Jim Crocker AI

08/04/2026

https://www.jimcrockerai.com/post/how-to-think-about-ai

Is AI good or bad? I have come to see that as the wrong question. AI is an amplifier - of human intelligence and creativity, but also of bias, greed, surveillance and institutional power.

07/19/2026

https://www.jimcrockerai.com/post/using-ai-to-think-better

A conversation about Dan Brown’s Origin became a living example of using AI to think better. These excerpts show AI clarifying complex ideas, identifying deeper questions, challenging assumptions and helping turn broad ambition into practical direction.

07/17/2026

https://www.jimcrockerai.com/post/ai-cognitive-amplification

Most discussion about AI focuses on automation, productivity and job elimination. My experience—and Dan Brown’s Origin—point to something potentially more consequential: AI’s ability to amplify how people question, connect, imagine and decide

06/25/2026

https://www.jimcrockerai.com/post/ai-capture-tools-governance-risk

AI glasses, meeting notetakers, Zoom recordings, and AI scribes create privacy and consent risks when organizations use them without governance oversight.

06/25/2026

https://www.jimcrockerai.com/post/how-to-spot-ai-glasses

Learn how to spot AI glasses, understand the privacy risks of hidden recording, and see what Canadian law says about consent in casual and clinical settings.

06/20/2026

If you’re a director on a public, private or non-profit board or know somebody who is, this Director self-evaluation may be of interest.

Currently, most evaluations are based on ratings, eg, 'how do I rate myself or my Board on strategy from 1-5?'. The problem with ratings is they measure confidence (how do I feel) not competence (what do I know).

This AI-enabled director self-evaluation doesn’t have any ratings. It analyses director responses to key governance questions – and finds strengths, weaknesses, inconsistencies and opportunities. The output is a no-nonsense appraisal (not for the faint of heart) and prioritized directions for becoming a better director. It's the type of analysis that never comes out of ratings-based assessments.

The evaluation isn’t perfect (it will evolve), but it works well – plus it’s a really good demonstration of the future of AI-enabled governance measurement. Try it here. No data is collected and only you see the results. https://directorselfevaluation.com/

A free AI-enabled director self-evaluation that analyzes how you reason through governance — not just what you score. Get a confidential Director Action Plan in 15 minutes.

06/08/2026

A post on social media suggested there is mass buyer remorse from companies that got into AI early. I decided to see if that's true and what lessons can be learned from companies that committed early to AI adoption?

What I found – there is some buyers remorse (expensive!); there are some real success stories and there are these lessons for companies committing now to AI.

1. AI is a force multiplier for capable people. It is not a substitute for judgment and firing people has been costly.
2. Successful AI adoptions were developed first and foremost to solve real business problems
3. AI scales bad data – it doesn’t fix it (and that can be expensive too!)
4. Leadership commitment is a reliable predictor of AI success

With examples from the early-mover companies that these lessons are drawn from.

The first wave of serious enterprise AI adoption is behind us. The results are in. McKinsey found 88% of companies use AI — but only 39% see earnings impact. Four lessons emerge from companies like JPMorgan, Walmart, Bank of America, and Klarna. None of the lessons are about the technology itself....

06/06/2026

Canada has a new AI policy called 'AI for All'. Here are some thoughts on what it means for Canadian business.

Mark Carney's "AI for All" strategy aims to lift Canadian business AI adoption from 12% to 60%. A look at what it promises, where Canadian business really stands, and whether it helps.

06/03/2026

Recent (2025) McKinsey research found that 66% of directors report limited to no knowledge or experience with AI(!!), yet 88% of organizations are already using AI in at least one business function. If you're a director who wants to learn more about AI in your organization here are six strong questions to ask:
1. What AI systems are currently in use across our organization — and who approved them?
2. Who in management owns AI risk — and what does that actually mean in practice?
3. What data are our AI systems trained on or using — and do we have the rights to it?
4. What happens when an AI system gets it wrong — and what is the escalation path?
5. How do we know our AI systems aren't producing discriminatory outcomes?
6. Are we using AI to do existing things faster — or to fundamentally change how we compete?

Strong AI governance doesn't require directors to be technical experts. What it does require is the willingness to ask specific, probing questions and to expect answers that are equally specific.

05/26/2026

Over the last few weeks I built and published five working AI apps. I'm not a coder.

Based on my coding 'success' it was tempting to conclude that software developers are about to disappear. But then I had a moment with a badly framed prompt that quietly burned through hours of work and a chunk of my budget. The AI worked confidently for a long time, producing output that looked like progress but wasn't.

That small, personal error turned out to be the real story — and it's the question I think Boards should be asking their CEOs right now.

I wrote it up for directors, CEOs, and anyone trying to think clearly about AI in their organization. Link is in first comment (note: putting it in comment is a traffic experiment).