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As the legal industry gradually integrates artificial intelligence (AI) into its practice, the underlying technology continues to advance at a fever pitch. Machine learning platforms arguably represent the pinnacle of AI development, and this technology currently augments and replicates intelligent human tasks in ways never before conceived. The business applications of machine learning are bearing fruit across a spectrum of industries and professions. Yet despite machine learning’s demonstrated promise, its forays into the legal industry have been uneven. In fact, the most advanced forms of machine learning have been relegated primarily to lower-level attorney tasks such as e-discovery, due-diligence, and legal research and, unfortunately, have yet to be embraced by the upper echelon legal decision-makers and strategists. This article explores this technology’s underutilization in law and highlights the inroads made by machine learning in other professions such as healthcare. It then provides an illustration of the capacity of machine learning and develops detailed hypotheticals of machine learning’s potential impact upon several representative areas of high-level legal decision-making, including lateral hiring, litigation strategy development, cost optimization, and overall law firm management. Finally, this article argues that incorporating machine learning will enable firms to permanently capture attorney expertise and develop deep reservoirs of reputational capital as a source of enduring competitive advantage.

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