INTRODUCTION
The term “Artificial Intelligence” was introduced by John McCarthy in year 19561. As per the white paper released by Niti Ayog of India in 2018, “AI is a constellation of technologies that enable machines to act with higher levels of intelligence and emulate the human capabilities of sense, comprehend and act”2. The raid development in Artificial Intelligence (AI) have transformed the creation, distribution, and protection of digital content, has raised significant legal challenges in the jurisdiction of copyright and intellectual property right (IPR). AI tools can generate music, literature, artwork and even software, raising grave lawful questions concerning authorship, ownership and infringement. The Indian Copyright Act 19573, copyright protection is granted to the author of an original work. However the Act does not clearly distinguish AI as an author. Under Section 2(d) of Indian Copyright Act 1957, “Author” defines as 4
(i) in relation to a literary or dramatic work, the author of the work;
(ii) in relation to a musical work, the composer;
(iii) in relation to an artistic work other than a photograph, the artist;
(iv) in relation to a photograph, the person taking the photograph;
(v) in relation to a cinematograph film or sound recording, the producer; and
(vi) in relation to any literary, dramatic, musical or artistic work which is computer-generated, the person who causes the work to be created;
However Section 2(d)(vi)5 states that in the case of any literary, dramatic, musical, or artistic work that is computer-generated, the author shall be “the person who causes the work to be created.” Despite this insertion, the statute remains vague in addressing the difficulties introduced by modern generative AI systems, mainly where human involvement is minimal or indirect.
The Delhi High Court clarified the meaning of “author” in Camlin Pvt. Ltd. v. National Pencil Industries6, holding that a “mechanically reproduced printed carton” cannot be protected by copyright, because the author of such a work cannot be identified. The court clarified that only natural beings that produce original works are eligible for copyright protection. Because a carton created by mechanical reproduction is not an author’s creativity, the plaintiff cannot assert copyright over it. The court came to the conclusion that a machine cannot have copyright over an artistic work or be acknowledged as its author.
The provisions of acquiring copyright ownership are defined under the Indian Copyright Act 19577, under Section 178 of the Act. The right of ownership is available only if one qualifies the provision of this Act. There is no other remedy in other laws prevailing in India to counter the violation of copyright ownership. However, the act provides several exceptions where ownership shifts, reflecting contractual and employment relationship: Subject to the provisions of this Act, the author of a work shall be the first owner of the copyright there in: Provided that—
(a) in the case of a literary, dramatic or artistic work made by the author in the course of his employment by the proprietor of a newspaper, magazine or similar periodical under a contract of service or apprenticeship, for the purpose of publication in a newspaper, magazine or similar periodical, the said proprietor shall, in the absence of any agreement to the contrary, be the first owner of the copyright in the work in so far as the copyright relates to the publication of the work in any newspaper, magazine or similar periodical, or to the reproduction of the work for the purpose of its being so published, but in all other respects the author shall be the first owner of the copyright in the work;
(b) subject to the provisions of clause (a), in the case of a photograph taken, or a painting or portrait drawn, or an engraving or a cinematograph film made, for valuable consideration at the instance of any person, such person shall, in the absence of any agreement to the contrary, be the first owner of the copyright therein;
(c) in the case of a work made in the course of the author’s employment under a contract of service or apprenticeship, to which clause (a) or clause (b) does not apply, the employer shall, in the absence of any agreement to the contrary, be the first owner of the copyright therein;(cc)in the case of any address or speech delivered in public, the person who has delivered such address or speech or if such person has delivered such address or speech on behalf of any other person, such other person shall be the first owner of the copyright therein notwithstanding that the person who delivers such address or speech, or, as the case may be, the person on whose behalf such address or speech is delivered, is employed by any other person who arranges such address or speech or on whose behalf or premises such address or speech is delivered;
(d) in the case of a Government work, Government shall, in the absence of any agreement to the contrary, be the first owner of the copyright therein;
(dd) in the case of a work made or first published by or under the direction or control of any public undertaking, such public undertaking shall, in the absence of any agreement to the contrary, be the first owner of the copyright therein9.
In the context of higher education, where students, researchers, and faculty gradually rely on generative AI tools (e.g., ChatGPT, Gemini, or Perplexity) for drafting essays, research papers, theses, and creative assignments, these legal doubts interconnect with issues of academic integrity, ethical responsibility, and institutional accountability.
