Data analytics are quickly transforming law, challenging its survival as a vibrant profession for natural persons. I argue that data analytics will continue to penetrate law, even in domains heretofore dominated by human decision-makers. I demonstrate this claim by describing how machine-learning techniques can be used to identify important fiduciary waivers. Notwithstanding their transformative power, however, I remain doubtful that data analytics will substantially displace law. The most powerful approaches in data analytics as applied to law require human practitioner inputs to train, calibrate, and supervise machine classifiers. Moreover, law's normative/prescriptive commitments are irreducibly dynamic and complex – traits poorly matched to algorithmic prediction.