportunities that are timely, relevant, and actionable. And it’s helping organizations scale that level of personalization across the entire workforce.

The takeaway: AI has turned personalized learning from an aspiration into a reality. Companies that embrace it won’t just keep up with change—they’ll lead it.

Homework Assignment for L&D Leaders

What’s a good lesson without a little reflection?

1. Choose one high-priority skill area in your organization (e.g., leadership, compliance, or digital skills).
2. Map how employees are currently trained in this area eg.what tools, content, and methods are used.
3. Identify at least two gaps where personalization could improve outcomes (for example, tailoring by role, adding real-time feedback, or integrating into workflows).
4. Draft a one-page plan for how AI could close those gaps.

Bring this back to your next team meeting and share one idea you could pilot in the next 90 days.

The post Personalized Training 101: Your Guide to Using AI for Learning appeared first on Degreed.

AI has arrived—not as a back-office tool, but as a front-line collaborator reshaping how we work, think, and create. Business cycles are accelerating. Knowledge work is evolving. The biggest question for today’s leaders: Is your workforce ready?

The old playbook—static training, one-size-fits-all programs, disconnected learning—can’t keep pace. To stay ahead, organizations must move beyond content delivery to strategic skill development at scale.

As Siya Raj Purohit, Education Go-To-Market at OpenAI, said at LENS 2025, “When people could start talking to AI, when the interface became language, something fundamental shifted.” Communicating with AI in everyday language makes it accessible to your entire workforce.

This shift has cracked open an entirely new way of learning where people and AI co-create value in real time. The challenge now isn’t just technological, it’s talent-based.

The Shift Has Already Begun

We’re not approaching an AI moment—we’re in it. As language becomes the interface, AI becomes more than a tool. It becomes a partner that enhances human thinking, creativity, and decision-making. “AI isn’t just a tool,” Purohit said. “It’s a thinking partner that can help employees at all levels.”

And it’s already having real-world impact. According to a report by the International Monetary Fund (IMF), 60% of jobs will be reshaped by AI. And by 2030, 50-67% of workers will need reskilling, depending on their location.

And yet, there’s a gap between expectation and readiness. Our 2025 How the Workforce Learns GenAI report shows that 48% of professionals expect their responsibilities to change due to Gen AI, but only 22% feel very confident using it.

The confident few aren’t waiting. They’re automating tasks, generating insights, and making better decisions today.

So, while AI may be disruptive, the real challenge—and opportunity—is human. This is a talent problem, not a technology problem.

From Disruption to Opportunity

Despite the magnitude of AI-driven change, forward-looking organizations aren’t bracing for impact, they’re moving from reaction to transformation.

Purohit outlines four stages of AI transformation:

1. AI Literacy. Build foundational understanding for individual employees by encouraging everyday use. You should see boosts in efficiency, work quality, creativity, and innovation.
2. Custom Workflows. Equip teams with AI that fits their roles and supports team-level problems. Focus on automation, extensibility, and collaboration.
3. AI-Enhanced Operations. Create repeatable processes across the organization to drive productivity. Gain operational efficiency and cost savings.
4. AI-Infused Offerings. Innovate with AI at the core of your business to deliver AI-powered products and services. You’ll enhance your product value and customer engagement.

“Each of these steps builds momentum and maintenance impact,” Purohit said. “And as learning leaders, I think you all are in the best position to lead this transformation.”

The New Learning Playbook: From Literacy to Innovation

“What changed wasn’t just how advanced these models became, but how they could be used… to explore ideas, build skills, unlock creativity,” said Purohit. But to build an AI-ready workforce, you need more than AI tools. You need an AI-powered learning partner. Degreed Maestro helps you move from AI ambition into real outcomes, like everyday AI mastery, personalized learning at scale, learning aligned to business goals, and a workforce built for innovation.

1. AI Literacy from Daily AI-Powered Learning

When your workforce understands how to use AI, it can help them do their jobs better. Building AI fluency starts by embedding AI into daily development. Degreed Maestro makes this easy with:

• Personalized, curated learning pathways adapted to roles and goals.
• AI-powered coaching in the flow of work.

