Translate, Don't Teach

I’ve walked into more meetings than I can count with a deck built around the AI architecture I was proud of. The agentic workflow, the model routing, the observability layer we’d spent time getting right. By the third slide, the audience was checking their phone and others have already flipped ahead to the appendix, looking for a number. Nobody in that room doubted the engineering. They just couldn’t tell, from what I’d shown them, whether it was worth another dollar.

I used to think the fix was more explanation. Slow down, add a glossary slide, spend ten more minutes on what a large language model actually does. That instinct turns out to be almost exactly backwards. The Deloitte Global Boardroom Program’s latest Governance of AI survey of 695 board directors and executives across 56 countries found that two-thirds still say their boards have “limited to no knowledge or experience” with AI. That’s an improvement (it was 79 percent a year earlier), but it means most boards you’re presenting to this year still aren’t fluent. And yet the same survey found only 8 percent of boards don’t engage with management on AI at all. The knowledge gap isn’t shutting the conversation down. It’s just changing what the conversation needs to be about.

Closing a knowledge gap with more education is a sound instinct in almost every other part of the business. It’s the wrong instinct here. Deloitte’s survey found that even as board AI literacy inches up, 31 percent of boards still say AI isn’t on their agenda at all (down sharply from 45 percent a year earlier), and a third of respondents say their boards still aren’t spending enough time on the topic. Boards aren’t asking for a seminar. They’re asking for something they can act on despite not being AI-literate, and that’s a very different assignment than the one most technical leaders prepare for.

This is particularly relevant for a CTO, because it reframes the job. Teaching the board how a model works is optional. Translating what it’s worth to the business is not. Those are two different skills, and most technical leaders default to the one they’re better at (mine, obviously, is the one my board never asked for). The gap between “I can explain this” and “I can make the board comfortable approving this” is where most AI proposals actually stall.

PwC’s Governance Insights Center found something adjacent in its own research on boardroom communication: 74 percent of directors say they want more time spent on strategy, not less, even as total board time stays flat or shrinks relative to everything competing for it. Their advice for executives boils down to a habit most of us break the moment we get nervous: name the headline before the supporting cast arrives, and let every fact in the room work in service of that one line rather than compete with it for attention.

I’ve started building every AI slide backwards from the single number I want the board to remember on the drive home. Not the token count, not the model name, not the roadmap. A dollar figure, a percentage, a date. Everything else in the deck exists to support that number, not to audition for its own applause. It’s a smaller deck than the one I used to build, and it lands better every time.

If a Deloitte-style knowledge gap is the industry norm, health system boards stack a second layer on top of it. A Black Book Research survey of 202 health system executives and 84 board members found that 94 percent of respondents say their organizations are prioritizing technology investments precisely because of their near-term, easy-to-measure payoff: lighter clinical burden, faster workflows, cleaner documentation. Healthcare boards aren’t skeptical of AI’s long-term promise. They’re skeptical of vague ones.

That tracks with what I see in my own boardroom. Pushback on an AI proposal rarely comes because the technology is unproven; it comes when the value is unproven on the board’s timeline. In a regulated, patient-facing business, “trust me, it pays off eventually” is a much harder sell than it would be in a typical SaaS pitch, and a HIPAA-covered board has every right to ask harder questions than a typical SaaS board would. The ask has to show up with its receipts already attached, not a promise to send them later.

The practical version of all this is less a slide template than a discipline: lead with the outcome in the board’s own currency (revenue, cost, risk-adjusted timeline), frame governance as the reason to trust the number rather than as a caveat that undercuts it, and leave exactly one ask on the table instead of three.

Deloitte’s survey also found that boards already pull CFOs into AI conversations 27 percent of the time, more than double the rate for CISOs or CROs. That’s a tell worth acting on. Your board already wants the finance lens in the room before you show up. Beat them to it, and the technical story becomes the appendix it should have been all along.

The next AI deck I build starts with the number, not the architecture. Everything else has to earn its slide by supporting that number, or it doesn’t make the cut.