Every boardroom right now sounds the same. Someone presents a slide on AI pilots, someone else mentions employee training on GenAI, and everyone nods as if progress is happening. But none of that answers the real question: Is AI changing the business in any material way? Sanjay Srivastava, writing for Forbes, says boards are stuck in demo mode. What they need is interrogation mode. Ten questions that cut through the hype and expose whether AI is creating outcomes or just theatre. It is uncomfortable, but it is the only path to real advantage.
Breakdown:
The article lays out ten board-level questions that shift AI conversations from feel-good updates to real accountability.
1. Ambition
Is the company trying to be a frontier leader or a fast follower, and in which functions?
This choice dictates risk appetite, capital allocation, and the speed of experimentation.
2. Strategy
How does AI reinforce or reshape the existing strategy?
If AI discussions never touch the business model, it is still being treated as a tech tool, not a strategic driver.
3. Outcomes
Are leaders measuring activity or results?
Pilots, training hours, and LLM accuracy are input metrics.
Boards should ask where margins improved, costs dropped, quality increased, or cycle times shrank.
4. Freed Capacity
When AI saves people time, where does that time go?
If it is not redeployed deliberately into revenue, innovation, or service improvements, it vanishes into daily noise.
5. Board Fitness
Does the board itself have the capability to oversee AI?
Not data scientists, but directors who understand value creation, risk, and transformation in an AI world.
6. Ownership
Can non-technical leaders explain the company’s AI strategy clearly?
If only the CIO or CTO can answer that question, AI is still a siloed technology project.
7. Workforce Readiness
Is the organisation psychologically and practically ready for AI?
Fear of job loss and blindness to existing waste are bigger blockers than tools.
8. Skills, Not Tools
Are teams trained to think about their work, not just use AI tools?
AI-ready teams understand workflows, judgement calls, and value points.
9. Assurance
What is the company’s audit, risk, and control framework for AI?
Boards must understand data lineage, bias monitoring, model drift, vendor risks, and IP protection.
10. Accelerators and Blockers
Who is driving AI adoption and who is slowing it down?
Resistance can come from genuine concerns or entrenched comfort zones. Boards need visibility into both.
The article closes by urging boards to embed AI into every committee: Strategy, Audit, Risk, Talent, Governance, and Compensation. Not as a separate agenda item, but as part of how the entire organisation operates.
Why this matters:
AI will soon be as foundational as finance, supply chain, or governance. Boards that treat it as an IT experiment will fall behind boards that treat it as a business transformation. The companies that win will be the ones whose directors ask harder questions about outcomes, impact, risk, talent, and capability. The real competitive edge in the next decade will come from governance quality, not model quality.
The Big Picture:
AI is becoming a structural force across industries, but adoption is uneven. Most companies are dabbling. A few are transforming. Boards are the difference. When directors demand clarity, rigour, and alignment to strategy, AI becomes a force multiplier. When boards accept dashboards and demos, AI becomes a side project. Governance is emerging as the next big battleground in enterprise AI.
The Crunch:
The board across the street is not smarter. They are just asking tougher questions. And that is what will decide who wins the next decade.