Industry internships are now a common part of AI PhDs, offering access to infrastructure, applied problems at scale, and networks beyond academia. This chapter explains when internships tend to pay off most, how to choose between research labs and more product-facing teams, and what companies typically look for in applications and interviews. It also covers how to integrate an internship into your PhD without losing momentum: set clear deliverables, watch for scope drift, clarify publication and IP constraints early, and keep your advisor in the loop. Used thoughtfully, an internship can be an accelerator rather than a detour.