Service 02 · AI Policies and Operational Model
AI Policies and Operational Model
Every AI initiative should run inside a frame your board chose: the governance team, its policies and operating model, and the appetite, thresholds and forbidden zones your board sets.
Why it matters
AI regulation now shapes the operating environment in every sector. Governance designed early and kept proportionate lets you put AI into real decisions and scale it with confidence, within the policies your board set and the regulations that apply.
What I do
Governance team and roles
Who decides, who reviews, who can override, and who is accountable, named before the first AI initiative needs them.
Policies and operating model
Policies fit to your risk appetite and to the AI regulations that apply to you, and an operating model light enough to use, strong enough to trust.
Appetite, thresholds, and forbidden zones
The value appetite your board will fund, the trust thresholds it will accept, and the zones no AI initiative may enter.
Decision rights
What may be delegated to AI, set at enterprise level and adapted per use case, because use cases carry different risk profiles and different owning teams.
What you get
- An AI governance team with named roles and decision rights
- Policies and an operating model sized to your organization and mapped to the AI regulations that apply to you
- A written AI strategy and policy frame: value appetite, trust thresholds, forbidden zones
Who it’s for: organisations putting AI into real decisions, in regulated or public-sector settings.
From the frame to assurance
The frame is where governance starts. Assurance of each AI use case inside it, from evidence to an audit-grade record, is the work of TWAF Tower, the platform built on the Two Wings AI Framework.