Something I keep coming back to after reading OpenAI's new policy paper yesterday. Sam Altman is proposing robot taxes, a public wealth fund, and AI access as a fundamental right. But the entire 13 page document barely mentions education. No section on AI literacy. No plan for who delivers the retraining.
Here's my question for you: If AI fluency becomes essential for participating in the economy, where should that education start? Schools? Employers? Community organizations? Self directed learning?
Drop your take below. There's no wrong answer here, just a conversation that needs to happen.
Good question. I believe it starts with educating the educators whether they be teachers (at all levels) or trainers in organizations/companies. Right now it seems like a free-for-all ... some folks are way ahead in adopting AI, others are barely accepting it's here and everyone else is somewhere in between. That brings up the next question: who should train the trainers? Despite organizations knowing AI fluency is essential, there seems to be very little to no formal training. Perhaps that's because everyone is still trying to figure out what AI fluency looks like in their professions. Of course there's the costs as well. Are organizations willing to invest in training? What metrics should be used to justify the investment? Thoughts?
You just named the exact bottleneck, Gretchen. The "who trains the trainers" problem is the reason most organizations stall on AI adoption even after they commit budget to it. They buy the tools, announce the initiative, and then realize nobody internally has enough fluency to actually teach the rest of the team.
Your point about the free-for-all is spot on. Right now the people furthest ahead are mostly self-taught, which means the gap between early adopters and everyone else keeps widening. Formal training programs are lagging because the technology moves faster than curriculum development cycles. By the time a training program gets approved, piloted, and rolled out, the tools have already changed.
On your metrics question: I think the most honest metric is not "did they complete the training" but "did their workflow actually change?" If someone finishes a course and goes right back to doing everything manually, the training failed regardless of what the completion certificate says. DataCamp's 2026 report found that organizations with structured AI upskilling programs are nearly twice as likely to report measurable ROI. The difference was not the content. It was whether the training connected to daily practice.
That is exactly the gap the SeedStacking approach was designed to close. Not a course you finish and forget. A daily habit that compounds. What does AI fluency training look like in your field right now? I am curious whether you are seeing any structured programs or if it is still mostly learn-on-your-own.