In higher education institutions (HEIs), AI tools facilitate personalized learning, data analysis, literature reviews, and content generation, enhancing efficiency and accessibility. However, their misuse such as submitting AI-generated text as original work without disclosure can constitute plagiarism or academic misconduct. This challenges the core principles of innovation and critical thinking that support academic pursuits. Faculty and students may inadvertently incorporate unattributed sources through AI “hallucinations” or biased outputs, further complicating attribution. Ownership disputes arise when AI-assisted works are produced: while the human user may claim authorship as the “causer,” minimal input (e.g., simple prompts) blurs the line, potentially rendering the work ineligible for full copyright protection if deemed insufficiently original.
NEP 202010 explicitly promotes the integration of emerging technologies, including AI, machine learning, and data science, into curricula at all levels to foster 21st-century skills such as critical thinking, creativity, problem-solving, and digital literacy. It advocates for AI in personalized learning, adaptive assessments, teacher training, and administrative efficiency, while establishing bodies like the National Educational Technology Forum (NETF) to guide ethical technology use.
However, NEP 2020’s emphasis on technology integration creates a tension with the unresolved legal and ethical challenges of AI-generated content. The policy encourages multidisciplinary research, holistic education, and innovation (e.g., through the National Research Foundation), but does not directly address authorship or ownership of AI outputs. In higher education, this gap is particularly evident: NEP promotes AI literacy and tools for research and teaching, yet widespread adoption risks amplifying plagiarism if students over-rely on generative AI without proper citation or human oversight.
To reconcile this, institutions must align NEP’s vision with robust academic integrity frameworks. The University Grants Commission (UGC)11 has responded by promoting AI use in research and teaching (e.g., recent approvals for AI in data analysis and projects, with mandates for citation and monitoring over-reliance), while extending anti-plagiarism regulations (2018) to cover AI-generated content. Mandatory AI ethics modules, disclosure requirements for AI assistance in submissions, and updated plagiarism detection tools (incorporating AI-content identifiers) are essential. This ensures that AI serves as a tool for augmentation rather than substitution, preserving human authorship under the Copyright Act while advancing NEP’s goals of ethical, inclusive, and innovative education.
To explain the practical implications of AI in authorship and ownership, particularly within the framework of the Indian Copyright Act, 195712, and its connection with higher education, the following case studies highlight key legal changes and differences. These examples underscore the ambiguities discussed earlier, where human involvement is pivotal for copyright protection, and the risks of academic misconduct arise from undisclosed AI use.
In Ankit Sahni v. Copyright Office, 2020–202113, Indian artist and programmer Ankit Sahni developed an AI tool called RAGHAV (Robust Artificially Intelligent Graphics and Art Visualizer). The AI generated an artwork titled “Suryast” by processing an input image through a modified version of an existing painting combined with AI algorithms. Sahni applied for copyright registration, listing himself and RAGHAV as co-authors.
The Indian Copyright Office initially granted registration, recognizing potential co-authorship. However, this was later withdrawn, as the Act requires human authorship under Section 2(d) of the India Copyright Act 195714. The office cited the lack of explicit provisions for non-human authors, aligning with precedents like Camlin Pvt. Ltd. v. National Pencil Industries15, which deny copyright to purely mechanical outputs without identifiable human creativity.
This case highlights the challenges for students and researchers using AI for creative assignments (e.g., digital art or design projects). If minimal human input is involved, the work may not qualify for copyright, potentially exposing it to unauthorized use. It also raises ethical questions: Should AI-assisted theses or artworks require disclosure to claim ownership?
Kaustubh Shakkarwar v. O.P. Jindal Global University 16
In 2024, LLM student Kaustubh Shakkarwar at O.P. Jindal Global University was accused of plagiarism after Turnitin’s AI-detection tool flagged his exam answers as “88% AI-generated,” leading to him failing the course. Shakkarwar filed a writ petition in the Punjab and Haryana High Court, challenging the university’s decision.
He argued that using AI does not constitute plagiarism under existing rules, as plagiarism requires copyright infringement of another’s work (citing R.G. Anand v. M/S. Delux Films17). Furthermore, invoking Section 2(d)(vi) of the Copyright Act, he claimed that even if AI was used, he as a person causing the work to be created retains authorship and ownership. The university’s rules lacked specific notification in the gazette for AI misuse as misconduct.
