Summary
On 7 August 2026, the Indian Patent Office issued Guidelines for the Use of Artificial Intelligence in Patent Examination Procedures. The Guidelines permit Examiners and Controllers to use AI for search support, classification, translation, language assistance, and drafting, while placing responsibility for verification, confidentiality, and final decision making on the human officer. They arrived at a time when courts had repeatedly set aside patent orders for want of independent reasoning and application of mind. Their success will therefore depend not merely on permitting AI, but on how the Patent Office controls the tools, records their use, discloses material assistance, and preserves genuine human judgment at every substantive stage of examination.
Introduction
On 7 August 2026, the Indian Patent Office issued the Guidelines for the Use of Artificial Intelligence in Patent Examination Procedures, with the objective of bringing order to a practice that had already begun finding its way into patent examination. The Guidelines identify permitted and prohibited uses, distinguish public AI tools from private systems, require Examiners and Controllers to exercise human oversight, and caution them against treating AI output as a substitute for their own judgment. As a first step, this is both necessary and sensible.
Patent examination, however, is not an ordinary administrative exercise in which technology can be introduced merely to save time or improve drafting. The search choices made by an Examiner influence the prior art placed against an application, the manner in which an objection is framed determines the case an applicant must answer, and the analysis of novelty and inventive step may decide whether the Patent Office grants or refuses a valuable statutory right. A Controller’s order may later come before a court, which will expect the order to disclose not only a conclusion, but also the reasoning and independent application of mind that led to it.
In this setting, an AI system does not merely assist with language or reduce the time spent on routine work. It may influence the search strategy used, the prior art identified as relevant, the technical material and analysis put forth, the objections raised, and even the reasoning that finds its way into an examination report or final order. When officers use such assistance carefully, AI may improve efficiency, speed, and consistency, but when they use it without adequate control, verification, or disclosure, the same AI may amplify arbitrary and unreasoned decision making, lower confidence in the patent office and its procedures, and harm the patent ecosystem.
The central question, therefore, is not whether the Patent Office should use AI, because its use has already begun and will almost certainly increase. The real question is how the Office can use AI without reducing accountability, consistency, procedural fairness, or the statutory duty of every Examiner and Controller to apply an independent mind. The answer will depend not merely on what the Guidelines permit, but on how the Patent Office consults stakeholders, controls the tools used by its officers, verifies substantive AI assistance, records material use, and makes that use sufficiently visible to those whose rights may be affected by it.
Stakeholders to the Table
Patent attorneys, applicants, inventors, research institutions, industry representatives, and members of the public do not merely observe the patent system from a distance. They prepare patent applications, respond to examination reports, attend hearings, challenge objections, and live with the consequences when an examination error affects the grant or refusal of a patent. Their experience places them in a strong position to identify the practical difficulties that may arise when the Patent Office uses AI for prior art searches, claim interpretation, inventive step analysis, translation, and the drafting of objections.
The Guidelines do not appear to have followed a public consultation process before their issuance. That fact may not, by itself, make them legally defective, because an administrative authority may issue internal guidance without undertaking consultation in every case. The nature of these Guidelines, however, makes consultation particularly important as they will influence the examination of thousands of patent applications, affect the manner in which officers use AI during substantive examination, and determine the information placed before applicants whose legal rights depend on the quality of that process.
The need for consultation also arises from the manner in which AI errors appear in practice. They may not always take the form of an obvious or dramatic failure. An AI tool may frame an overbroad search query, treat an irrelevant document as close prior art, mistranslate a technical expression, remove an important qualification while summarising a document, or produce a polished objection that does not answer the applicant’s submission. Patent attorneys and applicants may encounter these problems while prosecuting applications, and their inputs can help the Office identify such failure points before they become part of routine practice.
The Guidelines already provide for an AI Governance Committee, which may periodically review the framework and consult stakeholders and AI experts. The Patent Office should use that mechanism at the beginning of implementation rather than wait for difficulties to emerge after AI practices have become established. An initial consultation, followed by periodic review based on actual examination experience, would allow the Office to improve its framework without slowing the adoption of technology. It would also ensure that those who regularly engage with Patent Office reasoning through responses, hearings, appeals, and judicial proceedings have a meaningful role in shaping the system before avoidable problems take root.
