EP281 Your Team's Nervous System Is Infrastructure - Sira Laurel on Load-Bearing Trust
AI Literacy for Entrepreneurs
Most of the leaders Sira Laurel works with look like they're winning. Inside, they're exhausted. Sira is an executive coach and facilitator who works on leadership, organizational design, cognitive load, trust and nervous system capacity. She has watched organizations get very good at making work faster while getting worse at deciding what the speed is for. AI raises the stakes on that question. Her starting point is that capacity covers far more than time. It includes attention, decision-making, emotional bandwidth and creative energy. A tool can hand back hours on the calendar while draining...
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EP280 Faster Than a Generation - Ian Alden Russell on Change That Outruns Us
AI Literacy for Entrepreneurs
This episode skips the tools, the prompts, and the latest model release. It goes somewhere more philosophical. started out as an archaeologist and anthropologist. He was the kid who loved museums and Indiana Jones. Since then he has worked across history, contemporary art and culture in Dublin, Istanbul, Beijing, Hong Kong, Pittsburgh and Doha. Now he works as a strategist helping organizations make sense of complexity and line up around change. His starting point is that change itself is old news. Humanity has absorbed huge technological shifts again and again. The new part is the speed....
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EP279 How higher ed moves from AI interest to governed use with James Hutson
AI Literacy for Entrepreneurs
A previous president from Lindenwood University (a former IBM executive) stands up in town halls and tells people he uses Claude - that it helped him organize the financial report. HR follows and says they used Gemini for an employee questionnaire. Then James Hutson PhD. goes and asks employees whether they understood that as permission. The answer? 'No. The policy says I'll get fired if I use it.' That gap is the subject of this episode. James is Senior Professor and Director of AI-Enabled Academic Transformation at Lindenwood University, with two PhDs - the first in art history, the second...
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EP278 AI Governance in Higher Ed with Dr. Eugene Chan
AI Literacy for Entrepreneurs
Most organizations govern AI the same way cities govern speeding. They set a rule, then punish people who break it. Dr. Eugene Chan thinks that's the least interesting tool available. He's a behavioural scientist - founder of the consultancy Behavieural and Professor of Business at Tyndale University - and his argument is that punishment is a lagging response to a problem you could have designed out. His analogy is a speed camera versus a speed bump. Both reduce speeding. The camera does it by fining you after the fact, and it needs maintenance forever. The speed bump does it by making the...
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EP277 Is AI Going to Take the Gift of Failure Away? asks Julie Cole
AI Literacy for Entrepreneurs
Episode description Julie Cole and her co-founders started Mabel's Labels in a Hamilton basement 23 years ago, back when customers were still nervous about typing a credit card number into a computer. They figured out early that they weren't really running a label company - they were running a tech company that happened to make labels. Nothing off the shelf did what they needed, so they built it themselves. Which is why her read on this moment carries some weight. She's watched every technology wave since. She's not a skeptic and she's not a cheerleader. She uses AI, has a clear personal rule...
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EP276 Your AI Strategy Is a Hammer. Where's the Nail? - with David Cohen
AI Literacy for Entrepreneurs
"We need AI" is the most common brief in business right now. David Cohen's read on what it means: usually nothing in particular. David is the founder of Superposition, a consultancy for data and AI consultancies - a meta consultancy, as he calls it. He's spent his career inside both big and boutique consulting shops, which makes him refreshingly blunt about what's actually happening in the services world right now. His diagnosis is that we're still in the solution-in-search-of-a-problem stage. Everybody's curious. Everybody's excited. There's enormous movement, enormous hype, and very few real...
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EP 275 "Do I Trust Myself?" Grace Gravestock on the Real Reason AI Adoption Stalls
AI Literacy for Entrepreneurs
Episode description Everyone's arguing about whether AI can be trusted. Almost nobody's asking the harder question underneath it. Grace Gravestock has spent more than twenty years leading change management on some of the highest-profile technology projects around - including the team that set the stage for the $67B Dell EMC integration. Her verdict on why AI pilots stall is unsentimental: it's the same reason ERP stalled, and CRM before that. People aren't using the technology the way it was intended. You can have the best tools in the world, and if people don't use them, it doesn't matter....
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EP 274 The Human OS - AI Adoption With Curiosity, Safety, and Monday Ease ft. Melissa Penton
AI Literacy for Entrepreneurs
In the final episode of the Podcast-to-Book series, host sits down with change leader and AI education lead (Sun Life) for a human-first conversation about what actually makes AI adoption work. They talk productivity vs room-for-life, why one-prompt culture is snake oil, the shift from prompt engineering to context engineering, and the simplest enterprise question that changes everything: “What would make Monday easier for employees?” Episode summary Susan closes out the Podcast-to-Book sprint with a conversation that feels like the point of the whole series: AI isn’t a tool problem....
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273 - Future-proofing your organization through continuing AI literacy
AI Literacy for Entrepreneurs
Most companies do a few AI trainings, run some pilots, and then stall. In this episode, host argues the only real future-proofing strategy is continuous AI literacy. She breaks down what “continuous literacy” actually includes (skill, judgment, workflow, norms), the predictable failure modes of the AI literacy divide, and a simple flywheel you can run monthly so capability keeps compounding. Episode summary Susan opens with a familiar pattern: a burst of AI excitement, a deck called “AI Strategy 2025” a few clever workflows… and then reality hits. Tools change. Policies shift....
