AI in Corporate Legal Operations and What It Means for You


Corporate legal departments have long worked against the perception that they function within the enterprise as a cumbersome cost center — as a department of “no” rather than as a strategic, value-added business partner. As far back as its 2001 annual meeting, the American Corporate Counsel Association (ACCA) held round-table discussions on the subject, focusing on both negative perceptions of corporate legal departments (such as lawyers are “risk-averse”, “don’t know the business” and “struggle to measure the benefit of preventing problems”), as well as possible solutions (like developing “value-added” campaigns, getting involved early, understanding business goals and aligning to support them). Nearly two decades have passed since the ACCA meeting, yet these issues persist. Rapid technological advancements, coupled with an evergreen mandate to become more efficient, have moved the needle and the debate has shifted in tone. We no longer talk about whether corporate legal departments will harness innovation to help drive efficiencies and add value — but when and how.

Recent survey data from different sources bear this out. In the Association of Corporate Counsel’s 2019 “Global Legal Department Benchmarking Report,” data collected from 508 legal departments across 30 countries shows that 53% of large departments (categorized as those with more than 100 staffers) are using legal tech solutions, with the top three being e-signature (44%), contract management (41%) and document management (38%).

Similarly, in its “2019 Future Ready Lawyer Survey,” global information services firm Wolters Kluwer found that emerging technology and its impacts loom large. Of the 700 U.S.- and U.K.-based survey respondents, which represented a cross-section of in-house counsel and attorneys in private practice, more than half expect to see “some impact from transformational technologies already here today,” including artificial intelligence, predictive analytics, machine learning, and big data.

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