Better or just faster? AI’s real role in health technology assessment (HTA)
In the first episode of “The Real-World Evidence is Clear” podcast, host Matthew Bending is joined by Jack Ishak and University College London professors Gianluca Baio and Rachael Hunter for a discussion focused on one of the most important questions facing HTA today: Is AI genuinely improving evidence generation and decision-making, or simply accelerating parts of the process?
The conversation explores areas where AI can genuinely add value, where it introduces new risks, and why trust, transparency and scientific judgment remain central as adoption increases.
Listen to the podcast
In this episode, the panel discusses
- Why the central question is not whether AI makes parts of HTA faster, but how to make it faster while remaining rigorous, credible and useful for decision-making
- Why without enough understanding of how it AI works, it can shift effort rather than eliminating it, with time saved upfront often reappearing later in checking, correction and validation
- Who is likely to shape the rules of AI use in HTA, and why regulators, industry, consulting and academia must move together
- The impact of technology and models evolving faster than traditional review cycles
- Ways AI may affect junior roles and the impact on training
Featured speakers
- Matthew Bending
Vice President, Global Head of Health Economics & Market Access, PPD Evidera Health Economics and Market Access, Thermo Fisher Scientific - Jack Ishak
Vice President, Statistical Methodology & Innovation, PPD Evidera Health Economics and Market Access, Thermo Fisher Scientific - Professor Gianluca Baio
Professor of Statistics and Health Economics, University College London - Professor Rachael Hunter
Professor of Health Economics, University College London