A Study on Ethical and Regulatory Challenges of AI Adoption in Healthcare

Author

Ch. Swathi, Dr. Y. Venkata Ramana

Abstract

 Artificial Intelligence (AI) can improve diagnostics, predictive analytics, and clinical decision support, yet its adoption in healthcare is constrained by unresolved ethical, legal, and regulatory challenges, including algorithmic bias, limited transparency, unclear accountability, and weak data-privacy safeguards. This study examines how ethical challenges, regulatory challenges, and governance factors relate to responsible AI adoption in healthcare. A descriptive, quantitative survey was conducted using a structured questionnaire; after removing repeated submissions, 22 valid responses from students and professionals in healthcare, technology/IT, and other fields were analysed using descriptive statistics, Cronbach's alpha, multiple linear regression, a chi-square test, and one-way ANOVA.

Respondents reported uniformly favourable views (construct means between 4.49 and 4.67 on a 5-point scale). The regression model was statistically significant (F(3, 18) = 57.62, p < .001, adjusted R² = .890). Ethical challenges (β = .40, p = .001) and governance factors (β = .41, p = .027) were significant positive predictors of responsible AI adoption, whereas regulatory challenges were not (p = .211), partly because they overlap strongly with governance factors. Responsible AI adoption did not differ significantly by respondent status (χ²(2) = 0.041, p = .980) or by field group (F(2, 19) = 0.41, p = .667). Most respondents named data privacy as the main challenge (68.2%) and attributed responsibility for AI errors mainly to AI developers (63.6%).

Because the sample is small, convenience-based, and predominantly young students, the findings are exploratory. The study nevertheless contributes an initial governance-oriented picture of what stakeholders expect from responsible AI adoption and identifies priorities for healthcare managers, policymakers, and regulators.

Keywords

Artificial Intelligence, Healthcare, Ethical Challenges, Regulatory Compliance, AI Governance, Patient Trust, Responsible AI Adoption

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References

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