Policy Update
Ashi Verma
Background
The advent of generative artificial intelligence has fundamentally altered the digital information ecosystem, giving rise to sophisticated synthetic media commonly referred to as deepfakes. While such technologies offer creative potential, their malicious deployment for impersonation, electoral manipulation, and creation of non-consensual intimate content has posed unprecedented threats to privacy, public order, and democratic discourse. The regulatory architecture under the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, primarily based on a reactive notice-and-takedown model, was found to be insufficient to generation driven content generation.
In this context, the (MeitY) and Information Technology (Intermediary Guidelines) Amendment Rules, 2026 represent a paradigmatic shift towards ex-ante accountability. Notified on 15th January 2026, the amendment was propelled by rising incidents of synthetic frauds reported during 2024-25, judicial observations in public interest litigations concerning deepfake harms, and deliberations of the Parliamentary Standing Committee on Communications and Information Technology. Drawing normative inspiration from international frameworks like the European Union Artificial Intelligence Act, 2024, the 2026 Amendment institutionalizes mandatory labelling, provenance disclosure, and enhanced due diligence obligations for intermediaries hosting synthetic content, thereby moving from post-facto removal to proactive transparency.
Functioning
1.Mandatory Labelling and Disclosure Norms – The Rules mandate that every intermediary deploying generative AI tools must ensure that any synthetically created or substantially altered content carries a prominent, visible label indicating its artificial origin. The labelling must be human readable, indelible, and remain intact during further sharing or reproduction.
2. Metadata Embedding and Provenance Tracking – Beyond visible labelling, the amendment requires embedding of Coalition readable metadata as per C2PA (Coalition for Content Provenance and Authenticity) standards. Such metadata must include details of the originator, AI model used, and timestamp of creation to enable traceability and forensic verification by law enforcement agencies.
3. Due Diligence Obligations for Intermediaries – Under revised Rule 3(1)(b)(v), intermediaries are obligated to deploy technical measures to detect deepfakes prior to publication and to inform users at the time of uploading about the prohibition on hosting undisclosed synthetic content. Failure to comply may lead to loss of safe harbour protection under Section 79 of the IT Act, 2000.
4. Grievance Redressal and Expedited Takedown Mechanism – The Rules establish a 24-hour expedited takedown window for complaints related to non-consensual deepfakes and impersonation, particularly concerning women and children. Grievance Officers are required to act upon verified complaints and provide an acknowledgement with action taken report.
Performance
The implementation of the Information Technology (Intermediary Guidelines) Amendment Rules, 2026 has demonstrated a mixed yet progressive trajectory in regulating synthetic content. On the positive front, large significant social media intermediaries have shown substantial compliance by embedding visible labels and C2PA compliant provenance metadata in AI-generated content, which has enhanced transparency and user ability to distinguish authentic from manipulated media.
The introduction of a 24-hour expedited takedown framework for deepfakes involving women and children has led to faster remedial action, with grievance redressal timelines improving considerably compared to the 2021 regime. Nevertheless, critical gaps remain. The effectiveness of labelling is undermined by technological circumvention, such as deliberate removal of watermarks and metadata stripping during re-sharing across platforms. Smaller intermediaries and decentralized open-source generative models largely remain outside effective enforcement due to limited technical capacity and jurisdictional constraints. Moreover, detection on end-to-end encrypted platforms continues to pose a structural challenge.
Overall, while the Rules have successfully established the normative foundation for synthetic content accountability, their practical efficacy hinges on robust detection infrastructure, interoperability of standards, and sustained coordination between intermediaries, MeitY, and law enforcement agencies.
Impact
The IT Amendment Rules, 2026 have produced a transformative impact on India’s intermediary governance regime.
Primarily, it has strengthened user empowerment and informational integrity by institutionalizing mandatory disclosure of synthetic origin, thereby reducing the risks of deception, electoral disinformation, and reputational harm caused by deepfakes.
Second, it has redefined the contours of intermediary liability by conditioning safe harbour protection under Section 79 upon compliance with labelling and traceability obligations, thus promoting greater platform accountability.
Third, from a privacy and gender justice standpoint, the Rules have provided an effective remedial framework against non-consensual intimate deepfakes, offering expedited relief to victims and deterring misuse of generative AI. Fourth, it has catalysed technological innovation by incentivizing investment in provenance technologies such as C2PA standards and deepfake detection systems.
