Designing learning for the AI world
Every year at Learning and Development (L&D) we discuss the future of learning. But here’s an inconvenient truth. 2026 is no longer an expectation. It’s about results. AI is no longer a pilot experiment or a slide embedded in a strategy deck. It’s already built into our inboxes, workflows, meetings, and decision-making. In some cases, output is generated so quickly and confidently that you stop and think, “That was faster than I expected.” So the real question in learning and development this year is not whether we should use AI or not. The question is: Are we designing learning that helps humans think better in a world where AI never sleeps?
The person in the room who can learn the fastest
Let’s be clear. AI has the fastest learning capabilities any organization has ever had. No onboarding required. Your content will be remembered even after the session ends. Don’t lose focus in the middle of the program. Just checking the box does not mean you will participate in the training. This means that learning and development has lost its long-standing monopoly on information. That’s not a bad thing.
Research on adult learning consistently shows that adults do not learn best by consuming more content. They learn by reflecting on experiences, understanding situations, applying judgment, and solving real and pressing problems. Information alone rarely changes behavior.
AI can generate answers in seconds. Humans still create meaning. This difference will become decisive in 2026.
What you see repeatedly on the ground
Across roles, industries, and experience levels, one pattern emerges repeatedly. Few people struggle because they don’t have enough knowledge. They struggle with knowing what to prioritize, how to make decisions under pressure, how to navigate uncertainty, and when to believe or doubt information.
Now it’s time to introduce AI into that environment. Learners no longer just ask, “What should I do?” They’re asking, “This is what the system says, but does it make sense? What happens if it’s wrong? Who has the final say?”
These are not technical questions. They are questions of judgment. This is not a technology gap. It’s a learning design gap.
Why learning design will need to change in 2026
Some traditional learning approaches are still rooted in previous realities. A long program designed far from the workplace. A one-size-fits-all competency model meant to fit everyone. One-size-fits-all learning measured by attendance and completion.
In an AI-enabled workplace, learning must also evolve. We need to move from content-heavy to context-heavy. From event-based to integrated into daily operations. From emphasizing knowledge to emphasizing judgment.
Cognitive science supports this change. Learning transfers when it is relevant, contextual, and immediately applicable. AI brings speed, scale, and access. Learning and development must bring about interpretation, reflection, and meaning-making.
Soft skills are no longer soft
For many years, these abilities were politely referred to as soft skills. In 2026, they will never be. Critical thinking, ethical decision making, self-awareness, collaboration, accountability: these are now risk management skills. When AI influences decision-making, bad decisions will spread faster and become more visible. Small errors can quickly ripple through systems, customers, and teams. Learning is no longer just about growth and potential. It is also important to avoid costly mistakes that can occur while driving at high speeds.
What kind of learning design will be useful in 2026?
Based on what works today, effective learning design in 2026 will likely look like this:
Short and situation-based. It’s integrated into your daily workflow. It’s built around real-life decisions people face. It is designed to make you question AI rather than blindly accepting it. We help you learn from your mistakes instead of hiding them.
Most importantly, it respects simple truths that adult learners already intuitively understand. Learning should make work easier, not harder.
Questions worth asking
Before you finalize your next study calendar, there is one question worth pondering over. If AI can already do this faster, what capabilities are humans actually building? If your learning endeavor doesn’t strengthen your judgment, confidence, ethics, collaboration, or adaptability, it may not be right for you in 2026.
Looking to the future
In 2026, we will no longer be choosing between humans and AI. It is about designing learning that keeps people firmly in charge. Successful organizations are not those that have the most advanced tools. These are the people who know when to trust AI, when to challenge AI, and when to lead beyond AI.
For learning and development, this moment does not threaten relevance. It is an invitation to redefine. This is learning that helps humans think clearly, decide wisely, and lead responsibly in an AI-driven world.
References and further information: Knowles, MS, EF Holton, and RA Swanson. 1973. Adult learners: A neglected species. Houston: Gulf Publishing.
[A foundational work on how adults learn through experience, reflection, and relevance.]
D. A. Kolb, 1984. Experiential learning: Experience as a source of learning and development. Englewood Cliffs, NJ: Prentice Hall.
[Explains why learning rooted in real experience leads to deeper understanding and behavior change.]
OECD. The future of artificial intelligence and skills
[Highlights the growing importance of human judgment, ethics, and critical thinking in AI-enabled workplaces.]
Salas, E., S. I. Tannenbaum, K. Kraiger, and K. A. Smith-Jentsch. 2012. “The Science of Training and Development in Organizations: What Matters in Practice.” Psychological Science in the Public Interest 13: 74-101. https://doi.org/10.1177/1529100612436661
[Evidence based insights on what actually drives learning transfer at work.]
