AI is changing more than how L&D creates content.
It is changing the work itself.
Tasks are being automated. Expertise is becoming easier to access. Employees are working alongside increasingly capable systems. And some of the knowledge we once expected people to carry with them can now sit inside workflows, tools, and AI.
That raises a bigger question for Learning & Development:
How do we help organizations build capability fast enough to keep up with the work?
I recently reviewed enterprise AI strategy and research from MIT, Stanford, and Google and adapted the strongest ideas for an L&D audience.
The resulting report, Rewiring Learning & Development for the AI Era, explores what this shift means in practice, including:
- why L&D should move from courses to capability
- why tasks and workflows are becoming more useful than job descriptions
- where capability should live: in the person, the workflow, AI, or the team
- why expertise may become more valuable, not less
- how to use AI speed for experimentation rather than simply faster production
- the role of the Minimum Effective Intervention
- how to measure the human + AI + workflow system
- how the instructional designer begins to evolve into a capability designer
- a practical maturity model for L&D in the AI era
The core argument is simple:
AI should not just help L&D create faster. It should help organizations learn, adapt, and build capability faster.
If that question is relevant to the work you are doing, you can download the full report below.