However, the framework also entails adverse implications, including increased compliance burden for smaller intermediaries and startups, risks of over-blocking legitimate creative AI content, and enforcement challenges in open-source ecosystems. Collectively, the Rules mark a significant step towards aligning Indian digital regulation with emerging global AI governance norms while balancing innovation with accountability.
Emerging Issues
- Technological Circumvention and Metadata Stripping – Despite mandatory watermarking, advanced users employ adversarial tools to remove visible labels and C2PA metadata during re-sharing, compression, or screen recording, rendering provenance tracking ineffective.
- Regulation of Open-Source and Decentralized Models – The Rules primarily target intermediaries, while open-source generative models available on platforms like GitHub and Hugging Face remain outside the enforcement ambit, allowing unregulated creation of deepfakes without any labelling compliance.
- Enforcement on End-to-End Encrypted Platforms – Detection and labelling obligations become unenforceable on encrypted messaging applications such as WhatsApp and Telegram, where synthetic content circulates virally without intermediary visibility.
- Conflict with Freedom of Expression and Creative Use – Over-broad labelling requirements risk chilling legitimate uses of synthetic media in satire, parody, cinema, and journalism. Lack of clear distinction between harmful deepfakes and permissible creative transformation raises concerns under Article 19(1)(a).
- Cross Border Jurisdictional Challenges – Most generative AI platforms operate from outside India, leading to difficulties in enforcing compliance, imposing penalties, and ensuring cooperation for forensic investigation and takedown of extraterritorial deepfake content.
Way Forward
To ensure effective implementation of the IT Amendment Rules, 2026, a multi-pronged approach is required that balances regulation with innovation. There is a need to develop robust, tamper-proof watermarking and detection technologies through collaboration between MeitY, academia, and private platforms, along with standardization of C2PA norms for cross-platform interoperability.
The regulatory scope must be expanded to include open-source generative AI models by introducing obligations for model developers to embed built-in labelling at the generation stage itself.
Simultaneously, a proportionate framework should be evolved to distinguish between malicious deepfakes and legitimate creative uses such as satire, parody, and cinematic expression to safeguard freedom of speech under Article 19(1)(a).
Capacity building of Grievance Officers and Grievance Appellate Committees, establishment of a centralized Deepfake Detection Cell, and public awareness campaigns on synthetic media literacy are essential to strengthen enforcement.
Finally, India should pursue international cooperation and mutual legal assistance agreements for cross-border enforcement, aligning its framework with global best practices like the EU AI Act, to create a safe, transparent, and accountable AI ecosystem.
References
Ministry of Electronics and Information Technology. (2021). Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021. https://www.meity.gov.in/writereaddata/files/Intermediary_Guidelines_and_Digital_Media_Ethics_Code_Rules-2021.pdf
Ministry of Electronics and Information Technology. (2026). Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Amendment Rules, 2026 – Notification G.S.R. 120(E). https://www.meity.gov.in/content/notifications-0
Government of India. (2000). The Information Technology Act, 2000. https://www.indiacode.nic.in/handle/123456789/1999
European Union. (2024). Regulation (EU) 2024/1689 – Artificial Intelligence Act. https://eur-lex.europa.eu/eli/reg/2024/1689/oj
Ministry of Electronics and Information Technology. (2023). Advisory on Deepfakes and Synthetic Content – Due diligence under IT Rules. https://www.meity.gov.in/content/advisories-0
About the Contributor
Ashi is pursuing B.A Program (History and Political Science) from Maitreyi College (NCWEB) South Campus Delhi University with a major in Political Science. She is passionate about governance, public policy, social issues and digital innovation, with a keen interest in research, academic writing, and data documentation. Through research and policy analysis, she aims to contribute to evidence-based policymaking and create meaningful social impact.
Acknowledgement
I would like to express my sincere gratitude to IMPRI (Impact and Policy Research Institute) for giving me the opportunity to work as an intern and write on such an important topic. I would also like to acknowledge the official MeitY and IndiaAI Mission for making authentic data available on the PIB Portal that helped me to complete this article.
Disclaimer
The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy or position of IMPRI (Impact and Policy Research Institute) or any other affiliated organisation. The information presented in this article is based on publicly available government sources and is intended solely for academic and research purposes
Reviewed By
Karnavi , Lahari
