A business-tested, down-to-earth explanation every board member with twenty minutes to spare and zero patience would like to hear.
Generative AI is on every board agenda — yet the conversation quality is rarely remarkable. Three reasons:
Transformers, LLMs, fine-tuning, RAG. The room fills with the stench of acronyms, the board nods along — and nobody can take decisive action on the most transformational technology of our lifetime.
Every vendor swears their AI will “revolutionize” your business. Without strong tech anchors, all the board can do is pick whomever they believe the most — basically a pitch contest.
Nobody wants to be the director who asks, “So what is this, exactly?” The result: million-dollar decisions about technology investments that no one at the table can explain.
Generative AI is what Google would be if you built it in 2024: the personality of a moody teenager, a pathological liar, and shaped in the image of the world we'd like to see.Our favorite internal definition — and the most useful one for deciding with a clear head
No acronyms, no math. These five ideas are enough to hold your own in any AI conversation:
These systems are trained on staggering amounts of text, images and data. Their “knowledge” is exactly as good — and exactly as biased — as what they absorbed.
Billions of mathematical “parameters” calculate the most likely next word. Impressive — but it doesn't understand reality the way a person does, which is why it can be brilliant and absurd in the same sentence.
It invents with the same confidence it has when it's right. For a company, this is the dangerous part: people take its output as fact and skip the verification — automation bias is thoroughly documented. Anything critical needs a human check. Which points to a truth nobody says out loud…
The evidence is nuanced: AI is absorbing routine, entry-level work — not expert judgment. Companies that use it purely to cut headcount lose to the ones that use it to make their people better. Human judgment is the most undervalued asset of the AI era.
How these models behave changes from one quarter to the next. The rules get rewritten, and the black boxes never get fully audited. The only way to build on a strong foundation is to govern methodically — not with faith “in the system”. Governing with method starts with strategic alignment.
If management or your vendors can't answer these six questions clearly, stop the conversation before proceeding any further:
Not “IT.” A cross-functional ownership team with a mandate, the right skills and a budget. If that doesn't exist, creating it is the first decision.
The honest answer is never “nothing.” “Shadow AI” — ungoverned AI use — exists in every company. The question is whether you govern it, or keep pretending it isn't there.
What confidential information might be leaving the company through careless AI use, and what rules exist to stop it. The answer defines your IP exposure and your legal and reputational liability.
For anything considered production-worthy: which use cases have an owner, KPIs and a clear baseline? Pilots without a baseline are expenses dressed up as innovation — MIT put that number at 95%.
Inaction has a price too: efficiency your competitors capture, talent that walks out the door, learning that never compounds.
How AI is used responsibly in decisions, when it's appropriate and with which tools, what the ground rules are — and who takes charge when something goes wrong.
Generative AI isn't a technical topic. It's a corporate-governance topic, anchored in the company's mission and principles — and like every board matter, it gets governed with clear information, owned decisions and method. Not with anxiety, doubt or hype.
We can run a free live session — 60 minutes, business language, no question too basic — for boards and executive committees. Let's grab a coffee and set it up.
