10 L&D Trends to Watch in 2026

When was the last time your employees learned something new without sitting through a formal training session?

Today, learning happens through AI, conversations with managers, on-demand resources, and everyday problem-solving. The boundaries between working and learning are becoming less defined.

So, as learning happens in more places, what is L&D responsible for? Connecting those moments to the capabilities people and the business actually need.

What's changing?

We looked across global research, industry reports, and the wider learning community to find the patterns connecting them.

What we found were 5 broader shifts shaping L&D, from how the function is evolving and workforce expectations are changing to how organizations are rethinking capability, designing learning experiences, and using technology to support learning.

The big takeaway?

The organizations that win in 2026 won't be the ones chasing the newest tool. They'll be the ones asking better questions about managers, about trust, about what AI should and shouldn't be doing in the flow of work. This year's biggest shifts aren't just about what's new. They're about the questions L&D can no longer afford to ignore.

Here's our breakdown of the 10 trends shaping L&D in 2026, and what to actually do about them. For the full playbook, grab the 2026 L&D Trend Report.

1. L&D Strategy: How the Function Itself Is Evolving

L&D is being asked to solve a different problem now. It starts with the people employees rely on every day, their managers, and extends to how a new generation is changing the way people learn, work, and use AI.

Managers Are the Most Important Layer (and Often the Least Developed)

For years, managers were promoted because they were good at their individual jobs, and the assumption was they'd figure out leadership by watching and doing. Manager development, when it happened at all, showed up as an annual workshop.

Why Now?

Managers today are expected to coach, lead change, build capability, and keep people engaged, all while navigating AI, tighter resources, and constant churn. The role has evolved fast, and it shows in what's landing on HR's desk. Gartner has ranked leader and manager development as the top HR priority globally for three years running. Most development programs haven't kept pace.

The Shift

The strain is showing up in how much people trust the person they report to. DDI's Global Leadership Forecast 2025 found trust in mid-level managers dropped from 46% to 29% in just two years. That's not a competence problem, it's a support problem.

Organizations that are getting this right are identifying future managers early and giving them exposure before they're handed the title.

What This Means for L&D

• Make manager development continuous, not annual.

• Build development around real management moments.

• Use peer learning to strengthen everyday leadership capability.

• Develop future managers before they step into the role.

• Equip managers with practical coaching and feedback tools.

Gen Z Has Changed the Rules of Learning (AI Just Sped It Up)

Learning used to be something organizations planned and employees attended. L&D decided the what, the when, and the how, and completion rates became the proxy for a healthy learning culture.

Why Now?

Gen Z doesn't wait for a scheduled course or dig through an LMS for answers. AI is always within reach, patient enough to field every question, and ready the second they need it. They're learning in the moment, and that habit is spreading fast across the rest of the workforce.

The Shift

That instinct to reach for AI first doesn't mean Gen Z blindly trusts what it gets back. Gallup's 2026 research found Gen Z's belief in AI's ability to speed up learning actually fell 7% in a single year. AI is making answers easier to find, but not automatically easier to trust. The teams handling this well are building real AI literacy instead of treating it as another training course, identifying confident Gen Z employees to act as informal AI mentors for the wider workforce, and giving managers simple AI prompts to bring into every 1-on-1.

What This Means for L&D

• Build AI literacy into everyday learning.

• Teach employees to question and validate AI outputs.

• Help employees understand when AI is useful, and when human judgement should take over.

• Use peer learning to build AI confidence.

• Give managers a role in helping teams reflect on how they use AI.

2. Workforce & Work Realities: How Changing Employee Expectations Are Reshaping Development

Employees have more control over how they learn than ever before. But as learning becomes more personal and self-directed, expectations around growth, mobility, and career visibility are changing too.

Learning Has Become Personal (but Growth Is Not Organizational)

Learning used to be tied tightly to work. Managers coached, colleagues shared experience, and the job itself reinforced new skills.

Why now

Learning today is increasingly self-directed, happening through AI, external platforms, certifications, and online communities, often completely outside the organization's line of sight. The volume of learning has grown. How much of it the organization can actually see has shrunk.

The Shift

Personal learning doesn't automatically turn into organizational capability. Unless it gets applied on the job and shared with others, its impact tends to stop with the one person who picked it up. Organizations that are ahead of this are pairing every course or AI learning moment with a real business challenge, creating peer learning circles and team reflection sessions, and turning individual learning into shared knowledge through playbooks and peer showcases.

Frontline Workers Don't Just Need Better Training, They Need Better Futures

Frontline learning used to stop at onboarding, compliance, and standard procedures, delivered in occasional classroom sessions.