Relevance to Higher Education and NEP 2020: This is one of the first direct challenges to AI plagiarism detection in Indian academia. It exposes gaps in institutional policies amid NEP 2020’s push for AI integration (e.g., personalized learning and research tools). Without clear guidelines, over-reliance on detection tools risks unfair penalties, while undisclosed AI use undermines integrity. The case may influence UGC mandates for AI disclosure in submissions.
A. Research Problem
The Indian Copyright Act of 1957, the rapid use of generative AI in higher education has raised ethical and legal questions about authorship, ownership, and academic integrity. Modern AI-generated works with little human input are not sufficiently addressed by Section 2(d) (vi), which results in conflicting institutional practices and interpretations. Although NEP 2020 promotes the incorporation of AI, the lack of ethical rules and explicit disclosure raises the possibility of plagiarism disputes and compromises academic integrity.
B. Hypothesis
The Indian Copyright Act, 1957 is inadequate in clearly defining authorship and ownership of AI-generated academic works due to the absence of explicit legal recognition and regulation of generative AI systems.
C. Scope of Study
This study examines into the legal, social, ethical and technological challenges posed by generative AI, in the context of copyright law particularly Sections 2(d) and 17, in determining authorship and ownership of AI-generated academic works. It therefore, focuses on the tension between the human and non-human originality. It examines into the fact that whether there can be stability between promoting innovation and protecting original content. It also analyses the use of generative AI tools by students, researchers, and faculty members in higher education institutions and the following responsibilities to academic integrity, plagiarism, and ethical responsibility. It further explores the role of institutional regulations, including UGC plagiarism regulations and the policy vision under NEP 2020, in addressing AI-assisted academic practices.
D. Existing Legal Situation
The Copyright Act, 1957
• Section 2(d) defines the term “Author”- as follows; For literary, dramatic, musical, or artistic works (other than computer-generated): The person who creates the work (e.g., the writer, composer, artist).
• Section 2(d)(vi) states that in the case of any literary, dramatic, musical, or artistic work that is computer-generated, the author shall be “the person who causes the work to be created.
• Section 17 define the term “Ownership”- establishes that the “Author” is the first “Owner” of the copyright, subject to exceptions (e.g., works created in employment belong to the employer; government works to the government).
• National Education Policy, 2020.
• UGC(promotion of academic integrity and prevention of plagiarism in higher educational institutions) Regulations, 2018
• UGC 2025
GENERATIVE AI AND COPYRIGHT: AUTHORSHIP & OWNERSHIP IN HIGHER EDUCATION
The Indian Copyright Act, 1957 governs the copyright regime in India. Section 13 of the Copyright Act grants copyright protection on literary, dramatic, musical, and artistic work, cinematography film and sound recordings.18 AI tools can generally create literary, musical and artistic work. However granting Copyright protection on generated works depends upon various criteria, originality of the work and creativity of the author.
Copyright shall exist only over those works that are “Original.” A certain nominal customary of creativity shall have to be met and shall have to emerge from the author. Section 2(d)19 describes the author depending on the type of work. Generally, it is the person who has authored it. Particularly, however, Section 2(d)(vi)20 deals with computer-generated works. “In relation to any literary, dramatic, musical, or artistic work which is computer-generated, the person who causes the work to be created” shall be deemed the author.
However in the case of AI generated works; it is the AI itself that performs the work of persons who are recognised as authors. Therefore the aforementioned definition of the author cannot be applicable in the case of AI generated work.
It appears to forecast some form of computer-assisted creation, but it was before the time of modern generative AIs in the form of ChatGPT, Deep AI, Perplexity and other tools. It is a separate generated work by AI to produce an outcome based on a prompt that might require very little human programming, thereby giving rise to questions such as these: Does the prompt programmer “cause” the creation? Does it require very significant human involvement? The Indian view takes a more human-focused view on authorship and ownership (Section 17)21, giving it to natural/juristic persons only.
In 2020-2021, Ankit Sahni Vs Copyright-Office22.An Indian artist and programmer made an application under the Copyright Act for registration of an artwork artificially created through AI named “Suryast” (inspired from Van Gogh’s works and made through the software RAGHAV). It was first registered jointly listing AI as an author, but subsequently refused AI-authorship on the ground that an AI can never become an author. The copyright holder, though non-human, lost the status of an author.
In India till 2008 followed the “sweat of the brow” doctrine. The Supreme Court of India, in the case of D.B. Modak and Anorther Vs Eastern Book Company and orthers23., discarded the sweat of the brow doctrine and shifted to the modicum of creativity, i.e., the minimum of creativity. The court held that there must be some substantive variation in the work for it to be copyrightable. Therefore it is pertinent to note that when a work is created by AI independently, it fulfils the first essential condition that is it originates from the Author and skill and labour is also employed.
