There has been considerable debate around the ethical issues raised by data-driven technologies such as artificial intelligence. Ethical principles for the field have focused on the need to ensure that such technologies are used for good rather than harm, that they enshrine principles of social justice and fairness, that they protect privacy, respect human autonomy and are open to scrutiny. While development of such principles is well advanced, there is as yet little consensus on the mechanisms appropriate for ethical governance in this field. This paper examines the prospects for the university ethics committee to undertake effective review of research conducted on data-driven technologies in the university context. Challenges identified include: the relatively narrow focus of university-based ethical review on the human subjects research process and lack of capacity to anticipate downstream impacts; the difficulties of accommodating the complex interplay of academic and commercial interests in the field; and the need to ensure appropriate expertise from both specialists and lay voices. Overall, the challenges identified sharpen appreciation of the need to encourage a joined-up and effective system of ethical governance that fosters an ethical culture rather than replacing ethical reflection with bureaucracy.