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Artificial Intelligence

Practical AI: where it helps, and where it doesn't

A grounded framework for choosing AI projects that solve real problems instead of chasing trends.

Sep 28, 2026 · 6 min read · Sample article

Every business is being told it needs AI. Far fewer are told which problems AI is actually good at solving. Starting with the technology rather than the problem is the most common reason AI initiatives stall.

Start with repetitive judgement

The best early candidates are tasks that require light judgement, happen often and follow recognisable patterns: classifying requests, drafting replies, extracting fields from documents, summarising long threads.

Keep humans where stakes are high

AI is excellent at producing a strong first draft. For decisions with financial, legal or reputational consequences, design for review and approval rather than full autonomy.

Measure before you scale

Collect real examples, define what a good result looks like and test against them. A small, well-evaluated pilot is worth more than a large, unmeasured rollout.

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