A Non-Technical Leader’s Guide to Getting Value From AI
How a non-technical leader gets real value from AI: start from problems, know what AI is good at, set a boundary, judge the cost, and name an owner and a measure.
How a non-technical leader gets real value from AI: start from problems, know what AI is good at, set a boundary, judge the cost, and name an owner and a measure.
The real reasons AI projects fail, and how to choose ones that pay off: start from a number, check the data, scope to production, give it an owner and guardrails.
How to write a one-page AI acceptable use policy people will actually follow: what to encourage, what to prohibit, the data line, approved tools, and keeping it live.
When to buy AI off the shelf and when to build it, the questions that decide it, the sensible middle ground, and where SMEs waste money.
How to build a practical AI strategy for an SME: start from the business, prioritise a few costed uses, tie in governance and ownership, and keep it small enough to deliver.
What AI readiness really means for an SME, the four things that decide it, and how to check whether you can get value from AI now or need to fix foundations first.
What an AI opportunity review looks at, where AI genuinely pays off for an SME, where it does not yet, and how to get a costed shortlist before you spend.