Artificial Intelligence in Healthcare : Market Dynamics, Ethical Imperatives, and Managerial Foresight
DOI:
https://doi.org/10.17010/pijom/2025/v18i9/174845Keywords:
AI in healthcare, artificial intelligence, healthcare applications.JEL Classification Codes : I18, M15, O31
Publication Chronology: Paper Submission Date : March 10, 2025 ; Paper sent back for Revision : June 10, 2025 ; Paper Acceptance Date : August 25, 2025 ; Paper Published Online : September 15, 2025
Abstract
Purpose : This paper explored the transformative impact of artificial intelligence (AI) on the healthcare sector, with a dual focus on global market trends and stakeholder perceptions. It examined the projected growth of AI applications in diagnostics, telemedicine, and hospital administration, while addressing ethical imperatives and managerial responsibilities.
Methods : The study synthesized secondary data from market research reports (Grand View Research, Markets and Data, AIPRM, and Statista) and presented two comparative tables outlining global and Indian healthcare AI projections. In addition, a survey was conducted among the stakeholders (physicians, patients, and healthcare administrators) to get their perceptions, concerns, and expectations on adopting AI in the healthcare sector.
Significant Findings : The global AI healthcare market is projected to reach $194 billion by 2030, with 90% hospital adoption. AI is expected to save $15 billion annually in India and create 500,000 new jobs. While stakeholders recognize AI’s potential to improve diagnostic accuracy and access, concerns persist around data privacy, job displacement, and fairness. Ethical governance, inclusive design, and strategic leadership are essential for responsible AI deployment.
Implications : Healthcare leaders must ethically integrate AI by training teams, aligning decisions with evolving regulations, and positioning AI as a supportive tool. Pilot projects may be initiated in many different places. However, to make strong, fair, and trustworthy systems, leaders need to have strong data governance, inclusive and ethical design, and collaboration across sectors.
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References
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