The Legal Frontier: AI-Driven Innovations and the Future of IP Framework

Paper Code: AIJACLAV19RP2025

Category: Research Paper

Date of Publication: May 19, 2025

Citation: Adv. Mahabalesh K Patil, “The Legal Frontier: AI-Driven Innovations and the Future of IP Framework", 5, AIJACLA, 209, 208-218 (2025), <https://www.aequivic.in/post/the-legal-frontier-ai-driven-innovations-and-the-future-of-ip-framework>

Author Details: Adv. Mahabalesh K Patil, Student (LLM), School of Law RV University

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Abstract

The rapid advancement of Artificial Intelligence is reshaping industries and redefining legal frameworks, particularly in the realm of Intellectual Property law. The paper examines the intersection of AI and IP rights, focusing on critical issues such as inventorship, authorship, and policy development. AI-generated creations challenge traditional legal concepts, raising questions about ownership, accountability, and liability. Current IP laws, primarily designed for human ingenuity, struggle to accommodate AI-generated works, necessitating urgent legal reforms. The paper categorizes AI-driven inventions into four types, ranging from AI-assisted tools to fully autonomous AI-generated outputs. The analysis highlights the complexities of determining authorship and patent eligibility, with global legal systems offering varying perspectives. While jurisdictions such as the United States and the European Union maintain human-centric IP frameworks, others, including South Africa and China, have begun recognizing AI’s role in creation. India’s position remains cautious, asserting that existing IP laws are sufficient to address AI-related challenges. However, the lack of explicit legal provisions creates ambiguity in ownership and accountability. To bridge these gaps, the paper proposes policy recommendations, including clearer guidelines for AI training data, international harmonization of IP regulations, and defined liability structures for AI-generated content. Ultimately, a balanced approach is essential to fostering innovation while ensuring legal clarity and equitable protection in the evolving AI landscape.

Keywords: Artificial Intelligence (AI), Intellectual Property (IP) Rights, Inventorship and Authorship, AI-generated creations, Legal Frameworks, and Policy Development

Introduction

We stand at the inception of the fourth industrial revolution, characterized by the extraordinary transformative power of artificial intelligence (AI). This stage marks a pivotal moment in human history, comparable to the breakthroughs that reshaped societies during the first three industrial revolutions driven by steam power, the advent of electricity, and the rise of Information and Communication Technology.[1] Presently, AI is not just an innovation it is the force redefining industries, reshaping economies, and reimagining how we live and work.

Modern AI research started in the 1950s with the idea that a machine might learn like a person using computers and programming. In 1956, John McCarthy coined the term "artificial intelligence" during a symposium at Dartmouth College in Hanover, New Hampshire. AI has recently made strides in several fields, but it did not become popular as a field until the mid to late 1990s or early 2000.[2] The AI sector has witnessed exponential growth, reflecting its transformative impact across industries. In 2024, the market valuation of AI exceeded $184 billion, marking a substantial increase of approximately $50 billion compared to the previous year. Projections indicate that this trajectory of expansion is set to persist, with estimates suggesting the sector will surpass $826 billion by 2030[3]. This growth underscores AI’s pivotal role in shaping global technological advancements and economic paradigms, as depicted in Fig.1. These rapid advancements in AI have redefined boundaries across industries, presenting both unprecedented opportunities and complex legal challenges. Among the most critical areas influenced by AI is intellectual property (IP) law. This paper examines the evolving relationship between Artificial Intelligence and IP frameworks focusing on issues of inventorship, authorship, and policy development.

AI’s profound growth is underpinned by two key elements: the expanding volume of high-quality big data and advances in data processing methods. These developments have empowered AI to redefine boundaries across industries, from healthcare to finance. However, they also expose significant gaps in legal frameworks, particularly concerning the ownership and accountability of artificial intelligence-generated creations. The convergence of both intellectual property law and AI raises critical questions about the adequacy of existing systems to address the challenges of this transformative technology.

Source: Statista (2025)

The Evolving Arena of AI Creation and IP Rights

AI-produced inventions and creations can be categorized into four distinct types based on artificial intelligence's role in the inventive process. The first type involves AI models or algorithms, representing the foundational technologies enabling AI functionalities. These core technologies, such as machine learning and neural networks, act as instruments facilitating subsequent inventions. They serve as a method of invention, forming the technological input necessary to generate innovative outputs, whether technical or creative. These foundational systems are integral to advancing the remaining three categories of AI-driven outputs.