There has not been any significant judicial verdict clarifying the matter of authorship in terms of generative AI until December 2025. Cases such as ANI Media Pvt. Ltd. v. OpenAI Inc, (Delhi High Court, 2024) while a final decision has not yet been rendered which may revolve around several key legal findings by the judicial. That is the training of an AI model on copyrighted news content constitutes duplicate under Indian copyright law, fair dealing can be extended to AI training in the absence of explicit legislative guidance. Whether reproduction by generative AI is merely derivative, or if it is transformative adding new value or functionality that reinterprets the original journalistic work. Whether Indian courts have jurisdiction when the alleged infringement affects an Indian entity and its operations. The liability framework for AI-generated content that causes reputational harm24.
Ownership correlates with authorship (Section 17)25: The author automatically retains ownership unless it is produced under employment/commission. In the case of works created with the help of AI, if the human contributed “creative inputs” such as refinement, oversight, etc., they can be considered the authors. Simple inputs, such as “produce a landscape,” are probably not enough.
Context in Higher Education
“Generative AI is being used in higher education for essay writing, research summaries, coding, image creation, and even presentations.” This increases the challenges of authorship. Any student or faculty member using the AI application can end up with an output that does not contain enough human creative output to be eligible for copyright. Institutions can also lay claim to the output if it is done within the framework of employment by the institution (Section 17(c))26, but the plagiarism guidelines require that there be no unauthorized use of AI.
Section 5227 of the Copyright Act, 1957 outlines fair dealing for purposes of research, private study, criticism, or review that might apply for non-commercial education by AI. Publication for profit of scholarly outputs produced by AI (theses converted to book form) might be problematic, though. Using copyrighted examples of education (technical journals, textbooks) for training an AI raises infringement issues, although nothing is specifically exempted other than fair dealing.
Kaustubh Shakkarwar v. O.P. Jindal Global University 28., In 2024, LLM student Kaustubh Shakkarwar at O.P. Jindal Global University was accused of plagiarism after Turnitin’s AI-detection tool flagged his exam answers as “88% AI-generated,” leading to him failing the course. Shakkarwar filed a writ petition in the Punjab and Haryana High Court, challenging the university’s decision.
He argued that using AI does not constitute plagiarism under existing rules, as plagiarism requires copyright infringement of another’s work (citing R.G. Anand v. M/S. Delux Films29)., the Supreme Court emphasized that copyright protection must not allow the mere reproduction of ideas, but only their expression. AI generated content must be assessed on case to case basis to determine whether it merely imitates human creativity or produces genuinely new expressions that warrant legal protection. Furthermore, invoking Section 2(d)(vi) of the Copyright Act, he claimed that even if AI was used, he as a person causing the work to be created retains authorship and ownership. The university’s rules lacked specific notification in the gazette for AI misuse as misconduct.
While the government of India, Working on a Paper Generative AI and Copyright, ONE NATION ONE LICENSE ONE PAYMENT Balancing AI Innovation and Copyright30the Ministry of Commerce and Industry will review the Act through an expert committee that will investigate the issue of authorship, ownership, and copyright ability in AI-generated works. A working paper recommends provisions such as blanket licenses in regard to training data. There are as yet no changes.”
The government had previously claimed that existing laws were adequate and that rights were granted to the human that “caused” the creation.
In higher education, this lack of clear entitlement prevents the overuse of AI. Distrustful from the human contribution to AI work can have final products that are in the public sphere. In the Indian system that tries to balance innovation and the rights of creators, the courts may change the act to provide that a large measure of human creativity must be involved in AI.
In comparison, countries such as the UK have codified the existence of computer-generated works (author as arranger), while countries such as the US require human authorship. A middle ground can be found in India’s Section 2(d)(vi), which must be developed to account for the autonomous nature of Generative AI.
LEGAL AND ETHICAL CHALLENGES OF GENERATIVE AI IN HIGHER EDUCATION
In recent times AI technology tools such as ChatGPT, Gemini, Perplexity and others tools are proving that computers can recognize and pass around human language into higher education institutions (HEIs). In India the transformation of AI tools assisting in drafting, essays, summarizing literature, teaching, learning and research has been producing creative content.
