Legal & Professional Services

Document review volume keeps climbing as matters span more data sources — email, Slack, Teams, cloud drives, mobile — and courts expect defensible process under the Federal Rules and the Sedona Principles. Thomson Reuters research found that 77 percent of legal professionals expect AI to significantly change their work within five years, yet most e-discovery workflows still rely on keyword culling and linear review because TAR 2.0 and continuous active learning models were never tuned to the firm's matter types and privilege protocols.

Research time is expensive when associates repeat the same foundation work across offices, or when key precedent lives in internal memos buried in iManage or NetDocuments that search tools never surface uniformly. Clients notice when answers arrive late or when two teams give slightly different reads on the same issue — and ABA ethics opinions on AI are raising the bar for verification and supervisory responsibility over AI-assisted work product.

Contract management spans drafting, redlining, negotiation, obligation tracking, and renewal — yet many firms still rely on shared drives and email threads for obligations that should be structured data inside a CLM like Ironclad, Icertis, or Agiloft. In-house legal teams face the same gap: thousands of active contracts with renewal dates, termination rights, and compliance obligations that no one tracks systematically.

Billing accuracy matters as much as utilization. Write-downs often trace back to unclear narratives, misaligned UTBMS task codes, LEDES formatting errors, or time spent reconstructing what actually happened on a matter. Outside counsel guidelines from corporate clients are getting stricter, and AI-assisted billing review on the client side means sloppy entries get flagged automatically.