• Why skill acquisition, not job training, should be the benchmark for modern learning.
• The dangers of “accidental instructional design” and how to avoid it.
• How small evidence-based tweaks can dramatically improve learning outcomes.
• The role of retrieval practice, mental models, and worked examples in skill mastery.
• Why spacing, interleaving, and desirable difficulty are critical to effective learning.
• How to balance tools, job aids, and training for lasting performance.
• The opportunities and risks of generative AI in L&D.
• Clark’s call for evidence-based practice to be the standard, not the exception.

Podcast Takeaways

• Clearly define why you’re implementing AI and what business or performance goals it should support.
• Many L&D platforms and tools already include AI features; maximize those before investing in new tech.
•  Tie AI initiatives to organizational priorities, not just L&D metrics.
• Ensure AI tools meet data security and compliance standards while allowing room for experimentation.
• Select solutions that solve major pain points and deliver measurable results.
• Educate L&D teams and stakeholders on AI basics to reduce fear and resistance.
• Explore AI agents and copilots that give learners instant answers without leaving their workflow.
• Track AI’s impact with relevant, pre-defined business metrics, not just output volume.

Podcast Takeaways: 

• AI adoption must balance innovation with security and compliance.
  
  
• Hallucinations highlight the need for human review. 
  
  
• AI is powerful, but not infallible.
  
  
• AI councils provide structure for testing, approving, and scaling tools.
  
  
• Start with clear requirements when evaluating AI solutions, not just features.
  
  
• Short-term pilots reduce risk while proving business value.
  
  
• Microsoft Copilot and Synthesia are transforming workflows, saving time, and streamlining stakeholder collaboration.
  
  
• AI efficiency creates capacity for creativity, experimentation, and higher-value work.
  
  
• The future of L&D leaders lies in curiosity and exploration, asking “How can AI help me today?”