What this is

Always current. Never finished. An editorial hub for technical executives writing, defending, or unwinding an AI strategy — staying at the cusp of AI development so you don't have to.

Operator-written briefs, frameworks, and tooling comparisons, reviewed and published by The AI Strategy Guide. Sourced, dated, and updated as the field moves — no retainers, no vendor sponsorships, no gated PDFs.

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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.

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Essay

AI Agent Security: The Runtime Tooling View of Prompt Injection, Data Exfil, and Output Trust

The operational read on AI agent security tooling in 2026 — the four threat categories that matter, the four procurement archetypes (runtime guardrails proxy, runtime monitoring, MLSecOps platform, OWASP-LLM assessment), where each named vendor sits in the pipeline, and the structural failure mode of treating these tools as a checkbox.

2026-05-30 · 15 min · T. Prommer
Essay

AI Brand Visibility Tools in 2026: The Honest Procurement Read

A practitioner's evaluation of the LLM brand-visibility tooling market — Profound, Otterly.AI, Peec AI, Goodie AI, AthenaHQ, Scrunch AI, Evertune, Daydream, Rankscale, Writesonic GEO, HubSpot AI Search Grader, Semrush AI Toolkit, Ahrefs Brand Radar, Surfer AI, Airops, Bluefish. Four archetypes, a four-criterion scoring rubric, and the consolidation prediction nobody in this market wants to hear.

2026-05-30 · 15 min · T. Prommer
Essay

AI Data Readiness: The Data Layer That Pre-Dates Your Strategy Approval

The four data-readiness checks no AI strategy survives without — inventory, classification, lineage, access controls — extended with the AI-specific surfaces classical data governance does not cover (training-data licensing, embedding-store provenance, prompt-context auditability), and the named-vendor read on Alation, Atlan, Collibra, Informatica, Databricks Unity Catalog, Snowflake Cortex, Select Star, Secoda, and Cloudera against an honest practitioner rubric.

2026-05-30 · 14 min · T. Prommer
Essay

AI Orchestration Frameworks in 2026: The Practitioner's Comparison

Framework-by-framework evaluation of the agentic AI orchestration landscape — LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, Haystack, Semantic Kernel, DSPy, Model Context Protocol, plus the model-vendor-native surfaces. Four criteria, named verdicts, and the honest answer to the question every engineering team asks: do I need a framework at all?

2026-05-30 · 14 min · T. Prommer
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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.

20Years CIO / CTO
68Briefs published
7Topic hubs

Readers ask first

What is an AI strategy, in one sentence?
A document that names which AI investments your organisation will make, in what order, with what success criteria, and what will get cut when the budget tightens. If it does not answer those four questions, it is not a strategy. It is a wish list with a cover page.
How is this different from a digital transformation strategy?
Digital transformation strategies tend to be about platforms and processes. AI strategies are about decisions you cannot yet make confidently: which capabilities to buy, which to build, which to govern, which to discontinue. The honesty about uncertainty is the difference. A digital strategy can be linear; an AI strategy has to be conditional.
Do we need a Chief AI Officer to write one?
No. You need someone accountable for the document who has actually run a programme. That can be a CTO, a CIO, a head of data, a fractional CAIO, or in a few cases the CEO. The title matters less than the experience. The named role I would avoid is 'AI Center of Excellence Lead' — Centers of Excellence default to the wrong incentive structure for this work.
How long should an AI strategy document be?
Twenty pages for the document itself, fifty for the appendix. The first three pages have to survive a non-technical board member reading them on a Sunday. If they cannot, you have written a research paper. The appendix is where the assumptions, the cost models, the failure-mode analysis, and the vendor evaluations live — read by two people, but the two people who matter.