2. Custom AI Workflows Create Adaptive Workforce Learning Experiences at Scale

Once individual employees are using AI every day, Degreed Maestro can equip entire teams with AI tailored to their function and skill needs. That includes:

• Role-plays help sales teams and other functions practice relevant conversations.
• Coaching at scale for all leaders, not just senior leaders.

3. AI-Enhanced Operations Drive Smarter Skill Management

To scale transformation across your entire workforce, you need smarter processes, not just more content. Degreed Maestro turns L&D into a strategic engine for performance, agility, and growth by supporting:

• Skill reviews that replace time-consuming manager evaluations with AI-guided assessments.
• Data-driven insights that connect learning to skill gains and performance outcomes.

4. AI-Infused Offerings Come from Innovating With a Smarter Workforce

AI can support your organization in a multitude of ways, but to fully leverage its benefits, bake it into your products and services. Degreed Maestro can prepare your entire workforce to lead the change by:

• Aligning learning with your business and talent strategies.
• Accelerating readiness for new roles and setups through adaptive learning journeys.

Now’s the Time to Lead

“It’s on us as learning leaders to make sure our workplaces are ready,” Purohit said. “This is not about tools. It’s about building environments where people can grow, experiment, and hopefully do their life’s best work.”

The age of AI demands more than digital transformation. It calls for a workforce learning transformation that puts people at the center and empowers them to adapt, grow, and lead.

Reimagine learning not as a support function, but as a strategic enabler of workforce resilience and innovation. Learn more about how AI is changing learning in How the Workforce Learns Gen AI.

The post AI Makes Workforce Learning Unstoppable appeared first on Degreed.

Voice AI falls short when:

• You need high fidelity for creating or inputting complex information.
• Visual referencing is crucial.
• You need time and space for in-depth problem-solving.
• Tasks involve non-speaking elements, like typing code or navigating a software interface.

This raised a key question for us: Could we harness the best of voice—its interactivity and adaptiveness—and apply it to non-voice contexts?

Our Latest Experiment: Adaptive Learning Exercises

Our answer became an innovative approach to “learn by doing.” The concept is simple: you start with a learning goal, which is then broken down into progressive requirements or milestones.

From there, AI generates micro-tasks, one at a time, to guide your understanding and practice. You receive immediate, personalized feedback after each attempt, and the next task dynamically adjusts based on your progress and comprehension. 

Early Feedback

• “I thought it was intuitive. I liked how it made you do something after each explanation and task description.” 
• “Overall, it was smooth. The feedback it gave me on my responses was helpful.”

Diversifying Modalities 

Hands-on interaction was critical. We began with text input for various tasks, then expanded to support a code editor for more technical applications.

Next, we integrated webcam and screen recordings. The screen recordings, in particular, proved invaluable, allowing early testers to demonstrate their abilities directly within the context of their work or specific applications. 

Early Feedback

• “I like how it had me not only write but record verbally. What I was reinforcing was what I learned. So those are very good.” 
• “It was definitely interactive and engaging.”

Finally, we added multiple-choice questions because constantly requiring text input can feel burdensome; these questions offer a lighter way to confirm understanding.

With this diverse array of modalities, AI can select the most appropriate format for each task and sequence them progressively, effectively managing cognitive load. In practice, this often means starting with multiple-choice questions to confirm foundational understanding, moving to text or code input for hands-on application, and concluding with webcam or screen recordings to demonstrate mastery.

Creating Tailored Instruction

A significant challenge was finding the sweet spot for instructional support: enough to prevent frustration, but not so much that it created noise. Our current solution involves several configuration options:

• Hints – Available on demand
• AI-Powered Q&A – For real-time clarification.
• Instructional Depth – Customizable from none, to basic, to in-depth.

We also include a “rabbit hole” icon on each task, allowing early testers to deep-dive into specific learning resources for additional context or explanation, if and when they need it. 

Navigating the Nuances 

Making the process truly adaptive came with its own set of challenges. If too open-ended, learners lacked clear expectations regarding time or effort. We opted for an initial structure combined with an adaptive path, ensuring progress was always visible.

Measuring progress against requirements was another hurdle, especially when mastery might take several attempts across an undetermined number of tasks. Achieving the “just right” feeling for adaptiveness required extensive iteration. The system needed to ease up when a learner struggled, chunk tasks into manageable sizes, build upon prior knowledge, and align with examples and instructions without removing the challenge entirely.

