INTRODUCTION
Artificial Intelligence is rapidly improving the efficiency and accuracy of medical services. AI-powered technologies are now being used in diagnosis, medical data analysis and interpreting patterns that are not easily detected through traditional methods. As a result, AI has become an increasingly important decision-support tool in modern medical practice. However, the growing use of AI in healthcare raises important legal questions regarding liability for harm caused by AI-assisted medical decisions. The opaque nature of many AI systems also makes it difficult for healthcare professionals and courts to understand the reasoning behind AI-generated recommendations.
In India, the Consumer Protection Act 2019[1], judicial precedents and professional standards for medical practitioners together govern medical negligence. The courts have established the standard of reasonable care to assess the liability of medical professionals. This reflects the traditional negligence framework in which medical decisions are made by human practitioners.
Several jurisdictions, unlike India, are developing comprehensive regulatory frameworks to address AI-related risks in healthcare. Consequently, medical AI disputes in India are largely addressed through traditional negligence principles that do not fully account for the complexities of AI-assisted healthcare. Thus, the law should evolve to reflect technological advancements while ensuring legal accountability and patient protection.
MEDICAL NEGLIGENCE AND THE STANDARD OF CARE
Medical negligence is a branch of tort law that arises when a healthcare professional fails to provide the level of care reasonably expected from a competent medical practitioner, resulting in injury to a patient[2]. Indian courts have frequently held that not every medical error amounts to negligence, as a doctor is not expected to guarantee a successful outcome. Therefore, liability arises only when his conduct falls below the accepted standard of care.
To establish medical negligence, four essential elements must be proved: duty of care, breach of duty, causation (nexus) and damage.[3] In AI-assisted healthcare, the use of an AI-generated recommendation does not diminish the doctor’s professional duty. The doctor must independently assess whether the recommendation is consistent with the patient’s condition, medical history and accepted medical practice. Unreasonable reliance on an AI recommendation that a competent practitioner would have questioned or verified may constitute negligence. However, reliance on AI does not itself amount to negligence where the doctor exercises reasonable clinical judgement. Thus, the relevant standard remains whether the doctor acted with reasonable care in the circumstances.
The Supreme Court has defined the standard of care required through its numerous judgments. In Dr Laxman Balkrishna Joshi v. Dr Trimbak Bapu Godbole[4], the Court observed that a doctor owes a duty of care while deciding whether to undertake a case, the appropriate course of treatment and administering the treatment. This judgment established that negligence is assessed by examining whether reasonable care was exercised.
In Jacob Mathew v. State of Punjab,[5] the Supreme Court relied upon the Bolam principle[6] while determining the standard of care, holding that a doctor is not negligent if the treatment adopted is supported by a responsible body of medical opinion. In Kunal Saha v. Dr Sukumar Mukherjee[7], the Supreme Court reaffirmed that medical professionals are accountable when their conduct falls substantially below accepted professional standards, particularly where such conduct causes serious injury or death.
Apart from judicial precedents, patients may seek remedies under the Consumer Protection Act, 2019.[8] Since paid medical services are recognised as “services” under consumer law, patients may approach Consumer Commissions for compensation when negligence is established.[9]
AI IN MODERN HEALTHCARE: BENEFITS AND CHALLENGES
AI refers to technologies that enable computer systems to perform tasks requiring human intelligence such as learning, reasoning and pattern recognition.[10] In healthcare, AI assists in analysing X-rays, CT scans, predicting disease risks, planning treatment and monitoring patients. It also supports robotic-assisted surgery, telemedicine and efficient healthcare delivery, especially in countries like India where the doctor-patient ratio remains low.
Despite these benefits, AI also raises concerns regarding accuracy, biased training data, informed consent, confidentiality and data security.[11] Although the Digital Personal Data Protection Act, 2023[12] provides a framework for protecting personal data, India lacks comprehensive legislation regulating AI in healthcare. The “black-box” nature of AI further complicates negligence claims because courts may be unable to understand how a recommendation was generated.[13] In such cases, courts should consider the system’s reliability, testing, known limitations and the doctor’s independent assessment. Lack of explainability should therefore be a relevant factor in determining whether reasonable care was exercised.
ASSESSING LIABILITY IN AI-ASSISTED MEDICAL DECISION-MAKING
Doctors increasingly rely on AI-generated recommendations, but the use of AI does not by itself transfer their professional responsibility. A doctor may be liable where they blindly rely on an AI recommendation without applying independent clinical judgement. However, liability may also extend to hospitals, developers or manufacturers where harm results from inadequate supervision, defective programming, insufficient testing or failure to disclose known limitations.
Responsibility should therefore be determined according to each stakeholder’s role and control. Doctors should remain responsible for unreasonable clinical decisions, hospitals for inadequate supervision or training, and developers or manufacturers for defective systems, inadequate testing or undisclosed risks. Where both the AI recommendation and the doctor’s decision contribute to the injury, courts should determine whether the harm would have occurred without the AI error and whether the doctor’s independent decision materially contributed to the injury.
