There have recently been dramatic increases in the technical capabilities of artificial intelligence (AI). 1 For example, in February 2016, Google’s DeepMind used its AI to beat Korean Go master Lee Se-dol, 2 and in January 2017, an AI system called DeepStack beat humans at the complex poker game Texas Hold ‘Em. 3 The Electronic Frontier Foundation (EFF) has tracked the rapid progress of AI in performing tasks at human-like levels of capability in domains including voice recognition, translation, visual image recognition and others. 4 These advancements have led to both excitement about the capability of new technology to boost economic growth and concern about the fate of human workers in a world in which computer algorithms can perform many of the functions that a human can (eg, Frey and Osborne 2013, Furman 2016a).

Indicative of this excitement and interest in the area, recent academic research, using national-level data on worldwide robotics shipments, suggests that robotics may have been responsible for about one-tenth of the increase in the gross domestic product (GDP) between 1993 and 2007 (Graetz and Michaels 2015). Moreover, according to the 2016 Economic Report of the President, worldwide demand for robotics has nearly doubled between 2010 and 2014, and the number and share of robotics-oriented patents have also increased (CEA 2016). Thus, robots may now be contributing even more to GDP growth than in the past. However, even as these technologies may be contributing to GDP growth at a national level, we lack an understanding about how and when they contribute to firm-level productivity, what conditions they complement or substitute for labor, how they affect new firm formation, and how they shape regional economies. We lack an understanding of these issues because, to date, there is a lack of firm-level data on the use of robotics and AI. Such data will be important to collect to answer these questions and to inform policymakers about the role of these new technologies in our economy and society.