AI Strategy

AI strategy defines how a business identifies, evaluates, and acts on artificial intelligence opportunities. In the UK, 80% of businesses are neither using nor planning to adopt AI (GOV.UK, February 2026), and 56% of CEOs report no measurable ROI from their AI investments. The gap is rarely a technology problem. It is a strategy problem: unclear objectives, missing governance, and no structured approach to vendor selection, budgeting, or compliance.

These guides cover the strategic decisions UK business leaders face when evaluating AI, from readiness assessment and business case development to regulatory compliance and build-versus-buy trade-offs.

Strategy matters because AI spending without a strategy tends to produce pilots that never reach production. A clear strategy does four things: it ties each AI initiative to a measurable commercial outcome rather than to the technology itself, it sets the governance and data-handling posture before tools are bought, it establishes how the business will choose between building and buying, and it sequences investment so early wins fund later ones. For UK businesses there is a specific compliance dimension to get right early, including UK GDPR, the EU AI Act where there is EU exposure, and sector regulation such as the FCA Consumer Duty in financial services.

These guides are written for commercially literate decision-makers who already understand the basics and want to make defensible choices. They cover readiness assessment, business case development, vendor due diligence, budgeting, build-versus-buy, and the UK regulatory perimeter, with the trade-offs made explicit rather than glossed over.

Where to start

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