The use of AI to write or even review academic work without the researcher’s own diligence and analytical effort could be considered as an act of dishonesty or cheating which could potentially violate academic ethics. Furthermore, in the context of employment, academic institutions and research institutions expect academics and researchers to use their intellect to produce academic works and develop knowledge in exchange for compensation as prescribed by their employment contracts. Ignoring AI-generated plagiarism may result in students and researchers lacking critical thinking and analytical skills, leading to an absence of new knowledge creation since academic works produced by the use of AI may be mere reformulations of existing data. Moreover, there is the issue of using the works of others without proper acknowledgement of the authors and information sources which poses significant legal challenges. Since AI offers more opportunities for academic misconduct, it is essential to consider the legal measures related to the use of AI in creating academic work and formulate clear standards and conditions for its use. This will help foster a better understanding of AI utilization without infringing copyright and without violating academic ethics and integrity31.
The National Education Policy 2020 focuses on the educational sector’s vision for a contemporary India and aspires to meet the quality education target outlined in the United Nations Sustained Development Goals for Education by 2030. Due to digitalization the Higher Educational Institutions are obligated to improve their education quality and performance time and again. The NEP advocates that the programs offered to students should cater to the needs of the industry that would in turn push them to be innovative32.
National Education Policy (NEP) 2020’s emphasis on technology-driven innovation they also introduce profound legal and ethical challenges. These challenges primarily revolve around academic integrity, plagiarism, authorship attribution, potential copyright infringement, institutional accountability, and the loss of critical thinking skills.
Legal Challenges
Plagiarism and Academic Misconduct: Students submitting AI-generated content as one’s individual work without disclosure is regularly seen as plagiarism or unfair resources. Plagiarism includes repetition from human sources, but AI outputs can copy styles, structures, or ideas from training data, leading to accidental overlaps. An AI detection tool which verifies the Plagiarism check streams high percentages of AI-generated text, but their accuracy is contested, raising issues of false positives and due process.
The landmark case of Kaustubh Shakkarwar v. O.P. Jindal Global University33 (2024–2025) illustrates this. An LLM student was initially failed for an exam submission flagged as “88% AI-generated.” The student challenged the decision in the Punjab and Haryana High Court, arguing that AI use does not constitute plagiarism (as it does not infringe another’s copyright) and invoking Section 2(d)(vi) of the Copyright Act, 1957, to claim authorship as the “causer” of the work. This case highlighted the gaps in institutional rules and the irregularity of tools, influencing calls for clear AI policies.
Authorship and Ownership Disputes: Under Section 2(d)(vi)34 and Section 1735 of the Copyright Act, 1957, the human “causing” the work is the author or owner. However minimal human input (e.g., simple prompts) may not meet the “modicum of creativity” threshold established in Eastern Book Company v. D.B. Modak (2008)36, possibly adaptation AI-heavy works disallowed for copyright. In academic contexts, this affects theses, research papers, and publications. If a student’s AI-assisted thesis lacks enough human creativity, it may enter the public domain, revealing it to misuse. Ability of using AI for publications face similar risks, especially if institutional claims arise under Section 17(c)37(employment works). Cases like Ankit Sahni v. Copyright Office38 (2020–2021) reinforce human-centric authorship, denying AI co-authorship.
Copyright Infringement in AI Teaching and Mechanism: Generative AI copies are qualified on vast datasets, often counting copyrighted academic materials (journals, books). This increases infringement claims under Section 51 of the Copyright Act, 195739, in Super Cassettes Industries Ltd Vs MySpace Inc40, the Delhi High Court held that online platforms must take active steps to stop copyright violations.
Institutional and Regulatory Gaps: UGC (Promotion of Academic Integrity and Prevention of Plagiarism in Higher Educational Institutions) Regulations, 201841, 2(l) defines the term Plagiarism- means the practice of taking someone else’s work or idea and passing them as one’s own42. However the UGC 2018 did not specify the pre-exist extensive generative AI, lacking specific provisions.
In September 2025, the University Grants Commission (UGC) announced a major policy shift, formally approving the use of AI tools in education for student projects with instructions for citation, disclosure, and nursing over-reliance. This decision comes after months of debate on whether AI-driven platforms enhance creativity or encourage dependency.