Why Now?

Frontline employees are no longer showing up just to clock hours; they're weighing whether the job leads anywhere. LinkedIn's 2025 Workplace Learning Report found career progress is now the number one motivation for employees to learn. That makes growth a business priority for frontline teams, not a nice-to-have benefit tacked onto the job.

The Shift

Organizations have invested heavily in training frontline employees to perform, but not nearly enough in helping them see a future inside the business. When frontline workers can't connect today's learning to tomorrow's opportunity, its value can feel short-term, for both the employee and the organisation.

The response is to map clear career paths, connect learning journeys to actual roles, equip frontline managers to have career conversations, and use practical assessments and simulations to help people prove they're ready for what's next.

What This Means for L&D

• Connect learning to visible career development pathways.

• Map skills to internal mobility and future roles.

• Equip managers for meaningful career conversations.

• Use practical assessments and simulations to validate role readiness.

3. Skills & Capability: How Organizations Are Rethinking the Capabilities They Need to Build

The question is no longer just who needs training. It's which capabilities actually matter, who needs them, and how that answer changes as AI takes over more of the work.

Stop Fixing Low Performers, Grow Everyday Performers

Performance support used to kick in only after someone fell behind, with training or improvement plans used to fix a problem that had already shown up.

Why Now

The old model of waiting for a problem to surface before stepping in isn't landing with either side of the table. Deloitte found only 32% of executives believe their performance management approach supports timely talent decisions, while 64% of workers see reviews as a waste of time. Most organizations are still better at reacting to performance problems than preventing them.

The Shift

The biggest opportunity isn't improving a small group of struggling employees, it's helping the much larger group of consistent, everyday performers get a little better, sooner. That means tracking time to proficiency, skill progression, and performance improvement.

What this means for L&D

• Use skills-based learning to identify capability gaps early.

• Shift from reactive training to continuous performance development.

• Extend development beyond high-potential employees.

• Use targeted learning interventions based on capability needs.

• Measure proficiency and performance.

The Skills Employees Need Are Changing (as AI Changes Work)

Skills used to be relatively stable. Competency frameworks laid out what each role needed, and L&D built those skills through training and experience.

Why Now

The pace of change isn't just picking up; it's touching almost every job description on the org chart. The World Economic Forum estimates 39% of workers' core skills will change by 2030. AI is quietly taking over parts of the job people used to do while introducing entirely new ways of working, and organizations are pouring investment into upskilling and reskilling for AI-enabled roles.

The Shift

As AI takes over parts of the work employees once performed, the question for L&D is no longer just which new skills people need to learn. It is also about understanding how roles themselves are changing and what humans should remain responsible for. The focus is shifting from simply building new skills to designing roles around the capabilities people bring that AI cannot replace.

What this means for L&D

• Run AI impact reviews to understand how roles are changing.

• Retire outdated skills as work evolves.

• Design roles around human strengths such as judgement, problem-solving, creativity and relationship-building.

4. Learning Design & Delivery: How Learning Experiences Must Evolve to Create Real Impact

Learning is getting shorter, faster, and more personalized. But speed creates its own questions. Are people actually building capability, and are personalized experiences helping them see beyond what they already know?

We've Mastered Microlearning (but Forgotten Learning Design)

Learning used to be built as a connected journey, designed for depth, giving employees the time to build understanding, practise skills, and connect ideas across a program.

Why Now

Learning today is increasingly delivered in smaller, faster formats. Microlearning, learning in the flow of work, and AI-powered recommendations have made short-form content the default answer to almost everything.

The Shift

Microlearning has made learning faster and easier to consume, but speed can come at the expense of connection. As programmes are increasingly broken into smaller pieces, the learning experience itself can become fragmented. Employees may complete individual modules without developing the understanding needed to connect ideas, apply them in context, or think more deeply about what they have learned. The shift is from simply making learning smaller to designing learning experiences that help people build understanding over time. 

What this means for L&D

• Check whether each module delivers value on its own or needs to be clearly connected to a larger learning journey.

• Reserve long-form and cohort learning for capabilities that require reflection, judgement and strategic thinking.

• Measure what changes in behaviour, decisions and task performance, not just whether learning was completed.

AI Is Personalizing Learning (but Not Expanding Perspectives)

Learning used to be personalized at the role level. Everyone in the same job followed the same path, at the same pace, and tailored simply meant tailored to a role rather than a person.

