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Generative AI in E-Discovery: Revolution or Sticker Shock?

The promising horizon of generative artificial intelligence has remained tantalizingly within reach for the legal community, with its profound implications in the domain of e-discovery. Yet, as the legal industry embraces and experiments with this cutting-edge technology, the recurring, daunting question remains: Is it truly worth the cost?

At the Relativity Fest 2023, an enlightening panel discussion themed, “Law Firms, Generative AI & The Future of E-Discovery,” witnessed eminent law firm professionals elucidating on their experiments with generative AI tools and the associated fiscal ramifications. Opinions were highlighted by a number of law firms, which are summarized below

Sidley Austin’s Stance: Economical Concerns Over Enthusiasm. Generative AI is undeniably transforming e-discovery, enhancing its precision and efficiency. But is the fiscal challenge too steep to surmount? Matt Jackson, overseeing data analytics and discovery at Sidley Austin, underlined the financial implications as a pivotal factor dictating the technology’s assimilation. Reflecting on the early adoption costs associated with TAR, Jackson observed, “any new technology is going to start at a higher price point.” Representing cost-conscious clientele, he asserted, “I can’t go to them and say, ‘I want to use this really nifty, cool tool, but it’s going to cost you more. That’s never going to fly.’”

Foley & Lardner’s Perspective: Eyes on the Future. Every technological acquisition is fundamentally an equation of costs against benefits. Michael Cichy, spearheading litigation support at Foley & Lardner, emphasized the prospective advantages of generative AI. He posited that leveraging AI would ultimately curtail client expenses by reallocating tasks traditionally handled by high-billed professionals. Adding to the merits, Cichy noted that the AI elucidates “why it thinks the document is responsive,” a clarity often absent in traditional review. This precocious detection can potentially diminish consequential costs linked to rectifying overlooked errors.

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Troutman Pepper Hamilton Sanders: Facing the “Generative AI Tax”. The economic landscape of e-discovery augmented by generative AI cannot be envisioned without scrutinizing pertinent court decisions. Jason Lichter of Troutman Pepper eMerge analogized the financial implications imposed by challenging counsels to the erstwhile “TAR tax.” Highlighting the need for judicial clarity, Lichter expressed, “We might need a judge to be the first to issue an opinion certifying that that generative AI is presumptively reasonable or defensible, under appropriate conditions.”

Quinn Emanuel Urquhart & Sullivan: A Waiting Game. As the fog around generative AI’s actual expenses persists, Melissa Dalziel from Quinn Emanuel Urquhart & Sullivan accentuated the embryonic stage of this tech integration. While cognizant of its potential superiority over TAR and human review, she candidly expressed, “We just don’t have the metrics to really be able to do that math.” Dalziel espoused continued exploration and emphasized collaborative learning among pioneers in the field.

As is evident from the above, while the entry of generative AI in the realm of e-discovery beckons a transformative era, a comprehensive cost-benefit analysis, backed by empirical data and conducive legal frameworks will be pivotal in determining its widespread acceptance.

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