The Regulated AI Operating Model
Five volumes for CIOs, CTOs, CROs, and boards in regulated finance who need to run AI agents safely and accountably at scale — and still answer the regulator's question.
99%
of firms plan AI agents
11%
ship them safely
95%
of those had an incident
The argument
Every regulated financial institution is having the same two conversations. We need to move faster on AI agents. And, in the next breath: we had an incident — can we produce the log the regulator wants? These are not two conversations. They are one, and the gap between them is an operating-model problem, not a technology one.
This series does not ask which model to buy or which vendor to sign. It answers the operating-model question: what your organisation must look like, operationally, to deploy AI agents in an environment answerable to a regulator, a board, and customers who trust you with their money and their data.
The five volumes
Vol V — Building and Shipping
Extending the SDLC, data governance, and change control you already run — plus the 18-month roadmap and the playbook by institution size.
For: Heads of Engineering, Programme Directors
Currently available on amazon.fr; further marketplaces to follow.
You do not need to read all five. You need the volume that speaks to the conversation you are in — the who-reads-what map at the front of each volume tells you which.
The authors
Written by two practitioners, peer-to-peer, not consultant-to-client.
Marcio Parente has built cloud and AI platforms in Swiss and European regulated finance since 2004. Roberto Barbosa is Head of AI Engineering at a major Gulf bank. No aspirational frameworks. No vendor pitches. What we have found that works, at the level of detail operating institutions require.
Start with the conversation you are in.
All five volumes are available on Amazon. Reviews are welcome — they are how books like this get found.