In Episode 23 of Season 7 of Data Debrief, Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's conversation with Greg Freeman, CEO and Founder of Data & AI Literacy Academy, and the gap between organisations that have given everyone a Copilot licence and those that are actually using AI to change how the business operates. As Catherine puts it, a Sunday league player and a Premier League player are both "playing football" – but nobody's confusing the two.
They also get into the week's headline that AI has a "greater than 10% chance" of wiping out humanity, why a growing anti-AI mood outside the data bubble matters for leaders trying to drive adoption, and why a landscaper turned content creator might be the best human-in-the-loop example going.
They also discuss:
Why September is the real new year for data leaders, with budget season and event chaos hitting at once.
Why the "AI will kill us all" headlines are irresponsible without the evidence to back them up.
How to tell the difference between a credible warning and a researcher looking for a headline on the way out the door.
Why 70% of Facebook comments on an AI-generated event poster are people refusing to attend, and what that tells leaders about the mood outside the bubble.
What a year five "meet the teacher" evening on WhatsApp groups has in common with the AI conversations happening in boardrooms.
Why the toilet-door graffiti of the 1970s and today's comment sections are the same human behaviour at a scale our brains can't cope with.
How Catherine explains agentic AI at the dinner table with trains and tracks, and why it still doesn't land.
Why "AI" is used to mean automation, machine learning, LLMs and agents interchangeably, and why that confusion matters.
What "buttonology" means, and why both hosts are stealing the term.
Why training and education are two different interventions, and why most organisations only do the first one.
What Greg's three personas – the asker, the conversationalist and the process redesigner – reveal about where most employees really are.
Why AI maturity scales measure who can drive the machine rather than who's transformed their thinking.
Why organisations want competitive advantage but are investing in local productivity, and why the two aren't the same thing.
Why picking four or five core use cases beats a Venn diagram of everything you could possibly do.
Why leaders must ask "have you actually understood this?" before accepting AI-assisted work.
Why people treat LLMs like Google when Google gave you sources and LLMs give you a decision.
Why the absence of sponsored results in LLMs makes people less likely to question what they're served.
Why the context layer, not the tool, is where the real value in AI sits.
What a founder's blanket ban on "Claude content" reveals about the perception problem holding back adoption.
Why whether AI sits with the CIO or the CDO comes down to whether it's seen as a tool or a transformation.
Why culture has to allow people to rip up a process and fail before any of the redesign talk becomes real.
Why cutting graduate intake could leave businesses with a succession crisis in a few years' time.
How the Dodgy Gardener quit his day job by pairing ChatGPT garden designs with advice from tradespeople in the comments.
Why attention is the digital currency of the future, and why B2C businesses will create roles to work out how to win it.
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