Your CEO just asked what your L&D strategy looks like for next year. You pull up the deck you built last quarter. It’s already outdated.
That’s the reality of learning and development right now. The ground shifts faster than most teams can plan for. Two years ago, everyone was talking about microlearning and remote training. Last year, AI dominated every conference panel. This year, the conversation has matured into something more interesting: what actually works when you put all these pieces together?
If you’re still getting grounded on the fundamentals, start with our guide on what training and development actually means before diving into trends. For everyone else, we’ve been tracking these shifts through conversations with practitioners on the RiseUp Radio podcast, through patterns we see across organizations using Risely, and through the research that keeps landing in our inboxes. Here are the learning and development trends that matter most in 2026.
Where did we come from? A quick look back
Before jumping into what’s next, it helps to see how fast the ground has shifted.
In 2024, L&D teams were still recovering from budget cuts and headcount reductions. Many operated in survival mode. AI was the shiny new thing, but most teams used it for basic content generation (write me a quiz, summarize this module) rather than anything strategic.
By 2025, the mood shifted to what Kelli Dragovich described in our podcast conversation as “cautious optimism”:
“I just feel like the soil is loosening up a bit, even though this growth isn’t out there yet. It’s underground and I feel good about that.”
That optimism was earned. Teams that survived the cuts came out leaner and more focused. They stopped trying to do everything and started asking better questions about what learning actually needed to accomplish.
Now in 2026, those questions are producing real answers.
1. AI coaching is replacing generic manager training
The biggest shift we’re seeing isn’t about AI creating content. It’s about AI becoming the coach that most managers never had access to.
Think about the traditional approach: a two-day workshop, maybe some follow-up e-learning modules, and then nothing. The manager goes back to their desk and faces a situation the workshop never covered. The gap between “knowing” and “doing” stays wide open.
AI coaching closes that gap by meeting managers in the moment. When a manager’s team feels overworked, they don’t need a module on delegation. They need help diagnosing whether the issue is expectations, skills, or headcount, and they need that help right now.
This is exactly what we built Risely’s AI coach Merlin to do. It starts with a blank slate, no assumptions about what the manager’s problem is. Through conversation, it helps them figure out what’s actually going on and what to do about it. The result is learning that’s tied to real situations, not hypothetical case studies.
Coaching observation: We’ve noticed that managers who engage with AI coaching regularly don’t just solve the immediate problem. They start recognizing patterns in their own behavior. One manager told us she realized she was avoiding difficult feedback conversations not because she didn’t know how, but because she was afraid of the emotional response. No workshop would have surfaced that.
2. Personalization went from buzzword to baseline
Personalized learning has been on trend lists for a decade. The difference now is that the technology finally caught up to the promise.
In 2024, “personalized” often meant letting people choose from a catalog. Pick your own adventure, but all the adventures lead to the same place. An Emeritus study found that 63% of professionals wanted personalized development opportunities, but most felt they weren’t getting them.
In 2026, personalization means the learning itself adapts. The content, the pace, the format, even the coaching approach shifts based on what the individual actually needs. This isn’t about learning preferences (visual vs. auditory, a framework that’s mostly been debunked anyway). It’s about context: what role you’re in, what challenge you’re facing, what skills you’ve already built.
For L&D teams, this trend demands a shift in thinking. You’re not building courses anymore. You’re building systems that can respond to individual situations at scale.
3. Skills-based strategies are finally getting practical
“Skills-based organization” was the phrase that launched a thousand conference talks. But for most of 2024 and 2025, it remained theoretical. Teams talked about skills taxonomies and competency frameworks without a clear path from framework to action.
That’s changing. The practical applications are emerging:
| What changed | Old approach | 2026 approach |
|---|---|---|
| Identifying gaps | Annual performance reviews | Continuous assessment with real-time data |
| Matching people to work | Job titles and org charts | Skills inventories and internal mobility |
| Measuring development | Course completion rates | Demonstrated skill improvement over time |
| Planning training | Catalog-based, one-size-fits-all | Targeted interventions based on actual gaps |
The shift matters because it connects L&D directly to business outcomes. When you can show that a specific skill improvement led to better team performance, you’re not fighting for budget anymore. You’re being asked to scale.
Dr. Steven Hunt, author of Talent Tectonics, pointed out in our podcast conversation that technology now allows us to spot potential that was previously invisible. Skills-based strategies aren’t just about filling gaps. They’re about finding strengths that traditional systems overlooked.
4. The L&D professional’s job description looks nothing like it did three years ago
If you’re an L&D professional reading this, your job has probably changed more in the last two years than in the previous ten.
The LinkedIn Workplace Learning Report flagged this shift early: analytical ability, data fluency, and “human skills” are now core requirements for L&D roles. You’re expected to be part data analyst, part experience designer, part internal consultant.
As Denise Fekete, a talent development and AI tools consultant, put it: “We’re teaching other people how to learn, so we should also be open to learning ourselves in this exponentially shifting area of L&D.”
