AI transformation

You cannot redesign work you have not diagnosed

Arist asks every employee where the new tools help and where they get in the way, then returns the answer by role and region.

Ask the people whose work is changing

The reason this is hard to measure is that the useful answer is qualitative and the available instruments are quantitative. A dashboard can count sessions. It cannot record that a team abandoned a tool because it produced work they could not defend to a customer, or that the biggest gain in the company is happening in one region nobody has asked about. That information exists, it is just held in people rather than in a system of record.

How it works

  1. 01

    Diagnose

    Interview the whole population by voice, not a sample of enthusiasts. Where the tools help, where they break, what people stopped using and why, and which workarounds have quietly become the process.

  2. 02

    Recommend

    Findings come back by role, region and function, separating the places a capability gap is the problem from the places the tool, the policy or the process is the problem.

  3. 03

    Fix

    The fix goes to the cohorts that need it, in the channels they already use, and the same question is asked again to confirm the change held.

Arist makes it remarkably easy to build high-quality learning in a short amount of time, without sacrificing depth or impact. Their needs analysis agent has also been incredibly valuable, providing fast, clear insights that help us focus on our biggest knowledge, skill, and competency gaps.
Brent BernierVP, Talent & Organization, MAPFRE

What you get

  • Usage data, and the reason behind it

    The tools’ own telemetry sits beside what people say, so you see why a team stopped using something rather than only that usage fell.

  • A defensible baseline

    Each finding carries what it is costing and how many interviews raised it, so the next AI investment is argued from evidence rather than belief.

  • Where the transformation is stuck

    The impact map puts every blocker on one surface by scale and confidence, so effort goes to the gap that matters rather than the one that is loudest.

AI transformation

Start from what your people actually do.

Bring us the transformation you are trying to justify, and we will tell you where it stands.