From Prototype and Beyond: The Journey Continues

This experiment will continue to evolve—thanks to feedback from more than 50 early testers (thank you!). We anticipate that admins and curators will design learning objectives, integrate these adaptive experiences into broader learning pathways, and benefit from robust reporting and insights. Per early feedback, a core component of this will be the ability to upload existing documentation or training materials to automatically generate and customize learning requirements by leveraging your organization’s unique knowledge and an employee’s unique work. 

As one early tester shared, it’s “a great tool. It’s opened my eyes to how companies can adopt it with proprietary knowledge to really help… an online assistant that will help in real time.”

Ultimately, this experiment has proven to be an exceptionally flexible, engaging, and effective learning tool. Its ability to provide immediate, tailored feedback without increasing administrative burden is invaluable. The AI-driven adaptive progression ensures the difficulty always feels “just right,” while optional deeper instruction empowers learners to customize their support. 

Early Feedback

• “For people who want to learn on the job and quickly need to understand something, yep, absolutely valuable.”
  

What’s Next for Adaptive Learning?

The success of this prototype has naturally sparked exciting, new “what if” possibilities for future development, including:

• Adaptive Assessments: Reimagining how we measure skills and knowledge.
• Adaptive Learning Support & Motivation: Moving beyond adapting instruction and tasks, we envision personalizing the way we support and motivate learners throughout their journey.
• Adaptive Workflows: Instead of screen recordings, which carry data sensitivities, can AI generate copy-cat workflows optimized for practice without real-data risks? 

Get Involved

If you’re interested in experiencing this prototype firsthand, you can:

• DM Taylor Blake on LinkedIn
• Sign up for our Experiments Email List
• Follow Degreed on LinkedIn

The post Degreed Experiments: Unlocking Hands-On, Adaptive Learning appeared first on Degreed.

That’s the missed opportunity facing many organizations. But it doesn’t have to be.

“The future of higher education is one of pluralism. It’s one of many actors, many organizations contributing powerfully, dynamically, and compellingly to a world where you as a learner are able to achieve whatever it is that you want to achieve,” said Michele Spires, Assistant Vice President at the American Council on Education (ACE). “It’s about a network of organizations that collectively work together… and you get a new framework for lifelong higher education.”

Lifelong learning resonates at the core of the Degreed mission. And it’s why we’re introducing the Degreed College Accreditation Service, powered by our new partnership with ACE and Credly by Pearson. It means your people’s internal learning can go further—earning college credit, formal credentials, and long-term value.

Workplace Learning That Counts Beyond the Workplace

Let’s be clear: This is more than a new feature. It’s a strategic lever for workforce transformation, designed to help you build, validate, and mobilize skills that matter to your business.

And make no mistake: This isn’t just a benefit for employees. It’s a strategy for organizations that want to attract, grow, and retain top talent in a skills-first world.

With Degreed College Accreditation Service, your learning programs in Degreed Academies can be evaluated for college credit. The Degreed Professional Services team works with you to align content to ACE standards and issue formally recognized, transferable credits via Credly.

Your people get more than just a course completion. They get:

• Credentialed learning programs that support internal mobility and reduce attrition
• Verified, portable credentials that boost talent visibility across and beyond your organization
• Frictionless access to continuing education, with no extra time, testing, or tuition costs

“We need a future where everyone gets recognition for all lifelong learning and skills,” said David Blake, Degreed Co-CEO and Cofounder. “This partnership with ACE represents a significant stepping stone in that journey—enabling workers to gain verifiable, transferable credentials that follow them throughout their careers.”

The Business Case for Recognized Learning

Organizations already invest millions in learning and development—but without formal recognition, those investments often fall short.

Today’s savvy learning leaders seek to provide their people with verifiable credentials to boost employee engagement, strengthen the employee value proposition, and reduce attrition. They aim to transform L&D from a support function into a strategic growth engine, delivering measurable ROI across the talent lifecycle.

Skills That Stick. Credits That Count

When skills are the currency of work, credentials are a key way that currency is verified. Formal recognition gives your workforce the power to advance—whether it’s into a new role, a different industry, or a formal degree.

With ACE and Credly, you gain not only credibility but also measurable proof of performance.

