AI programme management
AI programme management: from roadmap to delivery
Build an AI programme around business outcomes, clear ownership and production readiness. A practical guide to priorities, governance and delivery.
9 min read
AI programme management
Taking an AI project into production means making decisions about priorities, data, ownership and cost. These guides help you build a roadmap, evaluate outputs and clarify release decisions. Start with the programme-management guide, then work through the issue holding your initiative back.
Start with this guide
AI programme management
AI governance: assign responsibility before release
Make AI governance operational with clear decision rights, release gates and incident ownership. Use a charter that your team can apply to real work.
9 min read
AI programme management
AI project risk register: turn concerns into controls
Build an AI project risk register around failure scenarios, owners and tested controls. Use a worked example to review residual risk before release.
9 min read
AI programme management
AI roadmap prioritisation: choose what to build first
Prioritise an AI roadmap around evidence, dependencies and measurable value. Use a practical decision sheet to choose the next project with confidence.
9 min read
AI programme management
Evaluating AI output: a practical quality scorecard
Evaluate AI output with task-specific criteria, representative cases and independent review. Build a scorecard that informs a clear release decision.
8 min read
AI programme management
Human-in-the-loop workflows: design useful review
Design human-in-the-loop workflows with clear review tasks, source access and escalation. Measure quality and workload before scaling AI assistance.
8 min read
AI programme management
An AI business case decision-makers can evaluate
Build an AI business case with a measured baseline, alternatives, full costs and explicit assumptions. Give decision-makers evidence for the next commitment.
9 min read
AI programme management
AI production KPIs: measure outcomes and operating risk
Choose AI production KPIs that connect quality, adoption, cost and business outcomes. Define useful denominators, review rules and actions before release.
10 min read
AI programme management
From AI PoC to production: a readiness checklist
Move an AI proof of concept towards production with clear evidence, owners and recovery plans. Use a practical checklist to decide the next release.
9 min read