Artificial Intelligence in Indian Dermatology: An IADVL Academy Position Statement and Policy Framework for Safe, Equitable, and Effective Adoption

Abstract Artificial intelligence (AI) systems, particularly deep learning models, are increasingly used in dermatology for image analysis, triage, remote monitoring, and decision support. For real-world adoption in the Indian dermatology ecosystem, robust validation, transparency, and governance are essential to protect patient safety and equity. This position statement synthesizes guidance from international dermatology societies and major regulatory approaches, and proposes India-adapted recommendations across clinical use, dataset curation, validation standards, ethics, privacy, liability, and policy. We performed a narrative synthesis of position statements from the American Academy of Dermatology (AAD), European Academy of Dermatology and Venereology (EADV), British Association of Dermatologists (BAD), and Australasian College of Dermatologists (ACD); regulatory frameworks, including the European Union Medical Device Regulation (EU MDR), the United States Food and Drug Administration (US FDA) Software as a Medical Device (SaMD) approach, National Institute for Health and Care Excellence (NICE) evidence standards, and Australia’s Therapeutic Goods Administration (TGA). Indian frameworks, including the Central Drugs Standard Control Organisation (CDSCO) Medical Device Rules, Bureau of Indian Standards/International Organization for Standardization (BIS/ISO) standards, the Digital Personal Data Protection (DPDP) Act, and Indian Council of Medical Research (ICMR) artificial intelligence ethics guidance were included. Seven domains were analyzed: governance, evidence generation, data bias, clinical safety, privacy, liability, and education. Principles emphasize clinician-in-the-loop use, prospective multicentric validation in representative Indian settings, skin-of-color inclusivity, transparent labeling and explainability, post-market surveillance, and clearer accountability. While clinical utility and health-economic evidence remain limited, validated and inclusive AI tools can responsibly expand access to quality dermatologic care in India, particularly in underserved areas.