The challenge
A typical situation: the organization hears about agents from every direction, but no one inside can say where to start. There are dozens of proposals from different teams, and no shared way to assess which would bring the most value relative to risk and build effort. The danger is that the first agent gets chosen by who shouts the loudest, not by what is actually worth doing.
How the solution is built
The proposed use cases are reviewed together with the business and IT, and each is assessed through three things: how much time it would save or how many errors it would reduce, how sensitive the data it would handle is, and how complex it would be to build within the governance model. The result is a prioritized roadmap, not just a list of ideas.
At the same time the organization’s readiness is mapped: which data is in shape as a foundation for an agent and which needs cleaning first, in the same way as when building an AI-ready intranet. This prevents the first agent from being built on poor data and failing for that reason.
What the solution aims for
The organization gets a concrete, prioritized order of progression for its first agents instead of picking the first idea that comes along. The first agent to be built rests on assessed value, not guesswork.
