Longevity in the age of artificial intelligence: opportunities, challenges, and the path toward equitable implementation
Social Determinants of Health,
Vol. 12 (2026),
1 January 2026
,
Page 1-11
https://doi.org/10.22037/sdh.v12i1.50696
Abstract
Background: The progressive integration of artificial intelligence (AI) into healthcare systems has generated substantial interest in its potential to extend human healthspan and lifespan. This narrative review examines the current state of AI applications relevant to longevity, with a focus on disease prediction and prevention, drug discovery, genomic analysis, and age-related risk stratification in older adults.
Methods: A comprehensive review of peer-reviewed literature was conducted using PubMed, Scopus, and Web of Science databases, supplemented by gray literature from regulatory agencies and international health organizations. Studies published between 2013 and 2024 were prioritized, with foundational works included where appropriate.
Results: Artificial intelligence demonstrates considerable promise in early detection of cardiovascular disease, oncologic conditions, and neurodegenerative disorders, often outperforming conventional risk models. Machine learning-based biological aging clocks offer novel frameworks for quantifying individual aging trajectories. However, persistent challenges including data fragmentation, algorithmic bias, regulatory ambiguity, and limited clinical interpretability constrain widespread adoption.
Conclusion: While AI holds transformative potential for extending both lifespan and healthspan, its realization depends on rigorous validation, equitable data representation, transparent model design, and interdisciplinary governance frameworks. AI should be positioned as a clinical decision-support tool that augments, rather than supplants, human medical judgment.
- Aging
- Artificial Intelligence
- Disease Prevention
- Healthcare
- Longevity
- Predictive Machine Learning
How to Cite
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