By Vishno Sudheendra
With judgment now reserved in ANI v OpenAI, India stands at the cusp of what might be its first major judicial reckoning with the copyright implications of generative AI. The case raises foundational questions on whether AI systems merely process information in new ways or unlawfully appropriate protected expression. Vishno Sudheendra examines two of the most contested issues from the final hearings: chatbot web search functionality and memorization. Vishno is a fourth-year B.A., LL.B (Hons) student at the National Law School of India University, Bangalore, with a keen interest in various aspects of IPR and technology law.
The judgment in ANI v OpenAI [CS(COMM) 1028/2024] has been reserved, with the last hearing culminating on 27th March, 2026 [order]. This litigation is the first (and, so far, the only) Copyright and AI training-related litigation in India. The DPIIT Working Paper had also left the question of whether AI training infringes copyright open, noting that it “does not attempt to resolve these questions or offer definitive conclusions” on this issue. Thus, the verdict in this case will shape the legal course of copyright and AI training-related issues in India. [Readers can view previous updates and analysis by Bharathwaj here]
In this post, I seek to discuss two interesting issues raised in the last two hearings- web search functionality of AI chatbots and memorization. The search functionality of AI chatbots allows them to access real-time information from the web using Retrieval Augmented Generation (“RAG”) – essentially, this complements their training data, which is updated periodically. ANI argued that this functionality is infringing and also drives down web traffic to their website, reducing readership. The second issue is that of memorization – this is a phenomenon where LLMs regurgitate their training data verbatim. GEMA v OpenAI (2025), a ruling of a Munich regional court, was also cited, where OpenAI was held liable for ChatGPT reproducing the lyrics of a song.
I argue that the search functionality of AI chatbots is still essentially non-expressive use, no different from the training process, and the regurgitation caused due memorization happens in most cases due to adversarial prompting, thus the user may be held liable in case they publish it (if not private/personal use exception might apply), and the AI developers are not liable, given that they have employed guardrails which are being circumvented by users. I further argue that secondary liability must also not be attributed to AI developers since these chatbots have substantial non-infringing uses and were not designed with an intent to infringe (barring situations where there is a lack of adequate guardrails, absent adversarial prompts).
The Web Search Functionality & RAG:
The training data of LLMs are updated periodically, which creates an information/knowledge gap in the interval…
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