Solutions
AI operating model
Turn governance into execution: approved rules applied to how each AI use is bought, built and approved, with every step leaving evidence.
The problem
The policy exists in a document but has not changed how things are bought, built or approved. Roles are defined on paper and each area handles it its own way.
How we intervene
We design how AI decisions are made and recorded in everyday work: approval workflows, control points in the procurement and development cycle, roles, and the evidence each step produces.
How the work unfolds
- Survey of how AI uses are approved today, who decides and what gets recorded.
- Design of the decision model and approval workflows.
- Integration of control points into the procurement and development cycle.
- Accompanied roll-out and verification of the evidence the controls produce.
Every project runs on the AGORA Delivery Framework —Qualify, Discover, Design, Deliver and Sustain—, which defines how the work is carried out. It is distinct from the commercial journey, which describes what can be engaged. See the methodology →
Deliverables
- A decision model and approval workflows for new AI uses.
- Control points embedded in the procurement and development cycle, each with an owner.
- Defined evidence produced by each control and where it is recorded.
- A review cadence and reporting to leadership.
Client participation
The organisation assigns the roles and adapts its processes. AGORA designs the model, accompanies the roll-out and verifies that controls produce the agreed evidence.
Where it fits in the commercial journey
- OperationalizeTurn governance into organizational execution.
The commercial journey describes what can be engaged. No organisation needs all four stages.
Next step
Let's talk about how AI decisions are made in your organisation today.
Sector references correspond to the professional trajectory of the firm's members, not to AGORA Advisory contracts.
Other solutions
AI readiness and strategy
Bring order to the AI initiatives that already exist and turn them into a prioritisation leadership can defend, before committing resources to pilots that never scale.
Data and operations
Make sure the data AI needs is available, owned and reliable, and that the processes using it are defined end to end.
Governance and risk
Build the AI governance model the organisation can sustain and demonstrate: policy, inventory, risk classification, roles and evidence proportional to its context.