The law currently provides creators exclusive rights over their creation for a limited time, which gives a human inventor or author a reason to invent or do the work. The harder question is what happens to it when the creator is a machine. This article looks at agentic artificial intelligence, meaning systems that set their own goals, plan, use tools and act with little human supervision, and asks whether the speed of their spread points to a new generation of intellectual property theory.
I. The unstated assumption
Reward an inventor or writer with an exclusive period, and the reasoning is that she or he will be motivated enough to pursue expensive projects knowing that others cannot profit from them without paying the inventor first. This is sound reasoning based on an unstated premise, namely that a human is the creator, and the motivation is supposed to spur him or her to action. What happens when we take away the human?
Agentic AI does not give the law a fresh reason to grant exclusive rights. What it does, and faster than anything before it, is push along a change already under way. The spread of a technology, its diffusion, has grown from a side effect of the incentive system into a test that now sits beside it. The strain shows up in two ways. The gap between an invention and its uptake, which diffusion scholars spent decades measuring, has nearly vanished. Technology diffusion is now super-fast with new systems reaching users worldwide in days rather than in decades. Since agentic AI is a general purpose way of inventing, what spreads is not just a product but the ability to invent itself. The early reactions of the existing intellectual property system, rules out any form of machine invention or machine authorship in the Thaler litigation. This indicates the pressure placed on the human foundation during this period of rapid diffusion.
Agentic artificial intelligence challenges that quiet assumption. The term covers a system that makes a goal, breaks it into steps, decides its own next moves, reaches for tools such as a web browser, a piece of code or a software interface, and adjusts as it goes, with a person checking in only occasionally. Systems like this are entering everyday life faster than anything in the historical record, and they do so while the thing producing their output is not a human person but an agentic AI device.
The question is whether the recent rapid technology diffusion, the shift captured in the World Intellectual Property Organization’s 2026 flagship report, marks the start of a new generation of intellectual property theory. This perspective signals a shifting balance, in which diffusion has come to be seen as a measure that is alongside the measure of incentive rather than subordinate to it. The agentic technology doing most to unsettle the standard norms of patenting, by cutting invention loose from any human the law can reward, is also the one spreading fastest. This incentive paradigm and the human at its centre need to be examined and also what all this means for India and the Global South.
Exclusive rights give the innovator some control and thus an incentive to invest. This traditional view represents the innovation as a trade-off: the cost of the monopoly, along with the losses to all those who, otherwise, could buy it cheap, is compared with the invention which the promise of monopoly inspires. Patents refer to this entity as an inventor, while copyrights refer to them as authors. Both mean a living person. The belief is that there is a person in place during the act of creation who will react to this offer of an incentive. Agentic AI attacks that assumption from both sides. On the one hand, the invention is accomplished through a true technological breakthrough, without any human deliberation involved. Hence, there may be no person whose creative effort can justly be recognized by the patent or copyright reward system. On the other hand, the invention appears to resemble a tool, and the issue becomes how much contribution on the part of the human operator needs to be present to qualify as the inventor or author under the patent law or copyright law. These two issues arise the moment the agentic AI tool itself begins to plan, choose, and adapt.
Three lines of change are suggested. Firstly, lawmakers can give the diffusion goal for agentic AI inputs a clear statutory form, so that human ownership of the data, models and computing power on which agentic AI depends, and of its outputs, is clear. Secondly, courts and IP offices may address how much human involvement is needed in work specifically created with the help of agentic AI. Thirdly, the accountability gap calls for a clear allocation of responsibility for autonomous action by agentic AI.
Lakshmidevi Somanath is Partner – Litigation & Strategy at Anand and Anand, India and a PhD Scholar (Working Professional) at IIT Kharagpur, India. She formerly served in the Intellectual Property Appellate Board, Government of India as a Member Judge.