Peter sits down with Kamil Banc — fractional Chief AI Officer, founder of AI Adopters Club, and self-described practitioner of “boring AI” — to talk about why AI adoption inside mid-market companies stalls, why culture eats tooling for breakfast, and why the marketers chasing the latest model release are usually the ones getting left behind.
Kamil’s core argument: the AI edge isn’t at the frontier. It’s in the fundamentals. The companies winning with AI right now aren’t the ones with the best tools — they’re the ones where employees have the time, safety, and motivation to develop AI intuition on real work. Everything else is theater.
About Kamil Banc
Kamil Banc is a fractional Chief AI Officer and AI culture advisor for mid-market American companies. He runs the AI Adopters Club, a newsletter with 13,000+ subscribers focused on practical AI workflows for operators, not enthusiasts. Born in Poland, raised in Germany, lived in Hawaii for a decade, now based in Jupiter, Florida. He describes himself, not entirely ironically, as an immigrant who’s more American than most Americans.
You can find Kamil at AI Adopters Club or on LinkedIn.
About Peter Benei
Peter Benei co-founded AI-Ready CMO the daily intelligence platform for senior marketing leaders. Peter has been serving as a CMO, marketing leader, and consultant to high-growth B2B scaleups for the past 10+ years. He has a background in advertising, working with Fortune 500 brands.
Connect with Peter on LinkedIn or read his newsletter.
Top 10 Takeaways
Boring AI beats frontier AI. Chasing the latest model release is a distraction. The compounding returns come from building repeatable evaluation processes — how you prompt, how you test outputs, how you record what works across tools. That’s the infrastructure nobody brags about on X, and it’s the infrastructure that actually moves the needle.
AI is a culture problem, not a tool problem. Buying team licenses and declaring victory is how 90% of rollouts die. Adoption happens when leadership creates time, space, and psychological safety for experimentation — not when they hand down a mandate and a Chat GPT seat.
Shadow AI is the canary. Employees are already using AI. They just won’t tell you, because they’re worried that automating their work will automate them out of a job. No company has a real AI governance policy yet, and until there’s an onboarding path with no punishment, shadow AI stays in the shadows — and its productivity gains stay off the books.
There are three types of AI-adopting leaders. The honest cost-cutter (we want to do more with less). The optimist who becomes a cost-cutter two weeks into the assessment (we’ll enable our people, actually wait, let’s freeze hiring). And the true believer. All three need to tell employees the same thing: your current job is going away, so automate it yourself before someone else does.
The play is the director’s chair. If you’re a graphic designer, let AI push the pixels, and you steer the brand voice. If you’re a data analyst, let AI crunch the data, and you learn corporate storytelling. Get above the compute layer — where decisions happen before AI can make them — while the window is open.
Coordination is 30% of the job. AI is coming for that too. When leadership talks about “AI productivity gains,” they usually mean outputs. The bigger lever is coordination — the meetings, the status updates, the Slack back-and-forth. Reduce coordination by 10%, and you’ve freed up serious hours. You’ve also diplomatically reduced the need for stakeholders.
Jevons’ Law applies to labor. Give a worker 5x productivity, and the boss will give them 5x the work at the same pay — because the competition is doing it too. There’s no structural incentive for companies to give back the gains. Workers figuring this out are already running two or three full-time remote jobs and planning to retire in ten years.
Minds Blown Per Week is the real adoption metric. Corporate AI training — “here’s how to generate a report with AI” — doesn’t create adopters. What creates adopters is a personal moment of disbelief. Writing a children’s book in four hours. Building a tool for your kid. Once the mind is blown, the person starts asking, “What else can I do with this?” across every domain of their life. That’s the flywheel.
Horse blinders beat tool sprawl. For anyone starting out: pick one project, solve it end-to-end, ignore every new tool and model release until you’re done. The hype cycle is designed to keep you shopping. Strategic focus on a single problem teaches you more about how AI actually works than a year of newsletters.
Taste is the new bottleneck. When spinning up a landing page takes an hour instead of a week, the constraint shifts. The question stops being “can we build this?” and becomes “is it worth building?” That’s a judgment problem, not a capability problem — and most teams don’t have the organizational muscle for it yet.
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The article referenced on the live recording by Kamil: How to build your brand system in 45 minutes without an agency.
