Sikich: The Right AI Rollout for a Law Firm Is a Sequencing Problem, Not a Training Problem

Sikich's July 2026 analysis of law firm AI implementation articulated a rollout model specifically validated by Macfarlanes' deployment of Harvey: practice area by practice area, until 80% of lawyers are on the platform regularly — with use cases identified by "experimenters" on non-billable time, standardised by a Centre of Excellence, and delivered via the AI capabilities already embedded in existing software before adding new tools. The key structural insight: "Most mid-market firms should start with the AI capabilities already embedded in their existing stack before adding new tools. For example, start with Microsoft Copilot in Dynamics 365, expand into the AI capabilities built into the practice management platform, and add specialised tools where additional depth is needed." The billable hour conflict is addressed directly: if AI enables a partner to complete work in 30 minutes that previously took 5 billable hours, and the answer is "less" compensation, the behaviour will not recur — which is why use case discovery should stay on non-billable time until the pricing model conversation is resolved. For COOs and innovation leads, the Centre of Excellence model — owning vendor evaluation, prompt standardisation, training, and governance — is the organisational answer to AI adoption that stalls after the procurement phase.