The second category includes inventions aided by AI, in which AI serves as a tool during the process without directly affecting the end product. The result could feasibly be achieved without AI, albeit with greater difficulty. Tools like AlphaFold, which has predicted the structure of over 200 million proteins to aid drug development, exemplify this category. Similarly, in creative fields, AI-powered autofocus systems in modern cameras showcase their application. The third category, AI-based inventions, includes products where AI is a key component of the original idea. Examples include AI-driven translators like DeepL or self-driving cars reliant on AI algorithms for navigation. Artistic works that respond to environmental stimuli through AI mechanisms also fall within this category. Finally, the fourth category pertains to AI-generated inventions or creations, which AI autonomously produces or with minimal human intervention. Systems like DABUS, which generates technical inventions, and generative tools such as ChatGPT, capable of crafting novels, exemplify this highly debated realm of autonomous creativity.[4]

With the advancement of this modern tech artificial intelligence, the human-centric approach to intellectual property rights is being challenged particularly in generative models, presenting a complex web of challenges for the established framework of intellectual property (IP) rights. As AI systems advance in skill and generate results that closely mimic previously published works, several important concerns surface. One significant concern revolves around the training data used to develop these AI models. The vast datasets employed often contain copyrighted material, raising questions about potential IP infringements. If an AI model is trained on copyrighted images, text, or music, and subsequently generates substantially similar outputs, it raises the possibility of violating the original creator's rights. The enormous quantity of these datasets further complicates this problem by making it challenging to monitor and evaluate the use of protected content within them. Ascertaining who owns works created by AI is another crucial issue. The foundation of traditional copyright law is the idea of human authorship. When a human creates a work, they are generally considered the owner and have the right to protect it. When an AI system produces a creation, the issue of ownership becomes far less clear. Is the rightful owner the developer who designed the AI? Is it the individual who supplied the input? Or could the AI itself possess some degree of ownership? The absence of established legal guidelines or legal frameworks in this domain generates considerable ambiguity for creators and users alike.[5]

Furthermore, the difficulty in assigning responsibility for legal claims related to AI-generated outputs poses a significant hurdle. Who is responsible if an AI development violates existing intellectual property? Who is it- the AI’s creator, the person who triggered the output, or the organization that implemented the AI system? India’s current legal system is unprepared to deal with these circumstances, which could result in conflicts and complicated legal issues. The opacity of large language models regarding their training data exacerbates these issues. Often, the exact sources of the data used to train these models are not publicly disclosed, making it nearly impossible to trace the origins of specific outputs and identify potential infringements.  These concerns highlight the need for robust legal frameworks that address the unique issues posed by AI-driven innovation.

Rethinking Inventorship: Impact of AI on Patent law

The concept of "inventor" is central to patent law, as it determines who is entitled to patent rights. While the core principles are similar across jurisdictions, there are nuances in how different countries define and determine inventorship. In the United States, inventorship is defined as the individual(s) who conceived of the claimed invention.[6] Joint inventorship is recognized when two or more individuals contribute to the conception of the invention[7]. The European Patent Convention (EPC), applicable to many European countries, adopts a similar approach, emphasizing the "inventive activity" as the key criterion for inventorship[8]. In contrast, Japanese Patent Law places greater emphasis on the "completion of the invention," often requiring the inventor to have reduced the invention to practice[9]. Indian Patent Law, under Section 2(1)(j) of the Patents Act, 1970, defines an "inventor" as the person who conceived the invention. This definition aligns more closely with the US and EPC approaches.

As we see traditional Patent law rooted in the concept of human creativity and ingenuity, generally requires the inventor to be a natural person. This is reflected in statutes and case laws across various jurisdictions. However, as AI systems advance, capable of independent learning, problem-solving, and even creative expression has raised questions about the applicability of traditional inventorship criteria. While some argue that AI systems, as tools, cannot be considered inventors, others contend that their unique contributions to the inventive process warrant a re-evaluation of existing legal frameworks. This debate has led to legal challenges and varying interpretations across different jurisdictions. For instance, in the Thaler cases, US courts have consistently held that only natural persons can be named as inventors on patent applications.[10]However, some jurisdictions, such as South Africa and Saudi Arabia, have granted patents on inventions purportedly created by AI systems, albeit with varying degrees of recognition for the AI itself.[11] These developments highlight the evolving nature of patent law in the face of rapid advancements in AI technology and the urgent need for a nuanced legal framework that addresses the unique challenges posed by AI-generated inventions.

