Widespread disruption to the language industry from artificial intelligence (AI) such as machine translation (MT) has been predicted for many years, but now that these technologies are being deployed, the effects are varied and, at times, unexpected. Neural MT, in particular, can produce output of greater quality compared to previous MT paradigms, but not without errors, and the best way to interact with MT to produce quality translation is not entirely clear. The use of MT and other forms of AI in the language industry necessitates consideration of risk, of value and of environmental and social sustainability. In this chapter, we introduce definitions of AI and automation, follow developments in AI within the language industry, and then consider the direction in which these developments need to go and how we might get there.