Gaining Insights on AI Measurement Strategies from APAC Legal Professionals

Relativity’s Phoebe Cantell reports on how Asia Pacific legal departments have moved from curiosity about generative artificial intelligence to practical adoption. At a recent NextGen GC Summit in Sydney, APAC legal department leaders discussed their company’s journey from pilot projects to full integration, emphasizing the use of AI measurement strategies.

The panel, led by Ryan Doherty of Relativity, offered perspectives that revealed a range in AI maturity. Evana Diep of software provider Boomi described her company’s approach: “Earlier this year, our CEO directed that every department needed to incorporate AI in their internal processes and made it a KPI for every single leader.”

Nevertheless, only 55 percent of APAC legal teams are comfortable using AI in eDiscovery, well below global averages. This reflects caution, not disinterest, as legal teams work through approval and risk processes.

Panelists stressed that AI’s value extends beyond cost savings. Low-risk, high-impact applications have emerged as early wins. They include AI-powered reviews of non-disclosure agreements, reducing hours of work to minutes, automating meeting transcription with instant action plans, and invoice processing systems that streamline workflows. 

A practical framework for measuring AI’s value was outlined by Katrina Gowan of CLOC Australia. Instead of relying on abstract metrics, Gowan recommended identifying repetitive tasks, tracking how often they are performed, and measuring the time each requires. Establishing this baseline allows teams to demonstrate measurable gains once AI tools are in place. 

Marty Gardner from supermarket chain Woolworths underscored the need for legal teams to weigh accuracy against efficiency. Gardner said that while AI can deliver greater precision, the real challenge is knowing when “good enough” is better than chasing perfection at the cost of delays.

The panelists noted that success in AI adoption will depend on starting with low-risk use cases and building organizational capability over time. Frameworks that include AI measurement strategies will be essential.