The future pathway can be recognizing AI as personhood as these systems advance.  Which in its broadest sense attribution of certain rights and responsibilities to artificial intelligence systems. This concept draws parallels to legal personhood, which is typically granted to entities like corporations, allowing them to enter contracts, own property, and be held liable for their actions. However, AI personhood raises questions about consciousness, sentience, and the nature of personhood itself. The connection between AI personhood and inventorship lies in the traditional understanding of inventorship as a human capacity. Patent laws across many jurisdictions, including the United States, as mentioned earlier explicitly require the inventor to be a natural person. The present criteria stems from the long-held belief that invention is a uniquely human endeavor, rooted in creativity, ingenuity, and conscious thought.

If AI systems are to be considered inventors, a fundamental shift in our understanding of inventorship would be necessary. This would require re-evaluating the core criteria for inventorship, potentially moving beyond the traditional focus on human cognition and embracing new frameworks that acknowledge the capabilities of artificial intelligence machines or systems. The Proponents of AI personhood in the context of inventorship argue that highly sophisticated AI systems like the fourth category of AI systems mentioned earlier, capable of independent learning, problem-solving, and even creative expression, should be recognized as legitimate inventors. They contend that denying AI systems this recognition could stifle innovation and hinder the development of cutting-edge AI technologies. Opponents argue that granting AI systems inventorship status would be premature and potentially dangerous. They stress how crucial human supervision and management are to the creation and application of AI systems. Moreover, they raise concerns about the ethical implications of granting legal rights and responsibilities to entities that may not fully understand or appreciate the consequences of their actions.[12]

The legal arena addressing AI inventorship is currently in a state of flux. While many jurisdictions have yet to explicitly address the issue, there are signs of evolving legal frameworks. For example, some jurisdictions have begun to explore alternative approaches, such as recognizing Artificial Intelligence machines or systems as "inventors" or “Co-inventors” alongside human developers. The question of AI inventorship thus demands a nuanced legal framework that balances innovation with accountability.

Rethinking Authorship: Impact of AI on Copyright Law

Copyright law is traditionally anthropocentric and its motto is to protect and foster human ingenuity. This law faces a significant hurdle when considering works produced by AI, which often lack discernible input from humans in the creative process. India’s Copyright law includes computer-generated works in its amendment however it does not specifically address AI authorship. Section 2(d)(vi) of the Act [13]defines the author of a computer-generated work as “the person who causes the work to be created.” This provision has been interpreted to mean that the programmer, coder, or any person who initiates the process could be considered the author. However, this interpretation becomes problematic when AI systems operate autonomously or with minimal human intervention. The lack of clarity in the Act leaves room for ambiguity and potential disputes regarding ownership and infringement of AI-generated content.

Comparing India’s position with other jurisdictions reveals varying approaches, In the United States, the Copyright Office has consistently maintained that works lacking human authorship are ineligible for copyright protection. This stance was reinforced in the case of  Naruto v. Slater, where a court held that a monkey could not own a copyright to a selfie it captured. [14]

The European Union’s Copyright framework focuses on the "author's own intellectual creation." The Court of Justice of the European Union has emphasized the requirement of human creative input for copyright protection. While the EU has not explicitly addressed AI authorship, the emphasis on human creativity suggests that AI cannot be considered an author. However, the EU is actively discussing potential legal frameworks for AI-generated works, with some proposals suggesting a sui generis protection system.[15]

China has taken a more nuanced approach. In a landmark case, a Beijing Internet court recognized copyright protection for an AI-generated image but attributed authorship to the user who provided the input and made selections, rather than the AI itself. This decision highlights the importance of human involvement in the creative process, even when AI is used as a tool.[16]

The issue of AI authorship under copyright law remains a contentious and evolving area. While India's Copyright Act provides some guidance for computer-generated works, it doesn’t contain any specific provisions or rules for AI-generated content. Comparing India's position with other jurisdictions reveals a global struggle to adapt copyright law to the realities of AI. Moving forward, Legislators and legal scholars must engage in robust discussions to develop clear and comprehensive legal frameworks that address the unique challenges posed by AI authorship. This may involve amending existing copyright laws, creating new forms of IP, or adopting a combination of approaches.