Comparative Table: UGC Guidelines Before and After September 2025
| Category | Earlier Policy | UGC Guidelines 2025 Updates |
|---|---|---|
| Use of AI in Projects | Not officially permitted | Allowed with proper citation |
| Teacher Training | No formal training | Mandatory AI integration workshops |
| Monitoring Committees | Not required | Universities must set up monitoring panels |
| Penalties for Misuse | Not clearly defined | Strict academic penalties introduced |
| Research Support | Limited AI involvement | AI encouraged for data analysis and coding |
This comparison shows how UGC guidelines have shifted from restriction to regulation, making AI tools in education more accessible. Source (Research Experts UGC Plagiarism Regulations 2018 – Latest Updates in 2025)
Ethical Challenges
Undermining Academic Integrity and Critical Thinking: AI generates a massive amount of academic content, which poses unique challenges to academia. It is essential to balance innovation and academic integrity this leads to adopting and creating new ethical standard guidelines to account for academic integrity and evaluate AI-generated research’s ethical and legal implications43. The use of Gen AI in academia has sparked debates, particularly concerning its role in producing writing outputs. Advocates see these tools as valuable aids for students and educators, enhancing efficiency and accessibility to resources. Critics however raise concerns about originality, ethical implications and the potential for over-reliance on AI-generated content44. Over-reliance on AI alternatives human effort, eroding skills like analysis, synthesis, and originality core to higher education. NEP 202045 promotes critical thinking and creativity, yet unchecked AI use risks producing “shallow” scholars. Ethical responsibility shifts: Students must disclose AI assistance, but vague boundaries (e.g., brainstorming vs. full drafting) create moral dilemmas.
Equity and Access Issues: AI tools exacerbate divides; privileged students access premium versions, while others rely on free/limited ones. Biases in AI (from training data) may perpetuate inequalities in outputs, affecting marginalized groups.
Attribution and Transparency: Failing to cite AI as a “tool” violates ethical norms of honesty. “Visions” (fabricated sources) mislead readers, compromising scholarly trust. Faculty using AI for teaching materials risk ethical lapses if undisclosed.
Broader Societal Implications: Widespread AI misuse devalues degrees, erodes public trust in academia, and stifles innovation by prioritizing efficiency over depth.
Emerging Responses and Recommendations
As of December 2025, India is addressing these through policy evolution: UGC’s 2025 approvals encourage ethical AI integration with disclosure requirements.
Department for Promotion of Industry and Internal Trade (DPIIT’s) working paper on generative AI proposes licensing for training data, indirectly impacting academic use.
Institutions are adopting AI ethics modules, updated plagiarism tools, and disclosure mandates.
To improve challenges:
• Mandate AI disclosure in submissions.
• Develop human-AI hybrid evaluation in written exams.
• Train faculty/students on ethical AI use.
• Amend Copyright Act for clearer AI provisions, balancing NEP’s innovation goals with integrity.
In conclusion, while generative AI boosts higher education, its legal doubts like (authorship, infringement) and ethical dangers, demand urgent, balanced frameworks. Without them, higher education institutions (HEIs) risk compromising the foundational values of originality and accountability that define scholarly pursuit.
JUDICIARY AND ADMINISTRATION: DEFINING AI AUTHORSHIP IN INDIAN EDUCATION
In India the “Copyright Act of 1957” presents its own set of hurdles in acknowledging AI-generated works. The Act provides copyright protection to human works, creating uncertainty for works generated solely by AI algorithms. While the European Union regards such works as under human ownership with appropriate oversight, India’s legal framework lacks clear provision, putting a closer evaluation of definitions of Author and work46.”
Adapting legal principles to developing AI mechanism is a persistent difficulty for the Indian Judiciary as technology improves. Currently copyright laws need to be construed and implemented in the context of rapidly changing technological environment. The judiciary can effectively navigate the complexities of AI involvement in copyright through proactive measures such as judicial guidelines, educational initiatives, and stakeholder engagement47.
Indian judicial and administrative responses to AI-generated works remain limited till now. The Copyright Act, 195748 emphasizes human centric authorship, with Section 2(d)(vi) attributing authorship of computer-generated works to “the person who causes the work to be created.” Courts and the Copyright Office interpret this strictly, requiring significant human creativity for protection. This approach directly impacts higher education, where students and faculty increasingly use generative AI for assignments, theses, and research.
Legislatively, India has not amended the Copyright Act to address AI, unlike countries like the UK. The 2019 Draft National E-Commerce Policy49 briefly mentioned AI’s impact on intellectual property but offered no concrete proposals. The absence of AI-specific provisions contrasts with India’s ambition to lead in AI innovation, as outlined in the NITI Aayog’s 2018 AI strategy50. Indian courts have not issued definitive rulings on generative AI authorship as of early 2026, but related cases provide insights.