And with Degreed, these credentials don’t exist in isolation. They’re fully integrated into your skill data ecosystem—making it easier to benchmark learning progress, analyze workforce capabilities, and report ROI across the enterprise.

Giving Learning the Recognition It Deserves

Your people put in the work. It’s time that work works harder for them. Let’s discuss how your company can turn internal learning into accredited pathways that drive business results and lifelong impact.

Learn more.

Let’s discuss skill building at your organization. Schedule a personalized, one-on-one call with a Degreed expert today.

The post Say Goodbye to Siloed Learning. Hello, Accredited Skills appeared first on Degreed.

For CLOs and CHROs, this means developing a workforce that understands, embraces, and uses Gen AI with confidence.

What is Gen AI confidence?

When your people use Gen AI with confidence, they’re more than just familiar with Gen AI tools. They’re able to skillfully—and easily—apply, experiment with, and integrate Gen AI into their daily workflows. It’s the difference between hesitating to use Gen AI and using it to drive innovation, efficiency, and better informed decision-making.

New Degreed research shows that 78% of employees lack the confidence and skills to use Gen AI effectively in their daily activities.

This eye-popping number comes from our upcoming How the Workforce Learns Gen AI 2025 report, a global survey we conducted in partnership with Harvard Business Publishing. It finds that people lack confidence because employee learning is insufficiently structured, support for Gen AI learning is limited, and basic learning infrastructure is lacking.

It all adds up to this: While many organizations invest in AI tools, few ensure the workforce is prepared to use those tools comprehensively.

Why Gen AI Confidence Matters

Gen AI confidence makes your organization more successful in three key ways.

1. Gen AI confidence reduces resistance to change.

One of the biggest barriers to Gen AI adoption isn’t the technology itself. It’s humans. Employees who lack confidence in their ability to use Gen AI often resist its integration—due to uncertainty, lack of training, or fear of job displacement. And organizations that actively build Gen AI confidence create an environment in which employees embrace AI as an enabler rather than a disruptor.

Furthermore, our research shows that organizations fostering high levels of AI confidence are nearly three times more successful at embedding Gen AI into daily workflows. Why? Because confident employees experiment more, integrate AI into their decision-making, and use AI tools with greater consistency. When Gen AI becomes a natural part of work rather than an intimidating add-on, adoption moves beyond isolated pilots and fuels operational transformation.

2. Gen AI confidence drives productivity.

Benefitting from Gen AI is about more than knowing how it works. It’s about actively using it to improve workflows and performance. Employees confident in their ability to use Gen AI are twice as likely to incorporate it into their daily tasks compared to those who lack confidence.

This consistent usage leads to greater efficiency, faster decision making, and higher-quality outputs. Our research shows employees are 77 times more likely to engage in Gen AI learning when they see tangible benefits to their work and careers.

Currently, Gen AI and other technologies have the potential to automate work activities that absorb 60% to 70% of employees’ time.

3. Gen AI confidence builds competitive advantage.

The organizations that will lead in the AI era aren’t just those that adopt Gen AI tools. They will be the ones that develop a workforce capable of using Gen AI tools fluently. Companies that prioritize AI upskilling and confidence-building are already pulling ahead, leveraging AI to boost productivity, automate routine work, and drive innovation at scale.

The gap between Gen AI-ready and Gen AI-lagging organizations is widening. Companies that fail to invest in AI fluency will soon face slower decision-making, operational inefficiencies, and difficulty attracting AI-savvy talent. Meanwhile, AI-ready companies are embedding AI into business strategies, accelerating transformation, and staying agile in an unpredictable market.

Gen AI Confidence: Driving Your Competitive Edge

For business leaders, the goal isn’t simply to introduce Gen AI training. It’s to cultivate Gen AI confidence at every level of the workforce. 

• CIOs can help the organization move beyond awareness by embedding Gen AI applications into daily hands-on work.
• CLOs can reengineer learning programs to emphasize experimentation and practical problem-solving with Gen AI.
• CHROs can showcase the real impact of Gen AI, so their people can see the tangible benefits to their work and careers.

Is your organization ready?

Gen AI confidence isn’t a natural byproduct of Gen AI adoption. It results from a deliberate, strategic initiative.

Let’s explore how your organization can build new Gen AI learning strategies—to be more open to change, more productive, and more competitive.