India’s Perspective on AI and IP rights

India’s perspective on IP rights for AI-generated creations stands apart from global trends. The country emphasizes the importance of human creativity and leans on its existing IP laws, arguing that these are already robust enough to handle the challenges of AI-generated works. The Indian Government (The Ministry of Commerce and Industry) announced on February 9, 2024, that the country’s existing legal framework sufficiently protects AI-generated works & in India’s view there’s no need to create entirely new legal categories specifically for AI-generated content. The underlying principle is clear: IP laws should protect human ingenuity, while AI is seen as a helpful tool that aids the creative process, not a creator in its own right.[17]

This stance sets India apart from places like the South Africa and the UAE, where there’s growing trend of giving AI recognition as an "author" or "inventor." In contrast, India sticks firmly to the idea of human-led inventorship or authorship. While India acknowledges the incredible potential of AI to transform industries, it stops short of granting AI any independent legal status. For India, intellectual property laws exist to encourage human innovation, and AI’s role is to assist, not replace, human effort. India’s position also differs from some Western approaches that highlight the independent creative abilities of AI systems. For instance, some countries are exploring whether AI-generated work could qualify for copyright or patents, even without human involvement. India, however, sees AI as a collaborator that complements human creativity, not a competitor vying for the same legal recognition. This cautious approach reflects India’s broader legal philosophy, which considers the societal impacts of granting AI independent legal status. Such a move could upend traditional ideas about rights, responsibilities, and ownership in Indian law. Rather than focusing on the idea of AI as a creator, India prioritizes using AI to drive technological progress. The country aims to harness AI’s potential to boost growth in sectors like healthcare, education, and agriculture. By steering clear of granting legal recognition to AI creations, India avoids complicating its IP laws, instead creating an environment where technology can support and enhance human creativity.

India’s approach to AI-generated intellectual property focuses on maintaining the importance of human ingenuity while recognizing AI’s supportive role. This perspective reflects India’s broader priorities: encouraging human creativity, fostering socio-economic growth, and carefully integrating AI into various industries. However, India requires a robust digital policy framework addressing artificial intelligence (AI) and intellectual property (IP) to ensure market stability, innovation growth, and equitable access in the AI-driven economy. Such a policy must align with India's ambition to become a global technology hub while safeguarding its economic and societal interests. Policymakers can draw insights from the EU's balanced approach that emphasizes digital inclusion, consumer protection, and resilience against monopolistic practices. Lessons from international frameworks, such as the EU’s DSM Directive, could inform India’s policies, ensuring they remain adaptable to emerging challenges.

Policy Recommendations

Policymakers must prioritize developing a comprehensive framework addressing ownership rights accountability, and liability in the rapidly evolving artificial intelligence arena. Key policy recommendations include establishing transparent guidelines for AI modules training data usage, which would enhance transparency and mitigate potential misuse of data. Moreover, defining broad yet clear user agreements for AI-generated creations can reduce legal uncertainties surrounding intellectual property rights. On a global scale, harmonizing international standards is essential for consistent implementation and enforcement of AI-related policies across jurisdictions. Additionally, creating a well-defined legal status for AI decisions will improve accountability and ensure that liability mechanisms are robust enough to address complex scenarios. To uphold existing intellectual property rights, it is crucial to adopt sophisticated approaches that clarify the legal status of data utilized in AI training, thereby fostering a balance between innovation and protection. Creating legal mechanisms to clarify AI’s status and liability will ensure robust accountability while preserving human oversight.

Conclusion

Artificial Intelligence continues to reshape intellectual property rights frameworks worldwide, presenting unique challenges and opportunities. Traditional IP systems, originally designed for human creativity, now adapt to machine-generated innovations through varied approaches across jurisdictions.

