Most enterprises don't have an AI problem. They have a literacy problem. In this episode, host Susan Diaz breaks down the "AI literacy divide" inside organizations, why it quietly creates haves and have-nots, and what baseline literacy actually looks like in practice.

AI literacy should be treated the same way we treat financial or health literacy - as a non-optional, minimum standard for everyone, not a niche skill for "AI people".

Susan maps out the current reality in many companies - a small group of confident experimenters, a vocal group of sceptics, and a silent majority stuck in the middle waiting for direction.

Then she paints two futures and shows how intentional, organization-wide AI literacy turns curiosity into real innovation instead of resentment, inequity, and stalled adoption.

 

Key takeaways

You don't have an AI tool problem. You have an AI literacy gap. Most people can "open ChatGPT" but don't understand what LLMs are, what they're good at, and where the risk line is.

Think "financial literacy" not "prompt engineering". Just like everyone is expected to understand interest, debt, and prevention in health, everyone should understand the basics of everyday AI, not build custom agents on weekends.

AI knowledge inside organizations is wildly uneven. A few people experiment confidently. A few are loudly doomsday. Many say nothing, don't feel safe asking questions, and quietly fall behind. That's the divide.

Leadership is often the least literate group. Junior staff may be hands-on with tools, while executives and middle managers are too busy or embarrassed to be beginners again - creating a strange power/knowledge mismatch.

Stop hunting for "one magic AI tool". AI in your company will look more like the internet than a single CRM. It will run through everything, not live on one platform. Literacy and workflows beat silver bullets.

Two things to stop immediately:
Stop treating AI as a binary "for or against" issue. It's already here, like calculators and the internet. The real question is how you'll adopt it.

Stop pretending inequity isn't part of AI adoption. If training only reaches leaders, tech folks, or men who speak up first, you're baking old bias into a new system.

Episode highlights

[00:01 ] "Most enterprises don't actually have an AI problem. They have a literacy problem."

[00:40 ] Financial and health literacy as models for what AI literacy should look like.

[01:39 ] The current reality: pockets of brilliance, pockets of panic, and a big silent middle.

[06:03 ] The Star Wars council metaphor: the Yoda faction, the doomscrolling faction, and the quiet middle.

[10:16 ] The first big red flag: leadership has never sat down to talk about AI as a cultural, strategic, and operational shift.

[12:13 ] Two employees in the same company: the confident AI experimenter vs the quietly left-behind colleague.

[18:21 ] When formal power and AI experience don't live in the same people.

[19:31 ] Why there will never be "one tool to rule them all" inside organisations.

[26:20 ] Company A vs Company B: what baseline AI literacy actually looks like.

[31:16 ] The skills every employee needs: plain-language understanding of LLMs, basic prompting, simple workflow mapping, and evaluation.

[32:13 ] Two things to stop doing now: binary thinking about AI and ignoring inequity in who gets to learn.

If you suspect your organization is quietly suffering scattered pilots, no shared language, lots of vibes but no vision, start here. Ask your leadership team: "What does baseline AI literacy look like for everyone here, and what's our plan to get there?"

Then share this episode with one person in your org who's brave enough to start that conversation.

Connect with Susan Diaz on LinkedIn to get a conversation started.

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