Schedule a personalized, one-on-one call with a Degreed expert today.

The post Build Gen AI Confidence for Workforce Agility & Productivity appeared first on Degreed.

Your product team spends a year developing a new platform. Extensive research reveals a solution that solves vital problems for the market. Your marketing team plans a creative launch campaign complete with strong messaging, email campaigns, digital ads, and social posts. A winning go-to-market strategy emerges, identifying key accounts and clearly defined buyer personas.

When launch day arrives, it’s time to pop the champagne, right?

Not so fast. Is the sales team enabled? Do your reps know less about the product than your prospects?

If you want a successful launch, your sales team needs to understand your product and practice the pitch. The team needs quick responses to key questions about how the product works and what it will do. It needs to articulate value in the context of specific client needs.

And your sales team needs to learn all this in fast and flexible ways that fit a busy schedule.

Customized Coaches for Your Business Needs

While out-of-the box AI coaches are powerful, the customization provided by Degreed Maestro amplifies the impact.

With Maestro, you can tailor AI coaches to reflect your company’s priorities, content, guidelines, brand-voice, and cultural style. This organizational context enables the coaches to converse with relevance, convey the right messages with specificity, and deliver impactful learning. 

This means that, with Maestro, you can scale activities—like personal feedback or sales coaching—previously limited by the rigors of human interaction. The use cases are numerous, but let’s focus on one example: Creating a customized coach that enables a sales team to launch a new product.

Maestro in Action: Creating a Sales Enablement Coach

In our last blog post, Mark used the Degreed Maestro Skill Review Coach while onboarding as a Sales Director—to uncover skill gaps and create a personalized learning Pathway that filled those gaps. 

Now, Mark’s employer turns to Maestro to build a customized coach that will prepare Mark and the rest of the sales team for action.

And let’s face it: Launching a new product is chaotic. Important feedback comes late. Strategies change. Features are shoved in. Messaging gets overhauled. The sales team needs collateral yesterday. 

Now imagine this isn’t just any launch.

The executive team considers this product a key differentiator for the business. Everyone needs to be extra careful about who has what information when.

It’s no secret that this very scenario—a moving-target strategy combined with need-to-know-only restrictions—is a real-life conundrum of enablement. The result has always been high stress and ineffective enablement. But creating a customized coach with Maestro* is so simple and effective that the effort is massively simplified. Forget about coordinating, for example, schedules in order to host an internal webinar series. On the contrary, all the key information the sales team needs can be uploaded into the coach at any time, even the day of the launch.

And because of the personalized nature of Degreed Maestro coaches, employees each get exactly the enablement they need, when they need it. 

Let’s say a Sales Director wants to practice a tailored pitch for a specific client before an important meeting. A coach can quickly provide helpful feedback based on the resources uploaded.

A Regional Vice President wants to understand the product’s ideal customer profile (ICP), to identify target accounts and forecast opportunities. It’s as simple as typing the question and getting an answer.

A member of the sales team needs a quick answer to an FAQ, but the product manager is in back to back meetings all day. Now, they can ask Maestro instead.

No more scrambling to create an enablement program with information that is quickly outdated. No more plans getting ruined by last-minute changes. No more fire drills.

And feel free to tweak the pitch deck right before launch.

Maestro can handle it.

Sales Enablement Coaching from the Sales Perspective

We’ve seen how the enablement team created a customized sales enablement coach, but what about the sales team experience? How was the coach received and used?

Let’s look at how Mark uses the coach to successfully close a deal. 

When the enablement team demo’d the coach, Mark was impressed with its ability to answer questions he would usually have to send to the Product Manager who built the solution. Mark was motivated to try it out. 

Because the coach was embedded into a Pathway about the new product, it’s easy for Mark to access the coach in the flow of learning. 

Mark starts a conversation with the coach to work through key questions he has about the product, and he receives important advice on how to tailor his sales pitch. 

Three days later, Mark runs into a client at a trade show. This person saw a press release about the new product and wants to meet later that day to discuss it. It’s quite loud at the tradeshow, so Mark kicks off a text-based conversation with the customized coach, quickly getting advice on how to tailor his pitch to the needs of that specific client. He’s even able to practice the pitch and receives constructive feedback on some key improvements.