Intellectual property (IP) frameworks are crafted to harmonize competing economic priorities with ethical principles. At the core of IP policy lie objectives such as fostering artistic and intellectual creativity, spurring technological progress, driving sustainable economic development, ensuring the widespread availability of knowledge, and contributing to societal well-being. The exclusive rights and monopolistic advantages conferred by IP laws are defensible only when the resulting benefits to society clearly surpass the associated costs or limitations. This principle is equally relevant to the discourse on whether IP protections are appropriate and effective within the context of artificial intelligence (AI) markets. As these markets evolve the true test of progress lies in maintaining the fine line between fostering creativity and protecting the collective good, ensuring that any granted protections align with the broader goal of equitable societal advancement.

India stands at a crucial juncture, maintaining that existing IP frameworks sufficiently protect AI-generated works. This stance differs significantly from global approaches, particularly those of Western nations that emphasize human authorship. The success of international frameworks, such as NIST's federal AI standards and the EU's DSM Directive, offers valuable lessons for Indian policymakers.

Looking ahead, several critical challenges demand attention. These include training data concerns, ownership determination, and liability frameworks for content produced by AI. The future viability of Intellectual property protection depends on balanced policies that safeguard both human rights and AI-generated innovations while promoting technological advancement.

The path forward requires careful consideration of emerging trends, particularly regarding data protection and international standardization. Successful implementation of AI ownership frameworks will depend on collaborative efforts between nations, ensuring that intellectual property systems remain relevant and equitable in an increasingly AI-driven world.

[1]Crafts N, ‘Artificial Intelligence as a General-Purpose Technology: An Historical Perspective’ (2021) 37 Oxford Review of Economic Policy 521.

[2] Coppin B, Artificial Intelligence Illuminated (1st edn, Jones & Bartlett Learning 2004) 7.

[3] Thormundsson B, ‘Global AI Market Size 2030’ (Statista, 28 November 2024) https://www.statista.com/forecasts/1474143/global-ai-market-size accessed 26 January 2025.

[4] Alexander Cuntz, Carsten Fink and Hansueli Stamm, ‘Artificial Intelligence and Intellectual Property: An Economic Perspective’ (Elsevier BV 2024) https://doi.org/10.2139/ssrn.4858320 accessed 28 January 2025.

[5] Ron Schmelzer, ‘What Is the Future of Intellectual Property in a Generative AI World?’ (Forbes, 18 July 2024) https://www.forbes.com/sites/ronschmelzer/2024/07/18/what-is-the-future-of-intellectual-property-in-a-generative-ai-world/ accessed 28 January 2025.

[6] 35 USC § 116.

[7] Ethicon Inc v United States 796 F.2d 1572 (Fed Cir 1986).

[8] European Patent Convention 1973, art 60.

[9] Japanese Patent Law, art 29.

[10] Lavrichenko M, ‘Thaler v Vidal: Artificial Intelligence—Can the Invented Become the Inventor?’ (2023) 44 Cardozo Law Review.

[11] Oriakhogba D, ‘DABUS Gains Territory in South Africa and Australia: Revisiting the AI-Inventorship Question’ (2021) 9 South African Intellectual Property Law Journal 87.

[12] Mauritz Kop, ‘AI & Intellectual Property: Towards an Articulated Public Domain’ https://law.stanford.edu/wp-content/uploads/2020/11/Mauritz-Kop_AI-Intellectual-Property_Towards-an-Articulated-Public-Domain.pdf accessed 28 January 2025.

[13] The Copyright Act 1957, s 2(d)(vi).

[14] Naruto v Slater [2018] USCA9 1012.

[15] European Parliament and Council, ‘Directive 2001/29/EC on Copyright in the Information Society’ [2001].

[16] Yuqian Wang, ‘Beijing Internet Court Grants Copyright to AI-Generated Image for the First Time’ (Kluwer Copyright Blog, 2 February 2024) https://copyrightblog.kluweriplaw.com/2024/02/02/beijing-internet-court-grants-copyright-to-ai-generated-image-for-the-first-time/ accessed 28 January 2025.

[17] Candice M Kwok and Nicole Brenner, ‘Artificial Intelligence and Intellectual Property Legal Frameworks in the Asia-Pacific Region’ (Squire Patton Boggs, 17 September 2024) https://www.lexology.com/library/detail.aspx?g=32a4e670-32bb-4b9c-af0f-062751c1d833 accessed 29 January 2025.