This commentary on the JSIS Special Issue on datification focuses on two key themes selected from among the many topics discussed by Special Issue authors: 1) the debate over algorithmic intelligence versus human intelligence, and 2) the consequences of strategic performance systems. The current algorithmic versus human intelligence debate echoes earlier discussions in our field about whether expert systems should replace or support human experts. As appealing as it is to assume that algorithms support expert workers, research suggests that people are not very effective at monitoring and overriding automation. In addition, post-automation work tends to evolve toward lower human knowledge and skill. These observations should caution datification researchers against simplistic theories and should guide researchers to study the multilevel sociotechnical conditions and stakeholders involved in the design, use, and consequences of algorithms in organizations. Strategic performance measurement and ranking systems are also not new, but what is new is the belief that they will not just inform, but also transform, human behavior. In this respect, performance systems resemble the career tournaments that promote intense competition and create great inequality in executive pay and promotion. In addition, performance systems increasing serve as infrastructures, operating at multiple levels of analysis simultaneously. These observations imply that designing and studying such systems involve ethical choices, intensifying the demands on datification researchers.