WHY THIS MATTERS TO ME (AND SHOULD TO YOU)
I’ve spent the last few years turning AI and XR into real upskilling tools - often in mission-driven organisations where the stakes are human, not just financial. The pattern is always the same: the board wants impact without nasty surprises; the teams want clarity without red tape. When governance works, you get both. When it doesn’t, you get “policy theatre” and stalled pilots.
This article distils what I’ve seen work - from framing the right conversations to operationalising guardrails - so your board can lead decisively without slowing the business to a crawl.
GOVERNANCE IS NOT A BRAKE. IT’S TRACTION
Most AI “governance” reads like a list of things you can’t do. That’s a missed opportunity. Good governance is an enablement system: it accelerates the right work and constrains the wrong work. Think of it as product management for decision-making - shipping value, safely, on purpose.
FOUR FAILURE PATTERNS I KEEP SEEING
1. Agenda drift: AI appears as a one-off board topic, then vanishes. No continuity, no momentum.
2. Shadow pilots: teams experiment in the dark; leaders discover them when something breaks.
3. Policy theatre: beautifully worded principles, zero operational bite.
4. Measurement myopia: cost savings tracked; trust, inclusion and experience ignored - until they bite back.
THE THREE LINES OF SIGHT
When I build AI/XR tools with clients, the boards that get results hold these lines of sight at once:
Ethics, trust, cultural inclusion and measurable impact sit across all three. If any line goes fuzzy, risk rises and value leaks.
SEVEN MOVES TO BUILD GOVERNANCE THAT WORKS (AND LASTS)
Make literacy a verb: Replace AI keynotes with hands-on governance. One hour a month, board and execs use the tools (yes, personally), critique outputs, and surface issues together. Curiosity isn’t a nice-to-have - it’s operational risk management.
Upgrade your competency matrix: You don’t need a board full of data scientists. You do need plural perspectives - product, risk, behavioural psychology, and change. Add “AI-cognate” experience to succession plans so oversight doesn’t hinge on one champion.
Map your system before you audit it: Instead of hunting “shadow AI,” draw a living system map: data sources, models, prompts, human checkpoints, third parties. Then audit reality against the map. In one client, this simple map surfaced a silent dependency that would’ve slowed procurement by three months.
Codify decision rights: “Who decides?” is the most underrated governance question. Create a decision rights grid for AI:
Turn principles into controls: Principles are direction. Controls are traction. Embed guardrails where work happens: templates, prompts, model access tiers, data retention defaults, vendor clauses. If a policy lives only in a PDF, it’s theatre.
Measure what money misses: I use a simple scorecard I call QUIP:
Set a cadence you can keep Governance fails when it’s episodic. Stand up a monthly AI review (operations), a quarterly risk & ethics check-in (board committee), and an annual strategy reset (full board) with explicit “start/stop/scale” decisions.
WHAT CHANGES WHEN YOU LEAD THIS WAY
When boards govern for traction, three things happen fast:
A 30/60/90 BOARD STARTER PLAN Days 1–30: Clarity
Days 31–60: Controls
Days 61–90: Cadence
FOR BOARDS WHO WANT MOMENTUM, NOT NOISE
If you’re serious about leading your organisation into the AI era, start small but start in the work - where models, people and processes meet. That’s where trust is built and value is created.
EXECUTIVE PROMPTS TO TAKE INTO YOUR NEXT MEETING
This is the work I love: blending leadership psychology with deep tech to help senior teams ship AI responsibly and at pace. If you want a structured push, my programmes are built for this - from an Executive Insights briefing to the Strategic Momentum Workshop, the Transformation Masterclass, and ongoing Coaching & Micro-Labs.
Relationship-first beats transaction-first - always.