A policy paper from Hepi and Taylor & Francis argues that artificial intelligence can accelerate translational research — speeding discovery-to-application workflows, improving search and interdisciplinarity — but warns of ethical risks that could erode trust in academia. Case studies, including a University of Warwick tool aiding police investigations, show concrete gains in processing large text datasets and linking evidence to outcomes. Authors and interviewed academics emphasize the need for strong data governance, metacognitive training to prevent deskilling, and transparency about algorithmic limits to ensure AI augments rather than undermines research integrity.