We thought 2025 would be the year AI became the norm at work. In reality, it was the year organizations realized how unprepared they are. While AI capabilities have advanced at breakneck speed, most teams are still stuck in early experimentation—testing tools, debating guardrails, and struggling to move from promise to practice.
That gap matters. AI is reshaping how work gets done faster than organizations are reshaping how people build skills, apply judgment, and stay ready. Over the next two years, this mismatch—not the technology itself—will determine which organizations pull ahead and which fall behind.
The organizations that will win won’t be the ones who simply “add AI.” They’ll be the ones who prepare their people, leaders, and learning ecosystem to use AI strategically, responsibly, and at scale.
Here are four AI-in-L&D trends you should prepare for in 2026, backed by the best available research and what we’re seeing in the market.
Trend #1: AI Adoption Is Rising, But Bottlenecked By Readiness
Many teams are already dabbling in AI, but few are truly ready to operationalize it.
In one 2026 enterprise L&D survey, 61% of organizations said they’ve fully or partially adopted AI into their L&D programs or are testing it, but adoption is uneven and hindered by gaps in AI literacy, unclear implementation plans, and weak infrastructure.
This is consistent with what L&D practitioners reported in broader sentiment research: AI use is still largely early-stage and concentrated in content creation and efficiency work rather than deeper learning transformation.
What to do now:
1. Run an AI readiness assessment for L&D (not the enterprise).
Readiness is comprehensive. It includes skills, governance, culture, and platform capability.
2. Define a “minimum viable AI policy” for learning teams.
Start with what data can be used, where it can be used, and what cannot be automated. Connect with your Legal and/or Security teams to define this policy.
3. Focus on 2–3 high-confidence use cases for 2026.
Don’t try to boil the ocean. Start small, gain confidence, then scale applications more broadly.
Trend #2: AI Can Only Accelerate Personalization With The Right Foundations
AI-driven personalization is finally becoming practical at scale, and it’s shaping what employees expect from learning.
Across 2026 L&D research, top AI uses and planned uses include:
- Tailoring content recommendations
- Automating content creation
- Identifying skill gaps proactively
- Creating adaptive learning paths
But here’s the truth: personalization is only as strong as the underlying system. If you don’t have consistent job architecture, skills language, role definitions, and content metadata, AI recommendations become noise.
What to do now:
1. Treat personalization as a data problem before it becomes a tech problem.
Tighten up your content tagging, role alignment, and skills frameworks.
2. Start with role-based personalization, not “everything for everyone.”
Identify your 5–10 most critical roles and build pathways that respond to real performance needs.
3. Design personalization as guidance, not automation.
Personalization should help learners choose better, not remove choice. Consider allowing learners to continue browsing your catalog, in addition to surfacing personalized content recommendations.
Trend #3: The Human Side of L&D Becomes More Valuable
There’s a myth floating around that AI will reduce the importance of human development.
The research says the opposite.
Leadership training and development remains the #1 priority going into 2026, with 61% of respondents expecting it to be their primary focus.
And the most in-demand capabilities organizations predict they’ll need by 2026 are overwhelmingly human: strategic/critical thinking, digital fluency, and leadership.
LinkedIn’s Workplace Learning research shows that organizations that invest deeply in career development and leadership readiness are also better positioned for AI transformation. In fact, career development champions are more likely to be at the “accelerating” or “leading” stages of generative AI adoption compared to others.
What to do now:
1. Double down on leadership development, but modernize it.
AI can help leaders, but leaders must still coach, guide, and build confidence through change. (Check out recommendations for leadership development in the age of AI, featuring insights from Duke Corporate Education’s Divya Shah, in this blog.)
2. Make “critical thinking with AI” a core learning outcome.
The goal isn’t to teach employees how to use AI, but how to use AI well. The key will be using it without outsourcing judgment. (This TED Talk on not letting AI kill your critical thinking would be a great addition to your AI training.)
3. Reinforce human learning loops: feedback, reflection, practice, coaching.
AI can scale support, but it cannot replace human accountability and context. Double down on the human elements of learning to see the best results.
Trend #4: Career Mobility and Skills Strategy Will Become the New “Proof” of L&D Value
As AI accelerates change, organizations will increasingly judge L&D by whether it drives:
- Internal mobility
- Skill movement
- Workforce adaptability
LinkedIn’s research makes this connection explicit: learning combined with career development accelerates the flow of critical skills to match business needs. Only 36% of organizations qualify as career development champions, and they outperform others across multiple business indicators, including confidence in profitability and talent attraction/retention.
When organizations can’t yet measure AI’s full ROI in performance terms, they will measure what they can see: career progress, skills movement, and retention.
What to do now:
1. Build learning paths that explicitly connect to roles and mobility.
Employees’ No. 1 motivation to learn is career progress. Make sure to design with this goal in mind.
2. Choose 3–5 mobility metrics that matter in 2026.
Not sure which to pick? Internal fill rates, skills acquisition, promotions, and engagement are good starts.
3. Integrate learning, talent, and workforce planning conversations.
Skills strategy isn’t an L&D initiative; it’s an enterprise capability. L&D should be at the center of it. This is how L&D gets its seat at the table—by creating a smart strategy for employee training and development tied to the future of work.
It’s Time to Prepare for an AI-Powered Organization
AI is a tool that’s transforming how work gets done, how decisions are made, and what people are expected to know on day one. That shift is already underway, whether organizations feel ready for it or not.
In 2026, the real differentiator won’t be which AI capabilities you turn on. It will be whether your learning strategy is equipped to support a workforce that needs to build skills faster, apply judgment in new ways, and move more fluidly as roles continue to change.
That means moving beyond learning as content delivery or program management, and toward learning as a system that helps people build capability over time.
The organizations that take that approach now won’t have all the answers yet. But they’ll be far better positioned to make AI useful as it becomes more deeply embedded in everyday work.
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