Aug 24, 2026 · 27 min
Organizations buy AI faster than they teach it
Ep 847: How to Train Your Team on AI: The 7 Steps to Educate Your Organization on LLMs (Start Here Series Vol 6)
Without structured education, expensive enterprise AI tools may produce adoption theater instead of better work.
- 1Effective AI education requires leadership involvement, standardized platforms, documented processes, and hands-on practice.
- 2Training should connect large language models to workflow improvement rather than treating tools as isolated experiments.
- 3The organizational shift is from operating AI tools to orchestrating AI-enabled work across repeatable processes.
Don't miss
The episode reframes AI training as a shift from operating individual tools to orchestrating AI-enabled work.
The brief
Jason Wilson opens with a familiar contradiction: organizations invest heavily in enterprise AI and use its language to signal innovation, yet often fail to teach employees how to use large language models effectively.
The proposed answer is a seven-step education framework built around leadership involvement, workflow improvement, platform standardization, documented processes, and hands-on practice.
Tools including Microsoft 365 Copilot, ChatGPT Enterprise, ChatGPT, and Google Gemini appear in a broader question: how should organizations turn access to AI into consistent working methods?
The episode’s central shift is from treating AI as an operator that completes isolated tasks to orchestrating AI-enabled work across repeatable organizational processes.
The takeaway is practical rather than technological: enterprise AI adoption depends on teaching people how to improve workflows, document what works, and practice deliberately.
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