EP 250 - The Hidden Cost of Experiment-Only AI Literacy
Release Date: 11/30/2025
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info_outlineLots of teams are playing with AI. Few are documenting, sharing, or governing what actually happens. In this episode, Susan unpacks the hidden cost of experiment-only AI literacy inside enterprises, from duplicate spend to shadow AI, and offers a path from Wild West to structured innovation.
Episode summary
In this solo episode, Susan looks at what really happens when AI experimentation is encouraged, but never captured or guided.
She explains why leadership often only sees one of two AI universes running inside the same company.
Then she breaks down how to keep curiosity alive and add just enough structure to protect brand, budgets, and people.
Key takeaways
AI is already in your organisation, whether it’s “approved” or not. Even with blanket bans, people de-identify data and reach for personal tools like ChatGPT or Claude on their phones.
You’re probably running two parallel AI universes. One official, “enterprise safe” tool stack that leadership can see. One unofficial, personal stack that actually solves problems.
Experimentation is good culture. “Experiment-only” is expensive. Without reporting, shared learning, or guardrails, you get duplicate tools, compliance risk, brand drift, and fake efficiency.
People are treating AI the way they once treated Google. If they can’t get answers inside the firewall, they go around it. That behaviour is normal… but now the stakes are much higher.
Stop chasing a single super-agent. AI can replace steps, not entire, multi-step, values-based processes that require judgement, politics, and context.
The real leverage is in literacy, not licences. Tools without shared language, playbooks, and training will never compound into competitive advantage.
Episode highlights
[00:02] The conference metaphor: high inspiration, zero notes, nothing sticks.
[01:30] The uncomfortable truth: people are using AI, even if policy says they shouldn’t.
[03:20] Why internal “safe” chatbots often feel generic and miss political and market nuance.
[05:22] How smart staff quietly step outside approved tools and into personal LLMs.
[10:05] The rise of two AI universes: official vs shadow, and where leadership can actually see.
[14:22] Experimentation as a sign of healthy, curious culture. Where it tips into risk.
[16:35] Hidden costs: duplicate spend, overlapping capabilities, and tool sprawl.
[17:28] Shadow AI, compliance risk, and what happens when sensitive data hits public models.
[18:05] Brand voice drift and micro-messaging shifts that compound over time.
[20:21] What leaders can do next: audits, simple guardrails, sandboxes, and shared findings.
[21:19] What a real AI playbook is (hint: documented workflows, not a buzzword PDF).
[22:24] The core question: do you actually know how your people are using AI today?
If you suspect there’s an invisible AI Wild West running inside your organization, start here.
Listen to the full episode and then ask your leadership team one question: “Do we really know how our people are using AI today?”
If the honest answer is “not really”, that’s your starting point for an AI audit and a literacy plan.
Connect with Susan Diaz on LinkedInfor to get a conversation started.
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