AI Strategy & Risk for Leadership

CEOs, COOs and senior leadership teams.

Set a clear AI direction for your organisation and govern its risks — not just understand the technology.

AI tools are spreading through companies faster than most leadership teams can set direction, which means staff are improvising rules in the gaps. Without a clear line from the top, you risk wasted spend on tools that don’t pay off, plus confidential information ending up in places it shouldn’t. Setting direction now is cheaper and calmer than correcting course after something goes wrong.

• Tell apart where AI can realistically help your business today from where the hype is running ahead of reality
• Pick and rank AI opportunities by the value they create and how hard they are to deliver
• Set a clear AI direction your teams can actually act on, with a few simple guardrails
• Decide when to build a tool, buy one, or wait — and roughly what each path costs you
• Draw clean accountability lines so it is never unclear who owns an AI decision
• Walk out with a one-page AI strategy your leadership team can use straight away

1. What AI can and can't do for your business right now

   • A plain-English picture of what today's AI tools actually do well
   • The difference between everyday AI assistants and purpose-built business systems
   • Common myths that lead to wasted spend, named and debunked
   • Where AI is already quietly being used across your teams today
   • How to judge a confident vendor pitch without a technical background

2. Where the real value is — and where the real risk hides

   • Spotting the tasks across your business where AI saves genuine time or money
   • A simple way to score opportunities by value and how hard they are to deliver
   • Sequencing a shortlist of use cases into a sensible order to tackle them
   • The places AI quietly introduces risk — bad decisions, data leakage, over-reliance
   • Checking whether your data and systems are ready before you commit

3. Setting an AI direction your teams can act on

   • Writing a short, clear statement of what AI is for in your organisation
   • Connecting the AI direction to goals your teams already care about
   • Deciding which decisions stay with people and which AI can assist
   • Naming who leads AI work and how progress gets reviewed
   • Communicating the direction so staff stop improvising their own rules

4. Guardrails: the few rules every organisation needs

   • The small set of rules that prevent most avoidable AI mistakes
   • What company information should never go into an outside AI tool
   • When a human must check AI output before it is acted on
   • Keeping a simple record of where AI is used and who owns it
   • Light-touch global principles — fairness, transparency, accountability — without legal overload

5. Spending wisely: build, buy or wait

   • The three paths — build your own, buy a tool, or hold off — and when each makes sense
   • What to ask a vendor before signing, and how to check their claims
   • Rough cost drivers beyond the licence fee: data, integration, training, oversight
   • Why adoption, not the tool, decides whether spend pays off
   • Avoiding lock-in and pilots that never turn into real value

6. A one-page AI strategy you leave with

   • Pulling your direction, priorities and guardrails onto a single page
   • Assigning owners and next steps so the page becomes action
   • Agreeing how you'll measure whether AI is actually helping
   • Setting a simple review rhythm to revisit the plan
   • A reusable template your leadership team keeps and updates