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Global Journal of Flexible Systems Management

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13-02-2024 | ORIGINAL RESEARCH

Analyzing Barriers in Adoption of Artificial Intelligence for Resilient Health Care Services to Society

Authors: Girish Kumar, Rajesh Kumar Singh, Vedpal Arya, Shivam Kumar Mishra

Published in: Global Journal of Flexible Systems Management | Issue 1/2024

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Abstract

Artificial intelligence (AI) is emerging as an alternative solution in the healthcare sector, offering opportunities to enhance efficiency and optimize the utilization of precious resources. The nascent stage of AI application in the Indian healthcare sector has gained momentum during COVID-19, witnessing a surge in AI-based startups and companies specializing in diagnostic and prescriptive healthcare. This paper systematically analyzes barriers to AI application in the Indian context, incorporating the concept of flexibility, and proposes insights for fostering its adoption for resilient and sustainable healthcare practices. The identified barriers are drawn from literature and experts’ inputs. These are further investigated using the decision-making trial and evaluation and laboratory methodology. This analysis not only categorizes barriers into cause-and-effect groups but also emphasizes the need for flexibility to adapt AI solutions to the dynamic healthcare sector. The paper underscores foundational barriers, including inadequate regulations, lack of awareness, high adaptation costs, and a scarcity of skilled AI expertise. In addition to managerial and social implications concerning regulation, implementation, economic viability, and data privacy, the study promotes flexibility as a key factor in addressing the evolving challenges in healthcare.

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Title: Analyzing Barriers in Adoption of Artificial Intelligence for Resilient Health Care Services to Society
Authors: Girish Kumar
Rajesh Kumar Singh
Vedpal Arya
Shivam Kumar Mishra
Publication date: 13-02-2024
Publisher: Springer India
Published in: Global Journal of Flexible Systems Management / Issue 1/2024
Print ISSN: 0972-2696
Electronic ISSN: 0974-0198
DOI: https://doi.org/10.1007/s40171-024-00373-4

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