In India, the judiciary has emphasized human intellectual effort as a prerequisite for copyright, in R.G. Anand v. Delux Films (1978)51, where the court held that originality requires a personal touch. AI-generated works challenge this notion, as the human role is often limited to providing a prompt, while the AI performs the creative synthesis. This disconnects between human input and AI output complicates the attribution of authorship and ownership52. Indian courts have not issued definitive rulings on generative AI authorship as of early 2026, but related cases provide insights.
Kaustubh Shakkarwar v. O.P. Jindal Global University53 (2024–2025, Punjab and Haryana High Court): An LLM student challenged his failure after Turnitin flagged his exam answers as 88% AI-generated. He argued AI use does not constitute plagiarism (absent direct infringement of another’s work) and invoked Section 2(d)(vi) to claim authorship as the “causer.” The university adopted a kind view, revising results to “Pass,” leading the Court to dispose of the petition, deeming remaining issues academic. This highlights institutional gaps in AI policies and reliability of detection tools, influencing calls for disclosure mandates in academia without resolving core authorship questions.
ANI Media Pvt. Ltd. v. OpenAI Inc54. (Delhi High Court, on-going since 2024): This focuses on input-side issues (training AI on copyrighted news) rather than output authorship. No final judgment by January 2026; hearings addressed jurisdiction, fair dealing (Section 52)55, and transformative use. It may indirectly shape views on AI outputs but does not directly address authorship in academic contexts.
No Supreme Court or High Court precedents specifically clarify generative AI authorship thresholds in education.
CONCLUSION
Once only humans were known for creation, invention and innovation, as time passed it has been replaced by the advance creativity which is known as Artificial Intelligence. It has given better efficiency than humans. The use of AI in creating works may involve literary, research, academic works has made humans works easy, but it is of those works which are copyright works of others without authorization, the issue of copyright protection and ownership of created work and the credit for its creation are matters of on-going debate. The relationship between education and technology is bidirectional as education enhances technological innovations and vis-a-versa technology improves the educational processes and outcomes. This paper has proved that the Hypothesis holds real that the (H-1)“Indian Copyright Act, 1957 is inadequate in clearly defining authorship and ownership of AI-generated academic works due to the absence of explicit legal recognition and regulation of generative AI systems”. Maintaining a balance between promoting AI innovation and safeguarding copyright holders’ rights is crucial as AI technology develops. To overcome these legal issues and support the development of AI in India, copyright laws must be modified, fair use in the context of AI is acknowledged, and strong governance structures be put in place.
Suggestions and Recommendations
• Amend The Copyright Act 1957: By giving clear provision to distinguishing between AI assisted and generated work defining the human creativity to qualify copyright protection and addressing Authorship/Ownership.
• Mandate of Disclosure of AI in Academic Submission: Students, Researchers and faculty have to disclose the AI assistance in their essays, theses, research paper and exams.
• Develop Institutional AI policies which creates clear framework for AI in teaching, learning and other methods
• Promote AI Literacy and Training: Introducing AI into education curriculum from school and higher education levels, with mandatory workshops for faculty and students on AI use.
• UGC and Regulations: UGC’s 2025 policy approving AI use with citation and monitoring requirements. Establish national guidelines for AI ethics in academia, including hybrid evaluation methods to assess human contribution.
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Footnotes
1. Who is the father of AI, https://raffle.ai/newsroom/who-is-the-father-of-ai (last Visited on 13.12.2025)
2. The white paper titled National Strategy for Artificial Intelligence’ https://www.niti.gov.in/sites/defaul t/files/2023-03/National-Strategy-for-ArtificialIntelligence.pdf (last Visited on 13.12.2025)
