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India is preparing a policy outline on how architects of artificial intelligence (AI) can use copyrighted material, a development that promises to impact AI giants and startups that digest vast amounts of data to spit out everything from quirky images to medical analyses.<\/p>\n<\/div>\n
The Department for Promotion of Industry and Internal Trade (DPIIT) has recommended a mandatory licensing model for AI developers, granting large language model (LLM) developers compulsory access to all “lawfully accessed copyrighted content” for model training without seeking individual permission from the creators; in turn, the developers would be required to pay royalties through a single, government-designated collecting body managed by rights holders.<\/p>\n<\/div>\n
\u201cThe entity will function as a centralized body for licensing and royalty distribution under the compulsory blanket licensing model,\u201d it said.<\/p>\n<\/div>\n
The DPIIT working paper said this would lower compliance costs for AI startups, reduce litigation risk, and create a level playing field between large and small players. It would also open a steady revenue stream for creators, including from India\u2019s vast informal creative sector.<\/p>\n<\/div>\n
The proposal argues that India requires a distinct regulatory structure that actively encourages AI innovation<\/a> while ensuring creators are fairly compensated when their works are used to train AI systems. The move, described as a “one nation, one licence, one payment” hybrid model, aims to fuel India’s ambitious \u20b9<\/span>10,300 crore IndiaAI Mission while ensuring creators are compensated.<\/p>\n<\/div>\n However, mandatory licensing and centralized royalty do not align with technical realities, said Kazim Rizvi, founding director of The Dialogue, a tech policy think tank. “Contemporary AI systems process billions of data points in iterative, non-deterministic ways that do not preserve work-level traceability. Expecting developers to identify, account for, or retrospectively reconstruct the contribution of individual copyrighted works is technically infeasible. A system premised on granular attribution, expansive repertoire completeness, or post-hoc compliance risks imposing burdens that would disproportionately harm startups and MSMEs, stifle research, and undermine India\u2019s competitiveness in global AI development,” Rizvi said, adding the model\u2019s potential retrospective application further opens a \u201cworm-box\u201d of uncertainty.<\/p>\n<\/div>\n “Training corpora evolves continuously, model weights cannot be reverse-engineered to reveal underlying works, and global regulatory practice does not impose retroactive obligations of this nature. Introducing such liabilities would chill investment, create interoperability risks, and generate systemic disputes without delivering meaningful benefits to creators” he said.<\/p>\n<\/div>\n The draft proposal, which will remain open for 30 days for feedback, is the government\u2019s first formal policy outline in an area that has sparked intense global debate over the future of intellectual property. It comes in the wake of soaring AI adoption, mushrooming AI startups and conflicts over the use of copyrighted content by AI developers.<\/p>\n<\/div>\n A DPIIT<\/a> committee formed in April, after examining frameworks in the US, EU, UK and others, concluded that India cannot afford to wait for international litigation to settle before making its move.<\/p>\n<\/div>\n The core legal dilemma the paper addresses is that AI training involves multiple acts of reproduction\u2014from downloading and storing works to generating temporary copies\u2014that raise clear infringement questions under India\u2019s Copyright Act. To resolve this, the DPIIT suggested designating a non-profit royalty-collection body, comprising copyright societies and collective management organizations, that would collect payments from AI developers and distribute royalties to both its members and registered non-members.<\/p>\n<\/div>\n Madhav Krishna, CEO and founder of Vahan.ai said while the intent to compensate creators is fair, blanket licensing will introduce “real friction” for AI developers in India. “Unlike Western companies that trained on vast internet datasets without such constraints, Indian developers will now face regulatory and financial hurdles from the outset,” he said.<\/p>\n<\/div>\n While the move seems directionally right, a key side effect could be a slowdown in AI development – something that ultimately harms India\u2019s ambitions to build and scale indigenous AI capabilities. We need a balanced approach that protects creators without stifling innovation, especially for early-stage startups,” Krishna said.<\/p>\n<\/div>\n As per Nikhil Kurhe, CEO and co-founder of Finarkein, a data and AI infrastructure platform, AI companies operate in a grey zone when it comes to negotiating licences, navigating copyright, and managing uncertain liabilities. India is also becoming the largest accessible AI market for both global and domestic players, with a rapidly growing base of active users.<\/p>\n<\/div>\n \u201cA blanket statutory license can create a predictable and transparent path forward for everyone to navigate these challenges. However, its implementation must be fair and scale-dependent; otherwise, it risks becoming an entry barrier for startups and further strengthening incumbents,\u201d Kurhe said.<\/p>\n<\/div>\n Crucially, the policy paper rejects the tech industry’s push for a broad “text-and-data-mining” (TDM) exception that would permit AI training without payment, a stance the committee argues would “undermine copyright” and leave smaller artists powerless to seek compensation. The paper also discards opt-out models, citing the unreasonable technical and legal burden they place on creators.<\/p>\n<\/div>\n The proposal arrives as India, through the IndiaAI Mission<\/a>, is actively positioning itself as a global AI hub, backing foundational model startups and expanding compute capacity. The government maintains that this licensing framework is vital for granting domestic AI firms transparent, legal access to rich, copyright-protected datasets, reducing barriers to innovation, and aligning with the goal of building sovereign AI capabilities.<\/p>\n<\/div>\n Entrepreneur Bhavish Aggarwal’s Krutrim AI<\/a> is currently building what it calls India’s first homegrown foundational LLM, trained extensively on Indic languages. Sarvam AI is another leading deeptech startup focused on developing high-performing, culturally fluent LLMs, including its OpenHathi Hindi model. The government-backed BharatGen Technology Foundation, established by an IIT Bombay consortium, is dedicated to constructing a multilingual LLM framework, while established players like Tech Mahindra are working on their in-house Indic model, Project Indus.<\/p>\n<\/div>\n Krishna Kamal Palakaluri, senior director at Mirror Security said, \u201cIf India pairs transparent royalty mechanisms with tiered pricing and strong data provenance standards, we can avoid a \u2018pay-to-play\u2019 ecosystem while still protecting creators. Done well, this framework could become a global reference model for secure, responsible, and innovation friendly AI development.\u201d<\/p>\n<\/div>\n Furthermore, the framework must remain strictly scoped to training data and explicitly exclude user prompts, logs, or security telemetry, said Palakaluri.<\/p>\n<\/div>\n The policy paper comes in the backdrop of escalating legal battles over AI. News agency ANI Media has sued OpenAI in the Delhi High Court, accusing the ChatGPT developer of unauthorized use of copyrighted articles to train its LLMs. This runs parallel to major global litigation, most notably The New York Times<\/a> v. OpenAI and Microsoft in the US, alleging the unauthorized use of millions of articles, and the Authors Guild class action, where prominent writers contend their books were copied wholesale, as well as specific sectoral challenges from Getty Images and the Concord Music Group, all testing the limits of fair use and transformative works in the AI era.<\/p>\n<\/div>\n