Buying and running AI

What an AI investment returns against what it costs, counted honestly enough to include the time spent adopting and maintaining it.

One specific job you intend AI to do, defined narrowly enough that you could tell whether it worked.

The set of AI tools an organisation actually runs together, chosen to cover its work rather than bought as one vendor's suite.

A small build to test whether an idea works at all, deliberately short of production quality and often mistaken for it.

A limited live trial with real users and real work, the step where most of what a proof of concept missed shows up.

An AI system people depend on for real work, which brings expectations about reliability, support and cost that a trial never faces.

Staff using AI tools the organisation has not approved, usually with good intentions, and the reason many first policies get written.

The choice between paying for a finished tool and assembling your own, usually decided by whether the capability is core to you.

Everything a tool costs over its life, including setup, training, integration and the staff time to run it, not only the licence.

An organisation's stated plan for where AI is worth using and where it is not, which mostly earns its keep by ruling things out.

How far a tool has actually been taken up in daily work, as opposed to how many people were given access to it.

A small central team that sets standards and supports AI work across an organisation, rather than owning every project itself.

The formal process of getting a purchase approved, which for AI tools often takes longer than the evaluation that preceded it.

Buying and starting on your own with a card, without talking to anyone, which suits small teams and rarely fits regulated work.

Buying through conversations with a vendor's sales team, which is how enterprise terms, security review and custom pricing are reached.

How hard it would be to move off a tool later, worth weighing while switching is still cheap rather than when it is not.

One named person's access under a plan, the unit most software is still sold in and the one AI pricing is moving away from.

The gap between a promising trial and something the organisation runs, where most AI projects quietly stop.

The person in a team who takes a tool up first and brings others with them, usually worth more to adoption than training does.

How long it takes before a tool is genuinely paying back, the measure that separates a quick win from a long programme.

The tier where a vendor's data handling, security and support terms usually change, which is why it is compared separately from features.

Where an organisation configures a tool centrally, including who has access, what is retained and which controls are enforced.

Taking a tool from a working pilot to everyone who should have it, which is a communication and training job more than a technical one.