Agree what good looks like before AI goes live
Three people have to agree the standard before an AI step touches real work, and it has to be a standard a reviewer can apply in seconds.
Articles on making AI useful in a UK business
Practical notes on making AI earn its place in a real business: start with one useful job, prove the value, and build from what pays back.
How to control AI running costs
The four lines an AI tool costs you every month, and the short review that keeps all of them in view.
What to do when AI gets it wrong
How far a wrong answer travelled decides what it costs you, and what you should do in the hour after you spot it.
How to write an AI use policy
A one-page policy that answers the four questions your people actually have at the moment they use AI.
When to involve your IT partner
The four triggers that mean a technical conversation is due, and how to brief the person who has to support the thing afterwards.
Moving on to the next job
How to tell your first AI job is finished, and how to pick a second one that teaches you something the first could not.
What a first AI job costs
The four costs behind a first AI job, how to build an estimate you can defend, and the limits that turn that estimate into a decision.
You don't need an AI strategy to start
A strategy is a useful document and worth writing. It is simply a better one after you have run a single job for three months.
Who owns the job
AI jobs rarely fail outright, they fade. Ownership is what stops that, and it means three specific things rather than a line on a job description.
How to measure a soft win from an AI job
How to turn a vague sense that AI is helping into one honest number you can decide on.