The new skill stack for L&D professionals looks something like this:
- Data literacy: Reading engagement metrics, correlating learning activities with performance outcomes, building a case with numbers
- AI fluency: Knowing what AI tools can and can’t do, evaluating vendors critically, designing AI-augmented learning experiences
- Experience design: Borrowed from product development, this means thinking about the learner’s journey the way a UX designer thinks about a user’s journey
- Business acumen: Speaking the language of ROI, retention, and productivity (not just “learning outcomes”)
- Stakeholder management: Selling programs internally, managing expectations, building coalitions
This isn’t about replacing what L&D professionals already do. It’s about adding layers that make the work more impactful and harder to cut when budgets get tight.
5. Human skills are the real growth area (yes, still)
Every year, someone predicts that “soft skills” will finally get the attention they deserve. And every year, they’re right, but the execution lags behind.
What’s different in 2026 is the framing. We’ve moved past the awkward “soft skills” label (at Risely, we call them people skills because that’s what they are). More importantly, organizations are recognizing that these skills aren’t a nice-to-have supplement to technical training. They’re the foundation that makes everything else work.
A manager who can’t give honest feedback won’t benefit from a project management certification. A team lead who avoids conflict will undermine any collaboration tool you deploy. An individual contributor who can’t communicate clearly will bottleneck every project they touch.
Coaching observation: The pattern we see repeatedly is that technical skills plateau while people skills compound. A manager who gets 10% better at active listening this quarter will be measurably better at conflict resolution next quarter, because the skills build on each other. That compounding effect is what makes investing in people skills so powerful for long-term team performance.
6. Learning is leaving the classroom (physical and virtual)
Inna Horvath gave us a reality check in a podcast conversation about AI and content creation:
“When it comes to content, it’s not enough to just type in ‘I need a course on talent management’ and you would have 10 pages of text, maybe a quiz with multiple choices if you are lucky. But that’s not enough. We all know that.”
She’s right. And the solution isn’t better courses. It’s rethinking where and how learning happens.
The most effective learning in 2026 is embedded in work itself. It happens in a coaching conversation after a tough meeting, in a quick reflection prompted by an AI coach, in a peer discussion about how a project went sideways. Paul Matthews, founder of People Alchemy, put it bluntly on our podcast:
“We’re right at the beginning of stumbling around in the dark.”
He meant it optimistically. The old model of classroom-to-screen translation was a dead end. What’s emerging is learning that’s woven into the daily rhythm of work. Some practitioners are taking this to creative extremes, like the equine-facilitated leadership program run by Janis Cooper at Best Friends Animal Society, where managers learn trust-building by working with horses. You don’t forget a lesson that involved a 1,200-pound animal.
7. Inside gigs and internal mobility are reshaping development
One of the most interesting learning and development trends isn’t about formal training at all. It’s about creating opportunities for people to learn by doing different work within the same organization.
Dr. Edie Goldberg has documented this approach at companies like HERE Technologies and TATA Communications. The concept is straightforward: instead of confining employees to rigid job descriptions, let them pick up projects across teams that match their skills and interests.
For managers, this requires a mindset shift from “my employee” to something more open. You’re not losing a team member when they contribute to another project. You’re building someone who brings back broader skills, fresh perspectives, and stronger cross-functional relationships.
For L&D teams, inside gigs create a natural partnership with HR. You maintain the skills inventory, design the development pathways, and measure the outcomes. The learning happens through the work itself, which solves the transfer problem that plagues traditional training.
8. Measurement is moving from vanity metrics to real impact
“We trained 500 people last quarter” tells you nothing about whether anyone got better at their job. L&D teams know this. The rest of the organization is starting to catch up.
The measurement shift looks like this:
- From completion rates to behavior change
- From satisfaction surveys to performance correlation
- From hours of training delivered to skills demonstrated on the job
- From annual reports to continuous dashboards
This trend connects directly to the skills-based strategies discussed earlier. When you can measure specific skill improvements over time, you can tie learning investments to business outcomes. That changes the conversation with leadership from “this is what we spent” to “this is what we produced.”
Data-driven learning isn’t new as a concept. What’s new is that the tools to do it well are finally accessible to mid-sized L&D teams, not just enterprises with dedicated analytics functions.
What this means for your team right now
If you’re building your L&D strategy for the rest of 2026, here’s where to focus:
- Audit your current approach. Where are you still running programs because you always have? Which ones actually produce skill improvement you can measure?
- Start small with AI. You don’t need to overhaul everything. Pick one use case (coaching for new managers, personalized skill development, assessment-driven learning paths) and pilot it.
- Build your own skills. The L&D professionals who thrive in this environment are the ones who treat their own development as seriously as they treat their programs. Get comfortable with data. Learn how AI tools work. Practice making the business case.
- Connect learning to work. Every program you run should have a clear line from “what we’re teaching” to “where they’ll use it tomorrow.” If you can’t draw that line, rethink the program.
- Invest in people skills. They compound. They transfer. And they’re the hardest thing for AI to replace.
The learning and development trends of 2026 all point in one direction: away from generic, content-heavy programs and toward personalized, embedded, measurable development that actually changes how people work. The teams that move fastest in this direction won’t just have better training. They’ll have better managers, stronger teams, and results they can prove.
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