Aaron Wan Jia He, Ferrina Hoi Yan Cheung, Yuna Shao, Gen Li, Xiaoyun Xie, Sophia Siu Chee Chan
Despite increasing concern about the climate impacts of AI, environmental outcomes are rarely considered within evaluations of AI technologies in clinical radiology. However, there are approaches available with smaller carbon footprints. To meet their stated aims on sustainability, funders and governance bodies should consider how to promote integration of environmental impact assessment into AI health research and evaluation.
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: Tobacco use remains a major public health challenge and the leading preventable cause of death worldwide. Artificial intelligence is increasingly applied in smoking cessation research, but its overall thematic landscape and development trends have not been systematically described.
WHAT IS ADDED BY THIS REPORT?: This bibliometric and content analysis identified 1,728 publications on artificial intelligence (AI) in smoking cessation from inception to March 5, 2026. Research output increased markedly after 2017, with intervention as the dominant domain, while prediction and diagnosis emerged as closely related AI areas and monitoring remained substantially underexplored.
WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: AI has strong potential to enhance tobacco control through digital interventions, predictive analytics, diagnostic support, and longitudinal monitoring. Expanding monitoring applications and strengthening trustworthy governance of AI may help improve smoking cessation strategies and support global tobacco control goals.