3. The Copyright Act, 1957, No.14 of 1957
4. Section 2(d) of Indian Copyright Act,1957
5. Section 2(d)(vi) of Indian Copyright Act.1957
6. Camlin Pvt. Ltd. v. National Pencil Industries AIR 1986 Delhi 444 (last Visited on 13.12.2025)
7. Supra Note 4, at 2
8. Section 17 of The Copyright Act, 1957
9. Supra note 9, at 3
10. National Education Policy 2020 Ministry of Human Resource Development Government of India.
11. UGC Plagiarism Regulations 2018 – Latest Updates in 2025 https://www.researchexperts.in/ugc-regulations-for-plagiarism/ (last visited on13.12.2025)
12. Supra Note 4, at 2
13. SURYAST U.S. Copyright office Review Board, December 11, 2023.
14. Supra note 5, at 2
15. AIR 1986 Delhi 444 (last Visited on 13.12.2025)
16. Kaustubh Shakkarwar v. O.P. Jindal Global University, Punjab and Harayana High Court CWP-29690-2024,
17. R.G. Anand Vs Delux Films (1978) 4 SCC 118
18. The Copyright Act, 1957, Section 13(1)
19. Supra note 5, at 2
20. Supra note 6, at 2
21. Supra note 9, at 3
22. Supra note 14, at 6
23. D.B. Modak and Anorther Vs Eastern Book Company, 2008 (1) SCC 1
24. COPYRIGHT IN THE AGE OF AI: A CASE COMMENT ON ANI VS. OPENAI, CS(COMM) 1028/2024 by Rajlatha Kotni (Partner), Swagita Pandey (Associate) and Anushka Tripathi (last visited on 30.12.2025)
25. Supra note 9, at 3
26. Section 17(c) of the Copyright Act, 1957
27. Section 57 of The Copyright Act, 1957
28. Supra note 17, at 7
29. R.G. Anand Vs Delux Films (1978) 4 SCC 118
30. Department for Promotion of Industries and Internal Trade Ministry of Commerce and Industry Government of India, https://www.dpiit.gov.in/static/uploads/2025/12/ff266bbeed10c48e3479c941484f3525.pdf (last visited on 30.12.2025)
31. Treeneat Sarapong, Noppanum Supasiripongchai, Patrawan Rattanakaset, Saowalak Sarapong and Nutt Sukavejworakiti, Copyright Law and the use of AI in academic works in the Thai Higher Educational Institutions, Journal of Intellectual Property Rights, Vol 30, November 2025, pp 776-786.
32. Meghna Aggarwal, Pramod Kumar, Seema Gupta and Ruby Mishra, Impact Assessment of NEP and IPR on institutes of Higher Education, Journal of Intellectual Property Rights Vol 29, March 2024, pp 12-126.
33. Supra note 29, at 13
34. Supra note 5, at 2
35. Supra note 9, at 3
36. Supra note 24, at 12
37. Supra note 27, at 13
38. Supra note 14, at 6
39. Section 51 of The Copyright Act, 1957
40. Super Cassettes Industries Ltd. v. MySpace Inc. 2011 (48) PTC 49 (Del)
41. UGC(promotion of academic integrity and prevention of plagiarism in higher educational institutions) Regulations, 2018, Notified on 23 July 2018.
42. Id
43. Priya Rai, Generative AI in Academia: Navigating Copyright and Intellectual Property Challenges. Indian Journal of Education Technology Volume 7, issue 2 july 2025,(last visited on 05.01.2025)
44. Brainerd prince, The evolving role of GenAI in academia, published in Education times newspaper on 17.11.2025,page no.4, www.educationtimes.com (last visited on 05.01.2025)
45. National Education Policy, 2020
46. Kinkini Mukherjee & Prashna Samaddar, The Role Of Indian Judiciary In Determining The Ambit Of Artificial Intelligence In Copyright, E- Journal of Academic Innovation and Research in Intellectual Property Assets, (E-JAIRIPA) Vol. V (ISSUE I) JAN -JUNE 2024, pg. 90-102( last visited on 05.01.2025)
47. Id
48. Supra note 4, at 2
49. National E-commerce Policy, 2019 – Draft, https://www.pwc.in/assets/pdfs/news-alert-tax/2019/pwc_news_alert_26_february_2019_national_ecommerce_policy_draft.pdf (last visited on 05.01.2025)
50. Asmi Vikas Kedare, The Impact Of Generative Ai On Copyright Law In India: Who Owns Ai-Created Works?, Indian Journal of Integrated Research in Law Volume V Issue III | ISSN: 2583-0538 (last visited on 05.01.2025)
51. R.G. Anand Vs Delux Films (1978) 4 SCC 118
52. Id Note 53
53. Supra note 29, at 13
54. copyright in the age of ai: a case comment on ani vs. openai, cs(comm) 1028/2024 by Rajlatha Kotni (Partner), Swagita Pandey (Associate) and Anushka Tripathi (last visited on 30.12.2025)
55. Section 52 of the Copyright Act, 1957