World Model Readiness Seeing through the AI pitch

Module · Seeing through the AI pitch

The Procurement Team AI Check

AI vendors sell the demo, and the demo is always the best day the product will ever have. Your procurement team stands between a slick pitch and a contract that is hard to leave, expensive to run, and built on claims nobody tested. This module checks the five disciplines that let the buying team see through the deck: testing the technical claims on your own data, checking references the vendor did not hand-pick, modelling the true cost past the licence line, holding a standard on exit terms, and scoring the specific risks an AI supplier brings that a normal software vendor does not.

Question 1 of 5 · Claims tested on your data

Do you test an AI vendor's technical claims on your own data before buying?

A vendor demo runs on data the vendor curated to make the product shine. Your data is messier, and the gap between the demo and your reality is where the disappointment lives. A proof of concept on your own inputs, measured against your own bar, is the only claim that counts. Everything before that is marketing.

Question 2 of 5 · References you chose

Do you check references you sourced yourself, not just the ones the vendor hand-picked?

The references a vendor offers are its happiest customers, coached and cherry-picked. The useful conversation is with a customer you found yourself, ideally one who churned or struggled. In a young AI market where products change monthly, a candid reference about what broke is worth more than three glowing ones about what worked.

Question 3 of 5 · True cost is modelled

Can your team model the real total cost of an AI tool, past the licence line?

The licence fee is the visible tip. Underneath sit usage-based charges that scale with success, integration and data-prep effort, the internal time to run and monitor it, and prices that reset at renewal once you are dependent. A team that models only the sticker price is comparing vendors on the one number designed to be compared.

Question 4 of 5 · Exit is negotiated in

Do your AI contracts include real exit terms: your data out, in a usable form, on notice?

The moment to negotiate leaving is before you sign, while you still have leverage. AI vendors lock you in through your accumulated data, tuned configurations, and embedded workflows. A contract with no clean exit, no data export in a usable format, no reasonable notice, turns a tool you outgrew into a hostage situation at renewal.

Question 5 of 5 · AI-specific risk scored

Do you score the risks specific to AI suppliers, not just the standard vendor checklist?

An AI supplier carries risks a normal software vendor does not: where your data goes and whether it trains their model, which foundation model sits underneath and what happens if it changes, how the tool behaves under the EU AI Act, and whether a young vendor will still exist at renewal. A generic security questionnaire asks none of this.

For the statistics · one click each

Three questions for the public picture

These do not affect your score. They feed the anonymised, aggregated statistics; groups under 8 respondents are never shown.

How many AI tools has your team bought or is evaluating?

None yet
One or two
A handful
Many, across teams
We have lost count

What do you require before an AI purchase is approved?

A vendor demo
Vendor benchmarks
An informal trial
A proof of concept on our data
No set requirement

How do your AI contracts handle leaving the vendor?

No exit terms
Whatever the vendor offered
Exit terms negotiated in
Exit negotiated and tested
No AI contracts yet

Your context

Used to calibrate the report. Company size and sector remain in the anonymized dataset; your email does not.