How AI Accelerates L&D: A Practical Framework

A practitioner's framework for where AI scales L&D work, where human craft is non-negotiable, and how to know the difference.
PowerPoint | Aptos Type System | Claude | ChatGPT | Brand Palette (#C40303)
Inside the Build
Situation
• Every L&D role I was interviewing for was asking the same question in different words: how do you use AI in your work?
• Candidates generally fell into two camps. Some had a tool stack but no framework. Others had a cautious posture but no real point of view. Senior candidates were expected to bring an AI POV, but very few had one concrete enough to defend.
Task
• Articulate my own POV on AI in L&D, grounded in my actual work rather than borrowed or theoretical.
• Demonstrate visual design skill, now a stated requirement in most senior L&D roles.
• Make it reusable: not a one-off application asset, but something I could anchor cover letters to, reference in interviews, and post publicly as thought leadership.
Action
• Built a 12-slide framework deck walking through three places where AI genuinely accelerates the work (analysis and audience research, drafting and iteration, media production) and three where human craft is non-negotiable (audience trust, judgment on whether training is even the right intervention, deep SME translation).
• Centered the deck on a framework table applying my principle, the do goes to AI and the review stays human, across the full learning lifecycle from analyze through evaluate.
• Designed it end to end in PowerPoint with a consistent brand system: Aptos typography, signature red against a charcoal and neutral palette, and dark section openers for visual rhythm, with no template defaults visible anywhere.
Result
• Stands as evidence of a defensible POV, the design fluency to communicate it, and a framework practical enough to apply on day one.
• Demonstrates how I translate strategic positions into concrete artifacts and maintain brand and visual consistency across long-form deliverables.
• The core principle is the same lens I bring to enablement work in practice: it is how I decide what to delegate to AI and what to keep under human judgment.
