The intersection of business and artificial intelligence in healthcare: Opportunities and ethical challenges

Jin young Hwang *

University of Edinburgh MA Social Policy and Economics, United Kingdom.
 
Review Article
GSC Advanced Research and Reviews, 2025, 22(01), 139-150.
Article DOI: 10.30574/gscarr.2025.22.1.0020
Publication history: 
Received on 05 December 2024; revised on 14 January 2025; accepted on 17 January 2025
 
Abstract: 
This dissertation seeks to examine the connection between business and artificial intelligence (AI) in the health sector, major possibilities, and the current ethical issues. It is evident that adoption of AI has revolutionized healthcare by improving clients’ satisfaction, productivity and cost by using technological tools such as analytical tools, tele surgery, and disease diagnosis. This is important because the global AI healthcare market has been estimated to grow to $45.2 Billion by 2026. The study of two different countries – the United States and the United Kingdom – offers an understanding of AI implementation, legislation, and ethical standards as the result of different health systems and legislation. This work reveal potential benefits are enhanced diagnostic accuracy, cost savings whereas the potential harms include violations of patient privacy, bias in algorithms, and accountable issues. The target field adopts theoretical concepts such as The Technology Acceptance Model and The Diffusion of Innovation Theory to review factors affecting AI uptake. This also looks into ethical considerations as a way of making sure that properly applied. The implications of the chosen regulatory frameworks as tools for the analysis of business and patient care strategies are demonstrated in the studied examples of GDPR and HIPAA. The studies provide practical recommendations for both healthcare organizations and policy-makers as well as companies that are importing AI into their services. In conclusion, this research provides to the improvement of healthcare while exploring the signals for confronting the moral issues of AI application on global healthcare settings.
 
Keywords: 
Artificial Intelligence; Ethical Challenges in AI; Healthcare Innovation; Regulatory Frameworks; Patient Data Privacy; AI Adoption Models
 
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