When he meets with the client later that day, Mark applies the advice he got from Maestro, and the client becomes even more intrigued. They schedule a follow-up call with the client’s broader team, which ultimately leads to the first purchase of the product.

The Power of Scaled Personalized Coaching

For Mark, the customized coach proved essential. It provided him with the individualized support he needed to sell the new product. But the customized coach didn’t help just Mark. It helped the entire sales team.

By scaling personalized support according to the company’s  unique new product, its goals, and its needs, Maestro upskilled the entire salesforce and equipped all members with what they needed to help grow the business. 

The launch was a success. Time to pop the champagne!

Find out more.

Schedule a personalized one-on-one call with us today.

*The Degreed Maestro customized coach is currently in development.

The post Degreed Maestro: AI Coaches for New-Product Sales Enablement appeared first on Degreed.

How can L&D professionals give employees enough time to learn at work?

Everyone wants to win. To achieve success, you must demonstrate to executives, employees, and managers that investing more time to learn at work is crucial. They all want to know how learning helps them complete their leg of the race, and that answer is different for all three. Executives need business alignment, employees need growth and managers need clear strategies to develop team members. 

Getting buy-in at all levels can feel as daunting as running a marathon. But if you first reframe how people typically think of time to learn at work, it’ll be an easier sell all around.

For more ways to win learning and influence the C-suite, download our free workbook to secure stakeholder buy-in.

Reframing Time to Learn at Work

How do we carve out more learning time without slowing the pace toward company goals? That is the question L&D professionals get on repeat from executives, managers, and employees. However, the question is problematic because it assumes that learning at work always deters productivity. 

Currently, business leaders and managers often think of learning hours as time dedicated to formal training. But if C-suite and managers (and even employees) only think of learning time as separate from work, they miss out on other critical forms of learning. 

If companies also invest in other kinds of learning like experiential learning and learning in the flow of work, you’ll boost learning without pulling employees away from productivity. And that makes getting buy-in from everyone easier. 

Experiential Learning

When a runner completes a 5k while training for a marathon, they get real-world race experience and earn a medal. Similarly, L&D programs that include experiential learning give employees contextualized learning while producing deliverables for the business. Experiential learning might include:

• Special projects
• Shadowing assignments
• Internal apprenticeships
• Trial periods

“Learning doesn’t always mean that you’re consuming content and taking a full time-out from work hours,” notes Stephanie Lyras, Director of Change Management, Engagement and Adoption at Degreed. The team of experts she belongs to helps organizations align learning to business strategy and measure learning impact. “When we see and can prove learning is an integrated part of delivering business outcomes, we can shift mindsets at the executive level to truly understand the value of learning.”

Learning in the Flow of Work

If experiential learning is like finishing a 5k, learning in the flow of work is like setting up cups of Gatorade along the route. Employees can get the juice they need to keep speeding along on their current tasks. Many employees learn in the flow of work as they run into and resolve on-the-job challenges by themselves, but L&D can invest in these moments to foster learning while boosting productivity.

Learning in the flow of work can look like:

• Googling a tutorial: Many employees do this on their own without L&D intervention.
• Asking a colleague: Foster these conversations by developing a mentoring and coaching program.
• Microlearning at the point of need: Bite-size content that employees can find in seconds and devour in minutes.
• Nudges: Brief reminders (usually push notifications or emails) about how to use knowledge on the job.

Buy-in from Executives

While it’s an important step to reframe learning time in terms of work productivity, for executives, the value of employees having more time to learn at work also comes from driving meaningful business outcomes. If you can walk the C-suite through a clear connection between learning on the job and business objectives, it’s much easier to get them onboard.

Many L&D pros struggle with speaking C-suite, but they also know that aligning learning programs to business goals is critical. It’s their #1 L&D focus area in 2024, according to LinkedIn’s Workplace Learning Report. But you’ll also need a plan for tracking your program’s success.

“If you’re going to have employees spending time to learn, executives need metrics,” says Lyras. “Whether that’s tied to employee engagement, productivity, retention rate, or how quickly a new employee onboards. You need a solid measurement strategy to track regularly so you can respond to the insights.”

The KPIs of Learning on the Job

Employee Retention

According to LinkedIn’s 2024 Workplace Learning Report, companies that prioritize learning see a 27% boost in employee retention. Those with a strong commitment see a 57% boost. 

