1. Current state
Map how AI decisions are made today and where risk accumulates.
Set up the minimum governance and operating rhythm to deliver AI safely, repeatedly, and at speed.
Clear phases, short cycles, and documentation that your team can keep using after the engagement.
Available in workshop-led, hybrid, or async-first formats depending on leadership availability.
Map how AI decisions are made today and where risk accumulates.
Define roles, ownership, and how product, data, IT, and legal collaborate.
Introduce a small set of controls: classification, evaluation, monitoring, and audit trails.
Create repeatable artefacts: one-pagers, checklists, and decision logs.
Pilot the operating model on one initiative and adjust with feedback.
Confirm the model supports speed, accountability, and compliance expectations.
It should do the opposite. Good governance removes ambiguity, reduces rework, and speeds up decisions.
Yes—at a practical level: risk classification, documentation, evaluation, and accountability.
Yes. The model is adapted to your risk appetite, sector constraints, and delivery capability.
If this looks like the right fit, let's discuss your context and desired outcomes.