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EP 272 - Mindset, Sales, and AI That Actually Helps with Gazzy Amin
AI Literacy for Entrepreneurs
Host sits down with sales strategist , founder of Sales Beyond Scripts, to talk about the real ways AI is changing revenue, planning, and scale. They cover AI as a thinking partner, how to use it across departments in a small business, why audits matter more than hype, and how mindset quietly determines whether you treat AI as a threat or an advantage. Episode summary This episode is part of Susan’s 30-episodes-in-30-days “podcast to book” sprint for Swan Dive Backwards. Susan and Gazzy zoom in on the selling process first. Then they zoom out to the whole business. They talk about three...
info_outlineAI doesn’t fail in organizations because the tools are bad. It fails because culture is glitchy. In this solo episode, host Susan Diaz explains why AI is just the “app” while your organizational culture is the real operating system - and she shares six culture pillars (plus practical steps) that determine whether AI adoption becomes momentum… or messy risk.
Episode summary
Susan reframes AI adoption with a simple metaphor: AI tools, pilots, and platforms are “apps”. But apps only run well if the operating system - your culture - is healthy. Because AI is used by humans, and humans have behaviour norms, and they value incentives, safety, and trust.
She connects this to the “experiment era” where organizations see unsupervised experimentation, shadow AI, and uneven skill levels - creating an AI literacy divide if leaders don’t intentionally design expectations and values.
From there, Susan defines culture plainly (“how we think, talk, and behave day-to-day”) and shows how it shows up in AI: what people feel safe admitting, whether experiments are shared or hidden, how mistakes are handled, and who gets invited into the conversation.
She then walks through six pillars of purposeful AI culture and closes with tactical steps for leaders: naming principles, building visible rituals, supporting different AI archetypes, aligning incentives, and communicating clearly.
Key takeaways
Stop treating AI like a one-time “project”. AI adoption doesn’t have a clean start/end date like an ERP rollout of yore. Culture is ongoing, and it shapes what happens in every meeting, workflow, and decision.
The “experiment era” creates shadow AI and uneven literacy. If unsupervised experimentation continues without an intentional culture, you get risk and a widening gap between power users and everyone else.
Six pillars of an AI-ready culture:
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Experimentation + guardrails - Pro-learning and pro-safety. Define sandboxes and simple rules of the road not 50-page legal docs.
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Psychological safety - People won’t admit confusion, ask for help, or disclose risky behaviour without safety. Leaders modelling “I’m learning too” matters.
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Transparency - A trust recession + AI makes honesty essential. Encourage show-and-tell, logging where AI helped, and “we’re not here to punish you” language.
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Quality, voice, and ethics - AI can draft, humans are accountable. Define what must be human-reviewed and what “good” looks like in your brand and deliverables.
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Access + inclusion - Who gets to play? Who gets training? Avoid new “haves/have-nots” dynamics across departments and demographics. AI literacy is a survival skill.
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Mentorship - Champions programs and pilot teams only work if mentorship is real and resourced (and doesn’t become unpaid side-of-desk work).
Four culture traps to avoid:
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Compliance-only culture (all “don’t”, no “here’s how to do it safely”)
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Innovation theatre (demos and buzzwords, no workflow change)
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Hero culture (1-2 AI geniuses and nothing scales)
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Silence culture (confusion and shadow AI stay hidden and leadership thinks “we’re fine”)
Culture is the outer ring around your AI flywheel. Your flywheel (audit → training → personalized tools → ROI) compounds over time, but culture is what makes the wheel safe and sustainable.
Episode highlights
[00:01] AI is a tool. Culture is the system it runs on.
[01:30] The experiment era: shadow AI and unsupervised adoption.
[02:01] The AI literacy divide: some people “run apps,” others can’t “install them.”
[03:00] Culture defined: how we think, talk, and behave—now applied to AI.
[04:56] Pillar 1: experimentation + guardrails (sandboxes + simple rules).
[07:23] Pillar 2: psychological safety and the shame factor.
[11:37] Pillar 3: transparency in a trust recession.
[13:57] Pillar 4: quality, voice, ethics—AI drafts, humans are accountable.
[16:33] Pillar 5: access + inclusion—AI literacy as survival skill.
[19:00] Pillar 6: mentorship and avoiding unpaid “champion” labour.
[23:31] Four bad patterns: compliance-only, innovation theatre, hero culture, silence culture.
[25:47] The closer: AI is the latest app. Culture is the operating system.
If your organization is buying tools and running pilots but still feels stuck, ask:
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What “AI culture” is forming by default right now - compliance-only, hero culture, silence?
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Which one pillar would make the biggest difference in the next 30 days: guardrails, safety, transparency, quality, inclusion, or mentorship?
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What ritual can we introduce this month (show-and-tell, office hours, workflow demos) to make AI learning visible and normal?
Connect with Susan Diaz on LinkedIn to get a conversation started.
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