AI strategy framework — a six-step model for executive teams

Step 1 & 2 — Baseline and portfolio

Quantify AI readiness across nine dimensions and benchmark against industry leaders. Then convert candidate use cases into a scored portfolio: value, complexity, data readiness, EU AI Act risk tier.

Step 3 & 4 — Data foundations and governance

Map every prioritized use case to the data products it requires (Bronze, Silver, Gold tiers) and to the canonical controls that govern it. Data and governance investments are sequenced so they unlock the next wave of use cases.

Step 5 & 6 — Operating model and value tracking

Define roles, decision rights and ownership for data products, use cases and agents. Track value realization per wave so the board sees outcomes, not activity.

Frequently asked questions

What should an AI strategy framework include?

A working AI strategy framework covers six steps: maturity baseline, prioritized use case portfolio, data foundations, governance, operating model and value tracking. AI-Koutsi ships all six and ties them together with shared lineage.

How is this different from McKinsey or BCG AI strategy work?

Traditional consulting delivers a static deliverable in 3–6 months. AI-Koutsi delivers the same six artifacts as a living portfolio model in 4 weeks — your team owns the data and outputs, and the strategy updates as the portfolio evolves.

Does the framework include EU AI Act and ISO 42001 alignment?

Yes. The governance step ships with a canonical control library that maps EU AI Act articles, NIST AI RMF functions and ISO 42001 clauses to each prioritized use case automatically.