THE SHORT ANSWER
Six questions, drawn from six weeks of conversations with pharma R&D leaders, that test whether an AI program will hold up under examination. None of them are technology questions. They can be answered in a room with no laptops open, and the answers say more about readiness than most maturity models.
Six weeks of listening, six questions
I started this series expecting to write about models and ended up writing about questions. Six of them kept returning in conversations with pharma R&D leaders, investors and technology partners, and they are collected here in one place.
Why questions rather than answers
Every AI maturity model I have been shown produces a score. Scores are useful for reporting and almost useless for deciding what to do on Monday. A question that cannot be answered points directly at the work.
None of these are technology questions. They can be answered in a room with no laptops open, by people who know how the work runs. The answers say more about AI readiness than any assessment I have seen.
Infrastructure is not the exciting part of AI. It may prove to be the part that decides who gets to keep going.
How to use them
Take one into a review that is already scheduled. Do not announce it as an exercise. Ask it in the ordinary course of the meeting and pay attention to how long the room takes to answer.
The pause is the finding. A question that produces four different answers from four people is telling you something a maturity score would have averaged away.
The one that matters most
The sixth question is the whole series. Six months from now, will it hold up? The first five are how you find out, and each takes a different route to the same place: whether the reasoning behind a decision will survive the people who made it.
One note from outside the list. These questions are not hypothetical. The foundation that institutions built for the world’s most complex multimodal research is now running inside a top-five pharmaceutical company; where the same upstream questions carry higher stakes.
What those teams share is not budget. It is that they treated readiness as the work, not a cleanup after the AI arrived.
The question to take into your next AI review
Which of the six can your organization not yet answer?
That is the conversation I would like to have next, and it is a better use of a meeting than another readiness assessment.
