All use cases

AI in Legal services

Faster first drafts. Sharper advice.

Law firms are uniquely well-placed to benefit from AI - precedent-rich, document-heavy, and full of work that's important but largely formulaic. The firms moving early are using AI to compress drafting time and reinvest the hours into higher-value advisory work.

Why modernise now

  • Clients are pushing back on hourly billing for routine work.
  • Trainees and associates are scarce; the work hasn't shrunk to match.
  • In-house teams are already using AI - external counsel needs to keep pace.

Where AI can help

First-pass drafting of NDAs, contracts, and standard letters.
Document review and clause extraction across large bundles.
AI-assisted legal research, grounded on firm-approved sources.
Matter summarisation and client update drafts.

How to think about AI in legal services

The use cases above are deliberately specific - real shapes of work, not generic promises. The pattern that runs through almost all of them is the same: AI absorbs the repetitive, document-heavy, or first-draft work, and a human keeps the final decision. That's the combination that tends to land well in UK SMBs, regardless of sector.

If you're trying to pick where to start, the right answer is rarely the most exciting use case. It's the one with the clearest baseline, the most willing owner, and the smallest blast radius if it doesn't work. Save the ambitious projects for pilot two or three, when you've built the muscle of finishing what you start.

Common starting points

Across the legal services businesses we speak to, the most common first pilots are the unglamorous ones - meeting notes, document summaries, drafting routine correspondence, triaging an inbox. They're not the use cases that make the keynote slides, but they're the ones that quietly compound week after week and build the confidence to try something bigger.

The mistake we see most often is jumping straight to a customer-facing AI before the internal one is working. Internal pilots are forgiving; customer-facing ones aren't. Get good at the former before you risk the latter.

What 'good' looks like at six months

A legal services business that's six months into a sensible AI rollout usually has two or three workflows running in production with measurable improvements, a one-page policy the team has actually read, a small group of confident internal champions, and a backlog of next pilots scoped well enough to start. None of that requires a big bang. It requires a small group of people doing the next sensible thing, on a regular cadence, for two quarters in a row.

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