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Resources

Tools, frameworks and straight answers

Free, practical material from our consulting practice — the same frameworks we use with clients, plus honest answers to the questions leadership teams ask us most.

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Take the frameworks with you

PDF

The AIX AI Roadmap

A phase-by-phase roadmap for building AI capability — readiness through pilots to scaled adoption, with governance gates and value checkpoints. 6 pages, board-ready.

Download the roadmap ↓
PDF

AI & Business Transformation Playbook

Principles, pitfalls and practices across strategy, governance, data foundations, process redesign, change and delivery. The companion guide to the roadmap.

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FAQs

The questions leaders actually ask

How do we know if we're ready for AI?
Readiness isn't binary — it's a profile across six dimensions: strategy clarity, data foundations, technology, skills, governance and culture. Our readiness assessment baselines each one and shows exactly where to invest first. Most organisations are more ready in some areas than they think, and less in others.
We've run pilots but nothing scales. Why?
Almost always one of four causes: pilots chosen for novelty rather than value; data foundations that don't survive production; no operating-model home for the solution; or adoption treated as an afterthought. We diagnose which apply, fix the foundations and industrialise what deserves to scale.
How long before we see value?
With well-chosen use cases, first measurable value typically lands in the Prove Value phase — early in the programme. We deliberately front-load quick, credible wins because they fund confidence for the harder, higher-value work that follows.
What does an engagement typically cost?
It depends on scope, but we always start small: a discovery and strategy phase is a fixed-fee, fixed-duration engagement with a board-ready roadmap as the output. You'll know the full-programme investment before committing to it — that's the point of the roadmap.
Are you tied to any technology vendors?
No. We hold no reseller agreements and take no commissions. Tooling recommendations are made after strategy and requirements are clear, judged solely on fit, cost and risk for your context.
How do you handle AI risk and regulation?
Governance is a workstream from day one — decision rights, model risk management, ethics principles and regulatory alignment (UK GDPR, and the EU AI Act where it applies). Our philosophy is proportionate governance: enough control to move fast safely, never bureaucracy for its own sake.
Will our people be replaced by AI?
The programmes that succeed redesign work around people, not away from them. In practice, value comes overwhelmingly from removing drudgery, speeding decisions and improving quality — and every roadmap includes reskilling so your people grow with the capability.
What happens when the engagement ends?
You keep the capability. Skills transfer is designed into delivery — champion networks, role-based training, documented playbooks — so improvement continues without us. Dependence on consultants is a design flaw, and we treat it as one.
Insights

Thinking worth your time

Perspective

Why most AI strategies are just shopping lists

A strategy chooses. If your AI plan doesn't say what you won't do, it isn't a strategy — it's a procurement queue. How to tell the difference, and how to fix it.

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Perspective

The pilot graveyard: four reasons AI never scales

Novelty-driven selection, brittle data, no operational home, forgotten humans. The autopsy of a hundred stalled pilots — and the discipline that prevents them.

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Perspective

Governance that speeds you up

Done right, AI governance is an accelerator: clear decision rights mean faster approvals, not slower ones. The proportionate-governance model we build with clients.

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