AI Operating Model & Authority Design
Define who owns AI, how it operates and what humans and agents are allowed to decide.
Design the organisational structure, lifecycle ownership, decision rights and governance model required to move AI from individual experimentation into accountable operation.
The problem
Human in the loop is not an operating model.
Organisations need explicit answers about who owns AI use cases, who approves changes, what is centralised or federated, how exceptions work, where professional judgement remains mandatory and what authority an agent may exercise.
Scope
Scope.
- AI ownership and accountability
- Centralised and federated responsibilities
- CoE and business-unit responsibilities
- Use-case lifecycle ownership
- Human and agent decision rights
- Approval and escalation paths
- Exception authority
- Evidence and audit responsibilities
- Operating cadence and governance forums
Outputs
Deliverables.
- Target AI operating model
- Role and accountability architecture
- Human and agent authority matrix
- Lifecycle ownership map
- Governance forums and decision routes
- Exception and escalation model
- Operating controls and evidence responsibilities
- Transition plan
Outcome
What the work is designed to make possible.
A usable operating model that can be embedded into real workflows, technology and governance rather than remaining an organisation chart or policy document.
Related routes
Continue from the operating problem.
AI initiatives should earn the right to scale.
Start from the evidence, authority and operating conditions around the work rather than from a preferred tool.