Why Now

AI is shifting learning from one-size-fits-all to one-size-fits-one, personalizing recommendations based on someone's role, performance, goals, and behaviour.

The Shift

AI can personalize learning, but it can also quietly narrow it. It recommends based only on what someone has already viewed or completed, creating an echo chamber. That limits exposure to adjacent skills the person didn't even know they needed. Growth begins where familiarity ends, not where the algorithm feels safest.

What this means for L&D

• Combine AI recommendations with performance data, manager input, peer feedback, and business priorities, rather than relying on a standalone AI engine.

• Blend personalized recommendations with adjacent skills, cross-functional knowledge, and future-focused capabilities.

• Build regular manager or mentor conversations into personalized journeys. AI personalizes. People provide the context and judgement.

5. Technology & Systems Enablement: How Technology Is Changing the Way Learning Is Delivered, Discovered, and Experienced

Technology is changing more than how people access learning. It's changing what sits behind it, from the data connecting learning and performance to the AI agents employees are starting to turn to for answers.

Learning Ecosystems Are Growing (but Data Is Still Fragmented)

Learning, people, and performance data used to live in separate systems, and connecting those datasets was hard enough that L&D often measured learning completely separately from business outcomes.

Why Now

Organizations are now investing in connected ecosystems where the LMS, LXP, HR, and performance platforms all exchange data, with the goal of understanding learning's impact on the business, not just delivering it.

The Shift

Connected platforms are only as good as the data flowing between them. Inconsistent skills frameworks, job architecture, and learner data still limit what these systems can do, and that weakens reporting, AI recommendations, and workforce insights. The challenge isn't connecting more tools. It's building a trusted data foundation.

What this means for L&D

• Standardize skills, job architecture, and learner data across existing systems before investing in something new.

• Evaluate how every new platform exchanges data with HR and business systems before purchase.

• Use AI and analytics to surface emerging skill gaps and workforce trends before they become business problems.

AI Agents Are Entering the Workplace (but Organizations Aren't Ready)

Employees used to learn by searching, digging through the LMS, an intranet, manuals, or a knowledge base, completing a course, and returning to work.

Why Now

AI is becoming embedded in everyday work faster than most organizations have figured out how to guide it. Microsoft's 2026 Work Trend Index found only 26% of AI users say their organization has a clear, consistent AI strategy. Employees increasingly turn to AI before they turn to search, asking a question and expecting one trusted answer or next step.

The Shift

Most learning content is still built to be browsed, but employees now expect answers to surface naturally inside a conversation. The gap isn't a content problem. It's a discoverability problem. Knowledge that can't be found or trusted through AI has little value, no matter how good it is. 

What this means for L&D

• Structure content around real employee questions and tasks.

• Make trusted knowledge accessible through AI.

• Govern the knowledge sources AI can access.

• Add content ownership and review processes to the governance point.

A Quick Reality Check from the Rest of the Industry

We didn't stop at our own research. Looking across the wider L&D conversation for 2026, from LinkedIn's Workplace Learning Report to Gartner, Deloitte, the World Economic Forum and independent industry surveys, the same threads keep showing up.

Across these sources, there is growing attention on how organisations build capabilities, support managers, connect learning to business priorities and respond to changing workforce needs. While the language and priorities vary, the direction is consistent: L&D is being asked to move beyond delivering programmes and play a more strategic role in organisational performance.

Social learning and stronger connections between employees are getting renewed attention in 2026, echoing what we're seeing around managers and peer learning.

Proving the impact of training is becoming harder to ignore. As L&D teams face greater pressure to connect learning with business outcomes, having a clear approach to training evaluation is essential. Our training evaluation guide explores how to measure what really matters. And there's a growing idea in the industry being called "learning debt": the capability gaps that build up when development can't keep pace with changing work. It isn't exactly the same as our microlearning trend, but both point to a similar risk: when speed becomes the priority, deeper capability can get left behind. 

Final Takeaway: Staying Ahead in 2026

Every year, L&D gets handed a new buzzword. Microlearning, personalization, AI. It’s easy to chase whatever’s new. But the real question isn’t what’s next. It’s what’s overdue.

Across these 10 trends, several priorities stand out: developing stronger managers, creating clearer career pathways, rethinking the capabilities people need as AI changes work, designing learning with greater intent, connecting data across the learning ecosystem, and building capabilities that support business needs.

These priorities form the foundation for a more effective approach to learning and development. Addressing them now can help organisations build the structure and capability needed to respond to future changes with greater confidence.

Want the full breakdown with tools and frameworks for each trend? Check out our latest 2026 L&D Trend Report.