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77 I L T A N E T . O R G Introduction The legal landscape is undergoing an extraordinary technological revolution. Artificial Intelligence ("A.I.") software can now update research, automate workflows, predict case outcomes, and even prepare drafts of pleadings and briefs – in a small fraction of the time it would take a human attorney to do the same. And in the time it takes to make a cup of coffee, data analytics applications can now analyze and interpret vast amounts of previously inaccessible, largely unstructured legal data (both internal firm data, as well as external court data) – enabling attorneys to anticipate the inclinations of their adversaries, the predispositions of their judges, and the likely amount of billable hours necessary to achieve a successful resolution of a matter. What is driving the rise of A.I. and Data Analytics? Where did these tools come from, and what do they do? And are robots really coming for lawyers' jobs? These questions, and more, are answered below. The Drive Towards Quality, Efficiency, and Predictability While lawyers of decades past could essentially name their price for legal work, it is the legal clients who now sit firmly in the driver's seat. Legal clients are more sophisticated, more savvy, and more innovative than ever before. While they still expect top-notch counsel and guidance, the highest quality work, and the best possible results, today's clients also seek greater efficiency from their outside counsel. And now more than ever, they seek greater predictability in fees, costs, and outcomes. These client expectations, coupled with extraordinary advances in technology, are driving the technological revolution we see today. The law firms who have learned to thrive in this new legal environment have heavily invested in technology and innovation. They have found a path to quality and efficiency – doing more with less – by using artificial intelligence and automation to handle the rote (but otherwise billable) aspects of a lawyer's day, freeing up the lawyers' time for the more strategic, bespoke aspects of their practice. And they have found the secret to providing greater predictability is to rely on data analytics – using past data to anticipate the future. The Transformation of Law: The Rise of A.I. and Data Analytics The A.I. revolution began with the imaginations of science- fiction writers and movie makers alike. However, by the turn of the mid-20th century, British mathematician and logician Alan Turing had introduced to the world the concept that machines, like humans, could use information input to solve problems and make decisions. 1 Today, he is known as a founding father of A.I. Turing's contributions to the field have had long-lasting substantial impacts on the areas of law, finance, medicine, and others, in ways even he could have never envisioned. Building on Turing's theories, in 1955, Allen Newell, Cliff Shaw, and Herbert Simon created the Logic Theorist. 2 It was the first A.I. program of its kind, and it became a landmark design in the area of machine-driven problem solving. The objective was simple – create a series of inputs from which the program could mirror the problem-solving skills of humans. The execution, on the other hand, was not so simple when working within the confines of then-available technology, and limits in computer processing power. Although largely unappreciated for its time, the Logic Theorist program demonstrated that Turing's theory of A.I. problem solving was in fact a reality. 3 By the 1980s, "expert systems" were introduced, which mimicked human decision-making processes on levels previously unseen, albeit still limited by computer speed and storage space. 4

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