Since AI systems do not possess legal personality, liability must ultimately rest with the human or corporate actors responsible for their development, deployment, supervision or clinical use. Courts should therefore examine the degree of control exercised by each actor when determining responsibility.
GLOBAL REGULATORY APPROACHES TO MEDICAL AI
Several countries and international organisations have developed their own legal frameworks to combat risks associated with AI-assisted medical practice and ensure patient protection. The European Union has enacted the EU AI Act, which adopts a risk-based classification of AI systems. Certain AI systems used in healthcare, particularly those affecting health and safety, may be subject to high-risk requirements involving reliability, documentation and human oversight.[14] In the US, AI medical systems are under the regulatory oversight of the US Food and Drug Administration (FDA), which helps reduce risks before AI reaches patients. Here, AI functions as Software as a Medical Device (SaMD), which is continuously monitored for patient safety and effectiveness.[15]
The WHO has also recognised the need for responsible AI governance to assist healthcare professionals. It has laid emphasis on transparency, accountability, fairness and human oversight, ensuring that technological innovation remains centred on patient welfare.[16] The comparative developments suggest that India need not replicate the EU or US frameworks but can adopt principles suited to its healthcare system. From the EU approach, India could introduce a risk-based classification for medical AI with stricter requirements for high-risk systems concerning accuracy, transparency and human oversight. From the US approach, India could strengthen pre-market evaluation and continuous monitoring of AI-enabled medical devices. These measures, supported by the WHO principles of transparency, accountability and fairness, could be implemented through sector-specific regulations for healthcare institutions, professionals, AI developers and manufacturers.
PROPOSED LEGAL REFORMS FOR AI-ASSISTED MEDICAL NEGLIGENCE IN INDIA
The traditional principles of duty of care, breach, causation and damage remain a valuable foundation, but India should introduce specific rules for AI-assisted medical decision-making. AI should complement, not replace, a doctor’s independent clinical judgement. First, courts should consider whether doctors reasonably selected, understood and verified AI recommendations before relying on them.
Second, responsibility should be clearly allocated among doctors, hospitals, developers and manufacturers according to their respective roles and control. Hospitals should ensure proper validation, monitoring and training, while developers and manufacturers should be accountable for defective systems, inadequate testing and undisclosed limitations.
Third, healthcare institutions should maintain records of the AI system used, its recommendations, relevant warnings and the doctor’s final clinical reasoning. Patients should also be informed when AI significantly contributes to diagnosis or treatment, particularly in high-risk cases.
Finally, India should establish minimum standards for high-risk medical AI covering accuracy, data quality, cybersecurity, validation, human oversight and periodic monitoring. Developers and healthcare institutions should also preserve relevant records to assist courts in assessing AI-related negligence. These measures would strengthen accountability while allowing existing principles of medical negligence to adapt to AI-assisted healthcare.
CONCLUSION
The integration of AI into healthcare presents both significant opportunities and legal challenges. While AI has the potential to improve diagnostic accuracy and treatment efficiency, it also raises questions regarding liability, transparency and patient protection. India’s existing medical negligence framework continues to provide a strong legal foundation, but it was developed before AI became part of clinical decision-making. Rather than replacing traditional principles, the law should evolve to clarify the standard of care, allocate responsibility among stakeholders and establish an appropriate regulatory framework. Such measured reforms would promote innovation while ensuring accountability and public confidence in the evolving landscape of AI-assisted healthcare.
Author(s) Name: Roopali Ashiwal (Kanoria School of Law for Women, Jaipur)
References:
[1] Consumer Protection Act 2019
[2] Laxman Balkrishna Joshi v Trimbak Bapu Godbole and Anr AIR 1969 SC 128
[3] Jacob Mathew v State of Punjab and Anr (2005) 6 SCC 1
[4] Dr Laxman Balkrishna Joshi (n 2)
[5] Jacob Mathew v State of Punjab and Anr (2005) 6 SCC 1
[6] Bolam v Friern Hospital Management Committee [1957] 1 WLR 582
[7] Dr Kunal Saha v Dr Sukumar Mukherjee (2011) Original Petition No 240/1999
[8] Consumer Protection Act 2019
[9] Indian Medical Association v VP Shantha and Ors (1995) 6 SCC 651
[10] ‘What is Artificial Intelligence (AI)?’ (International Organization for Standardization) <https://www.iso.org/artificial-intelligence/what-is-ai> accessed 12 July 2026
[11] Clara Cestonaro et al., ‘Defining medical liability when artificial intelligence is applied on diagnostic algorithms: a systematic review’ (2023) 10 Frontiers in Medicine 1305756 <https://pmc.ncbi.nlm.nih.gov/articles/PMC10711067/> accessed 12 July 2026
[12] Digital Personal Data Protection Act 2023
[13] Cestonaro (n 11)
[14] EU Artificial Intelligence Act 2024
[15] ‘Artificial Intelligence-Enabled Medical Devices’ (US Food and Drug Administration) <https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices> accessed 12 July 2026
[16] Ethics and Governance of Artificial Intelligence for Health: WHO Guidance (World Health Organization 2021)