Methodology
Strategy model linking business objectives to AI opportunities, a prioritised portfolio, operating model and value case.
Components
AI vision & objectives; Opportunity mapping; Use-case portfolio; Value case & prioritisation; Operating model; Roadmap & funding.
Governance
Executive/board own AI strategy; AI leadership executes; finance validates value. L1 Initial L2 Developing L3 Defined L4 Managed L5 Optimised Ad hoc Basic, siloed Standardised & Quantified & integrated Predictive & embedded governed
Maturity levels
Implementation roadmap
Diagnose (assess maturity) → Design (tailor framework & governance) → Build (policies, standards, controls, pipelines) → Embed (training, culture, adoption) → Assure (test, benchmark, re-score).
Deliverables
Framework document, governance & RACI, policy/standard templates, maturity score & roadmap, board reporting pack.
Advisory opportunities
AI strategy definition; Use-case portfolio; Value-case build.
Across the Data & AI ecosystem
Knowledge graph · 6 relations