OBJECTIVES: Innovations in artificial intelligence (AI) allows greater efficiencies in health-economics and outcomes research (HEOR). Three crucial pillars ensure the optimal employment of AI methodologies for the purpose of HEOR activities informing health technology assessment (HTA)s:

METHODS: A review of key HTA agencies’ (EU5, Sweden, and Canada) guidelines to assess their views on the use of AI for HTAs was conducted in June 2024.

RESULTS: The National Institute for Health and Care Excellence (NICE) in the UK and the Federal Joint Committee (G-BA) in Germany have AI guidance in development. None of the other reviewed agencies have guidance on the use of AI for HTA. NICE’s manual for developing guidance (PMG20) describes the use of machine learning to support literature reviews. Namely, for study type classification and priority screening prior to manual review.

CONCLUSIONS: There is a lack of guidance on the use of AI for HTA. The largely undefined level of HTA stakeholder acceptance on the use of AI may lead to underuse or possibly irresponsible use of AI (e.g., lack of transparency). Manufacturers and pharmaceutical companies should seek a dialogue on this topic outside of product negotiations to establish best practices.