Why law firms need a different kind of AI audit
A generic AI readiness review doesn't hold up against what a law firm actually has to protect. Firms carry obligations most businesses don't: SRA Standards and Regulations on competence and client care, a duty of confidentiality that survives long after a matter closes, and privilege — a protection that can be permanently and irreversibly waived if the wrong material ends up in the wrong system.
AI-assisted drafting and document review tools raise all three at once. A tool that sends matter documents to a third-party model provider, retains prompts for training, or lacks a clear data-processing basis can create a confidentiality or GDPR problem well before anyone notices a quality issue in the output. And the output itself carries its own risk: AI-assisted drafting that hallucinates a case citation or misstates a point of law is now a well-documented professional risk, not a hypothetical one.
An audit built for a firm has to treat compliance, confidentiality, and output reliability as one connected question — not three separate reports from three separate vendors.
What the audit covers
Where AI is worth the risk
Which practice areas and workflows genuinely benefit from AI assistance, ranked against the risk each one carries — drafting support is not the same risk class as client-facing advice generation.
Where matter data actually goes
How client and matter data flows through any AI tool in use or under consideration — retention, training use, subprocessors, and where privilege could be put at risk.
What's already in the building
An honest inventory of AI tools already in use across the firm — including the ones IT doesn't know about — and whether they meet the bar the firm needs them to.
Whether the drafting can be trusted
For firms already using AI-assisted drafting or research tools, evidence-based testing of failure modes — fabricated citations, misstated authority, and where human review is (and isn't) actually happening.
Who signs off, and on what basis
Whether there's a named owner, a documented policy, and a decision trail that would hold up to a regulator, an insurer, or a client asking how the firm is managing this.
Mapped to real obligations
Findings mapped explicitly to the SRA Standards and Regulations and UK GDPR requirements that apply — not a generic compliance checklist bolted on afterwards.
This is an operational and technical audit, not legal advice — findings on regulatory alignment are there to inform the firm's own compliance and risk decisions, not to replace them.
How we work
- Fit check. A short, free conversation to establish whether an audit is the right next step, and roughly what it would need to cover. No cost, no obligation.
- Scoped audit. Once fit is confirmed, the scope, inputs, exclusions, and price are agreed and locked in writing before any work starts — a fixed price, quoted after the fit check, not billed by the hour.
- Report. A written, evidence-backed report: findings, risk ranking, and a prioritised action plan the firm can act on directly, plus one factual-correction round within the agreed window.
- Optional build. If the audit surfaces something worth fixing or building — a policy, a workflow, a tool integration — that's a separate, explicitly scoped engagement. The audit's findings are never used to upsell a foregone conclusion.
Who this is for
Firms already using AI-assisted drafting or research tools and wanting an independent check on where the risk actually sits; firms deciding whether to adopt AI tooling and needing an evidence-backed view before committing budget or partner sign-off; and firms that need a documented answer for a client, insurer, or regulator asking how AI use is being managed.