DPIIT Reviews Copyright Rules for Generative AI Training

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  • Last Updated on 11 December, 2025

copyright and generative AI training

Working Paper No. P-24029/34/2025-IPR-VII, Dated: 08.12.2025

1. Background

The Department for Promotion of Industry and Internal Trade (DPIIT) has constituted a Committee to examine the interface between Generative Artificial Intelligence (GenAI) and copyright law in India. Rapid adoption of AI models—particularly those trained using large datasets containing copyrighted material—has raised questions on legality, ownership, consent, liability, and compensation mechanisms.

Given the global debate on whether AI training constitutes fair use, infringement, or permitted data mining, the Committee has been tasked with reviewing the adequacy of India’s current copyright regime.

2. Scope of Examination

The Committee will assess:

  • Whether the existing Copyright Act and related jurisprudence adequately address the use of copyrighted works in AI training
  • The implications of:
    1. Text and data mining (TDM)
    2. Replicative output
    3. Derivative content generated by AI
    4. Attribution and authorship
  • The need for new carve-outs, exceptions, or licensing mechanisms that can balance:

    1. Innovation incentives
    2. Copyright protection
    3. Commercial exploitation safeguards

The objective is to examine whether India’s legal framework provides sufficient clarity for creators, platform developers, dataset curators, and AI enterprises.

3. Need for Possible Legislative Amendments

The Committee has been asked to determine whether:

  • Existing copyright exceptions, including those relating to research, transient storage, or fair dealing, are sufficient in the context of AI training
    or
  • Legislative amendments, regulatory guidance, or model licensing frameworks are required to:
    1. Protect rights holders
    2. Enable lawful and scalable AI innovation
    3. Provide certainty to market participants

The review also covers ownership of AI-generated works, originality thresholds, and attribution responsibilities.

4. Working Paper Released for Consultation

As part of its consultative process, Part I of the Working Paper has been released for public and stakeholder feedback.

Stakeholders such as:

  • Technology companies
  • AI developers and research institutions
  • Publishers, authors, and content creators
  • IP lawyers, civil society bodies, and policy experts

are invited to submit comments to help shape the future regulatory and legislative position around generative AI and copyright compliance.

5. Policy Significance

The initiative aims to:

  • Reduce uncertainty surrounding use of copyrighted material in large-scale dataset training
  • Provide predictable legal norms for AI development and monetisation
  • Strengthen creator rights and attribution safeguards
  • Enable a balanced ecosystem that protects innovation without undermining original copyright

India’s approach may influence market models, licensing practices, and global data-sharing norms, given the increasing scale of AI development and cross-border technology operations.

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Taxmann Publications has a dedicated in-house Research & Editorial Team. This team consists of a team of Chartered Accountants, Company Secretaries, and Lawyers. This team works under the guidance and supervision of editor-in-chief Mr Rakesh Bhargava.

The Research and Editorial Team is responsible for developing reliable and accurate content for the readers. The team follows the six-sigma approach to achieve the benchmark of zero error in its publications and research platforms. The team ensures that the following publication guidelines are thoroughly followed while developing the content:

  • The statutory material is obtained only from the authorized and reliable sources
  • All the latest developments in the judicial and legislative fields are covered
  • Prepare the analytical write-ups on current, controversial, and important issues to help the readers to understand the concept and its implications
  • Every content published by Taxmann is complete, accurate and lucid
  • All evidence-based statements are supported with proper reference to Section, Circular No., Notification No. or citations
  • The golden rules of grammar, style and consistency are thoroughly followed
  • Font and size that's easy to read and remain consistent across all imprint and digital publications are applied