If learning increases retention by half, then it saves your company money. It saves you money because it costs six times more to replace someone than train them internally. Get a pulse on current employee retention rates, and start doing the math for the future of retention.

Changes in Employee Productivity

While engagement has been a staple L&D metric for years, the C-suite won’t see a clear connection to their bottom line. So translate engagement into a metric they already know and love: productivity. A Gallup study shows that companies with the highest engagement are 17% more productive—and 21% more profitable—than those with low engagement.

Measuring productivity is unique to each role, and could look different depending on how your company tracks work. If you’ve implemented Objectives and Key Results (OKRs) or Scrum story points, you have built-in productivity metrics. Or you can focus on specific deliverables—like completed projects or finished products. Whatever the metric, consider both the quantity and quality of work.

Business Impacts for Specific Roles

Business impact will vary by department. For customer service, it might be a boost in customer satisfaction or fewer escalations. For sales, there might be more deals closed. Find out which metrics executives want to see, and make sure you’re designing learning experiences that drive them.

Buy-in from Employees

Business outcomes get executives on board, but what gets employees learning? Learning that answers the question: “What’s in it for me?” If employees don’t see the value of learning in your organization — or don’t feel supported — you’ll struggle to get them on board like a couch potato struggles to hit the track.

Showing the value of learning time

The top two reasons employees spend more time learning are to progress toward career goals and stay up-to-date in their field. 

Connect Career Paths, Skills, and Learning

Document and share clear career pathing so employees can see exactly what the possibilities are. Then document the skills they need to progress to each level—and the learning activities that will get them there.

Communicate Relevance

Share how you see your company responding to industry advancements like AI and robotics—and how their roles will change as a result. Emphasize the skills employees will need—and that you’re committed to helping them gain them.

Signaling Support

When I train for a race, the support of my friends, family, and trainer keeps me motivated to keep putting in the miles. Similarly, employees need regular reminders that the organization values learning. You can support company learning culture in several ways:

• Nudges: emails and push notifications that remind employees to learn signal that the organization values learning time.
• Microlearning: building easier-to-fit small lessons throughout the day empowers employees to dedicate the time to learn.
• Coaching and mentoring programs: colleagues who dedicate time to an employee’s growth show that coworkers also buy into learning.
• Reflecting and sharing: setting aside time to reflect on training or experiences gives employees the time to solidify their learning.
• Make it part of the conversation: managers who discuss learning in learning in everyday conversations signal leadership buy-in and support.

Buy-in from Managers

Building support at the manager level begins at the C-suite and then trickles down to managers and employees. Executives can praise learning success, hold managers accountable for learning successes, and push for investing in learning technology. And these are all signals to managers that they should climb aboard the learning train.

But you can’t stop at the boardroom. You have to show managers themselves how more learning time will earn them their own medals—AKA, meet their team and department goals and land their bonuses. If you can do that, then you’ve got allies.

Often, your head of people is a great place to start because effective training solves so many HR challenges—like less need to hire talent amid the current skills gap, employee retention and attracting high performers. But you can’t stop at HR, either. You need all managers onboard, and for that you’ll need to switch up your tactics.

Speak Management

When you approach managers about the benefits of providing more learning time, tailor your message. How you do that depends on your company structure, but here’s what managers will want to know:

• Sales: How will more time to learn help employees hit their targets?
• Customer support: How will it boost NPS, customer retention, resolution times, and conversation abandonment rates?
• Marketing: How will it help employees keep up with new trends, channels, and technologies?
• Production: How will it decrease waste, errors, quality issues, and production costs?

The ROI of More Time to Learn at Work

It’s all too easy to get into a stalemate around learning. The old way of thinking pits learning against productivity goals, and it’s the same mindset that views L&D as a cost center, not a value center. But if you reframe learning as complementary to productivity, you’re well on your way to boosting learning time on the job. More importantly, you’re helping your company view L&D as a business-critical initiative—and that’s the key to winning the skills race.

Want to learn more ways to win learning and influence the C-suite? Download, “A Workbook to Secure Stakeholder Buy-In.”

The post Time to Learn at Work: Getting Buy-in is a Company Relay appeared first on Degreed.