Everyone Is Talking About AI. The Board Is Asking Different Questions.
In most organisations, AI conversations start enthusiastically.
There is excitement about productivity gains, competitive advantage, and “not being left behind”. Tools are trialled. Licences are purchased. Pilots are launched.
But when AI reaches the boardroom, the tone changes.
The questions become quieter, sharper, and more uncomfortable:
- Where is AI already being used in our business?
- What data is being exposed, and to whom?
- What risk have we unintentionally introduced?
- What value are we actually getting for what we’ve spent?
These are not anti-AI questions.
They are leadership questions.
And increasingly, boards are asking them earlier than many organisations expect.
AI Is Already in the Business – Whether You Planned for It or Not
One of the biggest misconceptions about AI adoption is that it is a future decision.
It isn’t.
In reality, AI is already present in most organisations:
- Employees using public AI tools to save time
- Teams experimenting with copilots and automation
- Departments running pilots with limited oversight
- Third-party platforms embedding AI by default
Much of this happens with good intent. People are trying to work more efficiently. But it often happens outside any formal strategy, governance, or operating model.
This is not a failure of people or technology.
It is a gap in organisational design.
Why the Board Is Right to Be Concerned
From a board perspective, AI introduces a unique tension:
- The business wants speed and innovation
- Security and risk want control and assurance
- IT is expected to enable both, often without additional resource
Without a joined-up approach, AI adoption creates fragmentation:
- Pilots that cannot scale
- Risk that grows faster than value
- Spend that increases without clear return
- Confusion over ownership and accountability
This is why many executives struggle to answer a simple question:
“Is our AI investment actually working?”
The Real Issue Isn’t AI. It’s the Lack of an Operating Model.
Most organisations do not fail at AI because the technology is immature.
They struggle because AI is introduced piecemeal:
- As isolated tools
- As disconnected projects
- As experiments without a path to scale
AI is treated as something to try, not something to run.
But AI is no longer experimental in its impact.
It affects data, decision-making, risk posture, and culture.
Anything with that level of influence requires structure.
What Comes Next
Over the next few weeks, we’ll explore why:
- Pilots rarely lead to sustained value
- Technology alone often increases complexity
- Governance doesn’t have to slow innovation
- Adoption is ultimately a people challenge
- AI value must be measurable to be defensible
Most importantly, we’ll explore what it looks like when organisations stop “doing AI” – and start operating it properly.
Because the organisations that succeed with AI won’t be the ones that move fastest.
They’ll be the ones that move with intent, control, and clarity.
If you’re keen to stay ahead of the AI curve, tune in to our four-part webinar series ‘The AI Endgame‘, designed for senior leaders who want to move beyond the hype and understand how AI can deliver measurable impact across the enterprise.
