General information only; not legal advice. Align with the CPR and current Practice Directions applicable to your matter.

Disclosure workloads are exploding. AI can help triage, cluster and summarise—with solicitor oversight and a clear audit trail. This playbook keeps your approach defensible and your team productive.

Where AI helps (and where it doesn’t)

• De‑duplication & near‑duplicate detection to cut volume.
• Clustering by issue/custodian to focus reviewers.
• Prioritised queues based on keywords, metadata and learned relevance.
• Suggested summaries & timelines that humans verify before use.
• It does not replace legal judgement or privilege calls.

Defensibility under the rules

Document your method in a short strategy note: scope, tools, QC sampling plan, escalation path, and who signs off. Keep recall/precision metrics, sampling results and change logs. If the court asks, you can explain what you did and why.

Quality control that stands up

• Conduct QC sampling on each batch; record acceptance thresholds.
• Track reviewer decisions and queries; resolve disagreements promptly.
• Treat privilege and redaction as separate, audited steps with clear instructions.

Costs & budgeting

AI can reduce time on repetitive tasks, but supervision time remains. Record the delta (before/after) and keep notes for costs management hearings. Use the evidence to refine future budgets.

Implementation tips

• Restrict browsing and imports to approved sources.
• Use legal holds and immutable audit logs.
• Run a small pilot first; publish what worked and what didn’t.

Further reading & internal links

• Accuracy & verification → /blog/hallucinations-legal-ai (when live)
• Evaluation metrics → /blog/llm-evaluation-law (when live)
• Contract analytics crossover → /blog/ai-due-diligence (when live)

FAQ

Is TAR still relevant?
Yes. TAR and LLM‑assisted review can complement each other. Use what is defensible and efficient for the case.