Legalfly Webinar: The Bottleneck in AI Contract Review Is the Firm's Knowledge Assets, Not the AI Tool

A Legalfly webinar on AI contract review this week surfaced a finding that KM teams have known but struggled to articulate in terms that procurement and leadership hear: the performance ceiling in AI contract review is not the model — it is the quality and structure of the firm's underlying knowledge assets. Precedent libraries, playbooks, and clause libraries are the retrieval substrate that determines AI output quality. Firms with well-maintained, tagged, and current clause libraries receive materially better AI-assisted contract review outputs than firms whose playbooks are PDFs last updated in 2019. This reframes KM from a retrieval service into a data quality and curation layer that directly governs AI performance — and makes investment in KM infrastructure a direct line item in AI ROI models. For KM directors seeking budget justification for precedent curation, taxonomy work, or playbook modernisation, this causal link — clean knowledge equals better AI output equals measurable business value — is now a documented, platform-sourced argument.