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Artificial intelligence innovation in healthcare: Literature review, exploratory analysis, and future research

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  • Zahlan, Ahmed
  • Ranjan, Ravi Prakash
  • Hayes, David

Abstract

Artificial intelligence (AI) innovation in healthcare has emerged as an increasingly significant area of research. AI, digital data collection, and computer infrastructure advancements have empowered humans to address complex healthcare challenges. This study conducts a systematic literature review (SLR) of peer-reviewed journal articles at the intersection of AI, innovation, and healthcare to offer research directions for scholars and leaders in healthcare management. To achieve this, the systematic review identified and analyzed 378 published studies on AI innovation in healthcare. Evaluating these publications based on inclusion and exclusion criteria yielded 75 studies ultimately selected for comprehensive analysis. This research adds to the scope of previous investigations by aiming to 1) emphasize the most crucial AI-based healthcare applications, 2) explore challenges associated with AI integration in healthcare, and 3) examine student adoption and incorporation of AI into existing healthcare curricula. We also conducted an exploratory study of over 2700 AI-enabled healthcare startups worldwide to supplement our literature review. The SLR reveals several gaps within the research scope and proposes corresponding future research directions. These future research directions will assist researchers and enable healthcare professionals to develop legislation that accelerates the adoption of AI solutions in healthcare, ultimately enhancing public access to efficient and effective healthcare services.

Suggested Citation

  • Zahlan, Ahmed & Ranjan, Ravi Prakash & Hayes, David, 2023. "Artificial intelligence innovation in healthcare: Literature review, exploratory analysis, and future research," Technology in Society, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:teinso:v:74:y:2023:i:c:s0160791x23001264
    DOI: 10.1016/j.techsoc.2023.102321
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    6. Williams, Robin & Anderson, Stuart & Cresswell, Kathrin & Kannelønning, Mari Serine & Mozaffar, Hajar & Yang, Xiao, 2024. "Domesticating AI in medical diagnosis," Technology in Society, Elsevier, vol. 76(C).
    7. Bin-Nashwan, Saeed Awadh & Li, Jackie Zhanbiao, 2025. "AI-infused knowledge and green intellectual capital: pathways to spur accounting performance drawn from RBV-KBV model and sustainability culture," Technology in Society, Elsevier, vol. 82(C).
    8. Li, Weixia & Wang, Jianguo, 2024. "Determinants of artificial intelligence-assisted diagnostic system adoption intention: A behavioral reasoning theory perspective," Technology in Society, Elsevier, vol. 78(C).
    9. Ali, Omar & Murray, Peter A. & Momin, Mujtaba & Al-Anzi, Fawaz S., 2023. "The knowledge and innovation challenges of ChatGPT: A scoping review," Technology in Society, Elsevier, vol. 75(C).
    10. Sebastian Bartsch & Oliver Behn & Alexander Benlian & Roger Brownsword & Sebastian Bücker & Marcus Düwell & Nico Formánek & Marc Jungtäubl & Michael Leyer & Alexander Richter & Jan-Hendrik Schmidt & M, 2025. "Governance of High-Risk AI Systems in Healthcare and Credit Scoring," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 67(4), pages 563-581, August.
    11. Arroyabe, Marta F. & Arranz, Carlos F.A. & Fernandez De Arroyabe, Ignacio & Fernandez de Arroyabe, Juan Carlos, 2024. "Analyzing AI adoption in European SMEs: A study of digital capabilities, innovation, and external environment," Technology in Society, Elsevier, vol. 79(C).
    12. Yang, Liang & Zhang, Manyang & Jia, Lin & Yan, Zhijun & Yin, Qiuju, 2025. "Understanding digital therapeutics in disease self-management: A systematic literature review," Technology in Society, Elsevier, vol. 81(C).

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