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Generative AI in healthcare: foundations, applications, challenges and future directions

Author

Listed:
  • Jiamin Zheng
  • Bin Li
  • Hongmei Li
  • Yang Lu

Abstract

Generative AI, as a key technology driving the digital transformation of the medical system, is reshaping the processing and application models of medical information. This study conducts a review on the technical foundation, application scenarios, key challenges, and future development trends of Generative AI in healthcare. Although Generative AI demonstrates value in information processing, decision support, and patient services, its actual deployment is concentrated in low-risk areas. The application of Generative AI in high-risk clinical scenarios is limited by the lack of technical reliability, organizational acceptance, and regulatory frameworks. Generative AI could be regarded as an auxiliary and human-oriented technological tool rather than as an autonomous system that replaces clinical professional judgment. The long-term impact of Generative AI in healthcare will depend on whether it can truly meet clinical practical needs. Through a governance model and a human-oriented implementation path, the true integration of Generative AI and the healthcare system can be achieved.

Suggested Citation

  • Jiamin Zheng & Bin Li & Hongmei Li & Yang Lu, 2026. "Generative AI in healthcare: foundations, applications, challenges and future directions," Journal of Management Analytics, Taylor & Francis Journals, vol. 13(2), pages 350-378, April.
    • Handle: RePEc:taf:tjmaxx:v:13:y:2026:i:2:p:350-378
    DOI: 10.1080/23270012.2026.2647940
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