AI implementation partner: how to choose one (checklist)

Start with what you need, not who you like

Before you speak to any supplier, write down the problem in a paragraph: what is slow or error-prone, who is affected, and what a good outcome looks like. Partners who are given a clear brief produce clearer proposals, and you can compare them on equal terms.

Decide too who inside your business will own the project. A partner can build and advise, but someone on your side has to make decisions, supply access and champion the change.

The checklist: approach and scope

• Do they ask about your process and your people before proposing technology?
• Is the work split into stages, each with a defined deliverable and a decision point?
• Do they explain what is out of scope, and what would change the price or timeline?
• Are they willing to start with a small pilot before a larger commitment?
• Do they discuss measurement, so you can tell whether it worked?
• Are they candid about where AI is a poor fit and a simpler tool would do?

The checklist: data, security and compliance

Any partner who touches your data should be able to explain, without jargon, where it is stored, who can access it, which third-party AI services are involved and how long information is kept. If personal data is involved, they should be comfortable discussing UK GDPR, data processing agreements and data protection impact assessments.

Ask what happens to your data if the relationship ends, and whether your information is used to train anyone else’s models. Vague answers here are a red flag.

The checklist: ownership, support and contract

• Who owns the code, workflows and configuration once built?
• Will you receive documentation another supplier could pick up?
• Are you tied to the partner’s own accounts or licences, or can you move?
• What support is included after launch, and what is charged separately?
• What are the notice periods and exit terms?
• Who is actually doing the work, and will they be the people you meet?

Checking credibility without being fooled

Ask to see examples of work and, where possible, speak to a past customer about how delivery actually went: communication, handling of problems, and whether the result lasted. Be careful with glossy claims about savings or returns. Honest suppliers talk about ranges, assumptions and what depends on your own data.

Also notice how they handle your questions. A partner who explains trade-offs, admits uncertainty and says no to some ideas is usually safer than one who agrees with everything.

Red flags worth walking away from

• Guaranteed outcomes or fixed savings promised before they have seen your process.
• Pressure to sign quickly or commit to a long contract up front.
• No clear answer on data location, access or retention.
• Everything is described as AI, with no explanation of how it works.
• Proposals with no stages, no deliverables and no way to stop early.

Frequently asked questions