Accountability requires evidence.Evidence requires measurement.
Measure what your AI is doing and what the people around it can do, with evidence you can act on.
You are spending real money on AI.
Your developers are building with it.
Your employees are using tools you did not choose.
Your customers are living with decisions it helped make.
You cannot yet tell whether the investment is working, or whether the systems are governed well enough to answer a regulator, a board, or a customer.
We are looking for pilot organizations.
METRIS is being built with a small number of organizations rather than for an imagined one. Pilot partners shape what gets measured, what a reading has to show to be useful, and what makes a finding worth acting on.
Who this is for
Organizations with AI already in real use, where someone in leadership is responsible for decisions about it and does not yet have a clear way to reason about readiness.
What it takes
One real AI use case. The evidence that already exists around it. Access to the people who work with the system and the people accountable for it. And honest reactions, including when a finding is wrong or does not matter.
What you get
A readiness baseline for that use case, and direct influence over an instrument while it is still being shaped.