As Artificial Intelligence (AI) becomes increasingly embedded in healthcare decision-making, diagnostics, drug development, and patient management, regulatory frameworks play a critical role in safeguarding public trust, ensuring patient safety, and aligning innovation with ethical and legal standards. Governments and institutions around the world are evolving their regulatory ecosystems to address the distinctive challenges posed by AI—from data privacy to liability and algorithmic accountability. This section outlines how India and leading global entities are shaping the governance of AI in healthcare.
India: Building a Foundational Framework for Responsible AI
India’s regulatory approach to healthcare AI is steadily evolving, aiming to balance innovation with protection.
Digital Personal Data Protection (DPDP) Act, 2023
The DPDP Act is India’s flagship legislation for personal data protection. It establishes robust frameworks for consent, data minimization, purpose limitation, and cross-border data transfer, with stringent safeguards for the processing of health data, considered a sensitive category. For AI in healthcare, this act mandates explicit patient consent, clear notice requirements, and stringent controls on data sharing between hospitals, third-party AI providers, and insurers. Its enforcement mechanisms represent a foundational shift toward data sovereignty and ethical data usage.
Information Technology (IT) Act, 2000 & SPDI Rules
The IT Act and its associated Sensitive Personal Data or Information (SPDI) Rules serve as the baseline legal instruments for managing digital healthcare data in India. While originally not AI-specific, they govern how medical platforms handle data security, breach notification, and patient information storage. These provisions act as a foundational layer for AI systems that handle or process EHRs, imaging data, or patient communications.
Clinical Establishments (Registration and Regulation) Act, 2010
While aimed at the regulation of healthcare facilities, this Act gains new relevance as AI-driven tools become integral to clinical practice. The inclusion of digital health services under its purview underscores the need for all establishments deploying AI-based diagnostics or virtual consultations to meet prescribed standards of care, safety, and ethical conduct.
National Medical Commission (NMC) Act
The NMC Act provides a legal framework governing medical education and professional conduct. As AI tools increasingly support or augment clinical decision-making, the NMC is expected to issue practice guidelines and ethical codes for clinicians using AI technologies. These would address issues like clinical accountability, consent, and the limits of AI-assisted diagnosis or treatment.
ICMR Ethical Guidelines for AI in Biomedical Research
India has demonstrated ethical foresight through the Indian Council of Medical Research (ICMR), which issued dedicated guidelines for AI in biomedical research and healthcare. These guidelines emphasize algorithmic transparency, patient safety, informed consent, and equity, advocating for explainable models and fairness audits to mitigate bias. The ICMR document is one of the most comprehensive public ethical charters on AI in the Global South.
Global Developments: Setting International Benchmarks
International regulatory efforts are also intensifying, with the European Union and the United States leading the charge in establishing comprehensive frameworks.
European Union AI Act
The EU AI Act, the world’s first comprehensive AI-specific regulation, adopts a risk-based approach to AI systems. In healthcare, most applications are classified as “high-risk,” subjecting them to strict design, testing, human oversight, data quality, and transparency requirements. The Act mandates explainability, prohibits certain types of opaque AI, and enforces continuous performance monitoring. For Indian AI developers eyeing the European market, compliance with the AI Act is non-negotiable.
European Health Data Space (EHDS)
The EHDS is designed to create a secure infrastructure for cross-border health data exchange across EU countries. It facilitates the use of anonymized datasets for research, innovation, and AI training, ensuring patient rights, transparency, and security. EHDS supports AI model development while aligning with GDPR principles, becoming a blueprint for how large-scale, privacy-aware data collaboration can fuel AI innovation.
EU Product Liability Directive
This directive has been updated to specifically include AI-based products, such as software-as-a-medical-device (SaMD). It holds manufacturers and developers liable for harm caused by defective AI tools, even when outcomes stem from automated learning or autonomous behavior. It aims to plug gaps in assigning fault when AI misbehaves—an area of increasing legal importance globally.
United States: Sector-Specific and Federated Regulation
FDA Guidance for AI/ML-Based Medical Devices
The U.S. Food and Drug Administration (FDA) has issued multiple draft guidances addressing AI in medical devices. It focuses on Total Product Life Cycle (TPLC) regulation, covering premarket approval, post-market performance monitoring, real-world evidence, and algorithm changes over time. The FDA now expects AI developers to submit explainability protocols, transparency documentation, and risk mitigation strategies.
Executive Order on Safe, Secure, and Trustworthy AI (2023)
In response to the rapid proliferation of generative and predictive AI models, the Biden Administration issued an Executive Order mandating that federal agencies, including the FDA, promote AI safety, fairness, and accountability. This includes calling for bias testing, protecting civil rights, and preventing algorithmic harm in sensitive domains like healthcare.
State-Level Regulations: Colorado & California
States are stepping in to regulate AI’s ethical dimensions. Colorado’s AI Act (2024) mandates impact assessments for high-risk AI systems in healthcare, including documentation of potential bias. California’s Assembly Bill 3030 requires explicit disclosure and patient consent for the use of AI in clinical decisions. These initiatives reflect a growing demand for algorithmic transparency at the point of care.
Conclusion
Across both developing and developed contexts, regulatory ecosystems are catching up to the fast-paced advances in AI. India’s evolving framework—anchored by data protection, medical ethics, and digital governance—is increasingly aligning with global best practices. Meanwhile, the EU’s stringent AI Act and the U.S.’s sector-specific regulations are setting international benchmarks for accountability, transparency, and risk control.
Together, these frameworks represent a shared commitment: to build a healthcare future where AI is not just intelligent, but safe, fair, explainable, and trustworthy. The challenge ahead lies in harmonizing innovation with governance—so that AI enhances care without compromising rights.
–Rashmi Kumari
