"When leaders ask me how to approach AI training, they're usually thinking about the technical stuff: prompt engineering, data security protocols, and which tools to use when. And yes, those matter. But if that's where your AI training stops, you're setting your team up to use a Ferrari like a golf cart. The real question isn't "How do we write better prompts?" It's "How do we fundamentally shift how our people work?""
"Most people use AI like an extremely fast research assistant. They ask it questions, get answers, and maybe copy-paste some results. This practice is like hiring a talented analyst and only asking them to file papers. Effective AI delegation means handing off substantive work with clear outcomes in mind. It requires a shift in mindset to "Here's the problem I'm trying to solve, here's the context you need, now help me think through solutions," rather than"
Organizations often focus AI training on technical topics like prompt engineering and data security, but those alone won't shift how people work. Teams will learn technical tool use through practice, yet four human-centered skills determine whether AI scales productivity: delegation (assigning outcomes and context rather than transactional queries), curiosity (iterating to turn AI into a thinking partner), contextual intelligence (making implicit knowledge explicit for better prompts and results), and discernment (critical evaluation of AI outputs). Building these skills requires changes in mindset, workflows, and managerial expectations to move from fast search to outcome-oriented collaboration.
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