What did your board ask you to do this quarter?
Each lane is the long version of a real conversation with a CTO or CAIO this year — the framework for the strategy ask, the role-scope for the hire, the audit playbook for governance, the discipline shift for engineering, and the tooling shortlist for capabilities. Pick the brief that matches your Q.
Write us an AI strategy.
Frameworks, roadmap, maturity. What goes in the document, what goes in the appendix, what gets cut — and what survives a Q3 board review.
02 · LEADERSHIPHire a CAIO.
Role scope, comp benchmarks, the 90-day plan. Seven questions for every shortlisted candidate, and the reporting lines that hold.
03 · GOVERNANCEAudit our AI governance.
EU AI Act, NIST AI RMF, tooling. The clause template two SaaS renewals failed without, and the CISO-versus-DPO boundary resolved.
04 · ENGINEERINGModernise software engineering.
Code review, testing, platform, maintenance. What changes about how engineering runs once half the code is AI-generated.
05 · CAPABILITIESPick AI capabilities & tooling.
AI-SRE, agents, orchestration, observability. The procurement frame no vendor will draw for you, and the tools that earn their licence.
— · BROWSENone of these match?
Open the full library of 79 briefs across 7 hubs. The most-asked board questions drive the lanes; the rest live one click in.
Latest research
All hubs →Communities of Practice for AI: An Operating Model
A shared channel is not a community of practice, and the difference is why most AI adoption programmes stall after the launch email. The operating model that actually spreads proficiency: the four roles, the prompt library as a governed asset, the weekly rituals, the seeding discipline, and how to federate from one team to the whole org without centralising it to death.
EssayMeasuring AI Adoption: A Leading and Lagging Indicator Set
Most AI adoption programmes are cancelled one quarter before they would have worked, because the board asked for lagging numbers that never move that fast and nobody was tracking the leading ones that do. The full indicator set, where each metric actually comes from, how to avoid the vanity-metric trap, and the reporting cadence that buys a slow-moving programme the time it needs to pay off.
EssayHow to Ring-Fence AI Learning Time Without Killing Delivery
Every manager agrees people need time to build AI proficiency, and every manager quietly reallocates that time the moment a sprint slips. The reason protected learning time collapses, the capacity maths that shows it costs less than the non-adoption it prevents, and the concrete mechanics of defending an hour a week so delivery survives and the habit actually forms.
EssayAI Sovereignty: Owning the Value Your Data Creates
Sovereignty is not a compliance topic; it is an economic one. It is your ownership of the value your data and knowhow create when a model touches them, and most boards are handing it away by treating a sovereignty decision as a procurement one. The mechanism, the four layers where ownership is won or lost, and the postures a board can actually choose between.
The hubs
- C1 →
Frameworks
Six widely-cited AI strategy frameworks scored against eight criteria — McKinsey, Microsoft CAF, Gartner, Databricks, IBM watsonx, and the operator-built four-question diagnostic. Honest about what each gets wrong.
- C2 →
Roadmap
Once an AI strategy exists, the question becomes the order in which to do the work. The roadmap cluster covers the discretionary-to-operating-budget transition, the six- and eighteen-month horizons, mid-programme pivots, and the difference between an AI transformation and an AI strategy with a louder cover sheet.
- C3 →
Maturity
Six AI maturity models — Gartner, Microsoft CAF, MITRE, CNA, Deloitte, and an operator-built version — plotted against one set of axes. Target maturity stage is conditional on strategic posture, not absolute.
- C4 →
Governance
What enterprise AI governance actually requires in 2026 — the EU AI Act August deadline, the NIST/ISO alphabet soup, the 35-tool platform market, and the CAIO/CISO/DPO boundary that breaks most programmes. Written by someone who has run the programmes, not audited them.
- C5 →
Roles
Should you hire a Chief AI Officer? Where does the role sit, what does the first 90 days look like, and where is the CAIO ↔ CTO ↔ CIO boundary. Written for executives deciding the org-chart question, not selling the search.
- C6 →
Capabilities
The serious AI coding tools market has compressed to four enterprise contenders, two emerging agents, and a handful of IDE plays. The strategic question is not which is best — it is who decides, what is actually being procured, and what the licence-versus-API split does to the budget twelve months in. Written for the VPE, the CIO, and the platform lead who will own the consequences.
- C7 →
Software Eng
What AI is doing to software engineering as a discipline, not a procurement line: the code review, testing, maintenance, and platform shifts a VP owns.
Editor & principal author
Tom Prommer
The AI Strategy Guide is edited by Tom Prommer — twenty years as CIO and CTO, with AI programs run and audited across European media and technology groups. Briefs are operator-written and editorially reviewed before they publish, so the opinion is foregrounded and the trade-offs are named, not buried. Prommer was named HotTopics Global CIO 2026.