Control the Tools
The Guidelines distinguish between public AI tools, which are freely or commercially available, and private AI tools that operate within restricted environments. This distinction serves an important purpose because officers must never place unpublished patent applications, confidential Office records, internal deliberations, or other protected material into public AI systems. Confidentiality, however, addresses only one part of the problem. The Patent Office must also know which AI system an officer used, what task the officer assigned to it, what model, version or service produced the output, and whether the Office can later trace and review that use.
If Examiners and Controllers may choose among several public and private AI systems without institutional control, officers handling comparable applications may receive materially different assistance, even when they ask similar questions. One system may generate useful search concepts, another may invent a technical relationship that the prior art does not support, and a third may analyse a document in a manner that removes the very distinction on which patentability depends. Differences in training data, retrieval methods, model design, system instructions, and update cycles may therefore influence examination, even though the applicant and the Patent Office may remain unaware of them.
Human verification remains essential, but the Office cannot rely on verification alone when it does not control the environment in which officers use AI. An officer may carefully check an output and still miss an error that arises from the manner in which the system retrieved, ranked, translated, or analysed information. Senior patent officers will also find it difficult to identify recurring errors, compare the performance of different tools, or investigate a disputed examination step when the Office has no reliable record of the system used and the work it performed.
The Patent Office should therefore create an approved and controlled architecture for AI use, instead of leaving officers to choose from an open field of products. It may adopt an approved list of tools, build a secure internal platform, or establish a controlled gateway through which officers access permitted AI systems. The precise technical arrangement may vary, but the governance result must remain clear: the Office should know the tool used, the model, version or service involved, the purpose for which the officer used it, and the record generated during that use.
Once the Office controls the tool environment, it can train officers more effectively, set common standards, review errors, compare performance, enforce confidentiality, and maintain a dependable audit trail. Building that structure at the beginning will prove far easier than attempting to reconstruct it after different AI systems, practices, and habits have become embedded across examination divisions.
AI and the Reasoning Problem
Over the last five years, courts have reversed and remanded several patent orders because Examiners and Controllers failed to engage with the material on record, answer the submissions made by applicants, or disclose the reasoning that connected the claims and prior art with the conclusion reached under the Patents Act. Those reversals and remands point to a deeper concern, namely that a patent order may state a conclusion without showing that the decision maker understood the claims, considered the prior art, answered the applicant’s submissions, and independently applied their mind.
AI now enters patent examination against this background. Generative AI systems can arrange facts, connect legal propositions, frame objections, and produce conclusions in language that appears clear, complete, and authoritative, even when the analysis beneath that language remains incomplete or incorrect. This creates a risk that is more difficult to detect than an ordinary drafting error. A poorly reasoned human draft often reveals its weakness through gaps, repetition, inconsistency, or confused language, whereas an AI generated draft may conceal the same weakness behind fluent sentences and an orderly presentation.
The problem, therefore, does not lie merely in the possibility that AI may produce a wrong answer. It lies in the possibility that AI may give a faulty and invalid analysis disguised as a reasoned decision. An officer working under time pressure may receive a polished draft that appears ready for adoption, even though it does not properly identify the relevant claim features, read the cited prior art as a whole, answer the applicant’s submissions, or explain how the material on record does not satisfy the statutory requirements. In such a case, drafting quality may pass for legal reasoning, and the form of a decision may replace the substance that the law requires.
The current Guidelines rightly require Examiners and Controllers to verify AI output independently before adopting it, but implementation must give real content to that requirement. Verification cannot stop with checking whether a cited document exists, correcting the grammar, or confirming that the draft reads well. Whenever AI assists with a substantive examination step, the officer must still understand the claims, identify the relevant technical features, study the prior art, consider the applicant’s response, and formulate the reasoning that connects the evidence with the conclusion under the Patents Act.
AI may help an officer organise and express that reasoning, but it cannot perform the statutory duty on the officer’s behalf. The more convincing the language produced by an AI system becomes, the more carefully the Patent Office must preserve this distinction. Unless it does so, AI will not correct the reasoning problem that courts have repeatedly identified. It will amplify that problem across more applications, at greater speed, and in a form that may be harder for applicants, supervisors, and courts to detect.
AI Disclosure and Audit Trail
The Guidelines take a useful step towards accountability by requiring officers to record material use of AI, including the name of the tool, the nature of the assistance, and the date on which it was used. They also contemplate a checklist and declaration through which the Examiner or Controller confirms that the tool was used only for permitted purposes, that its output was independently verified, and that the officer adopted the final work after applying an independent mind. These measures create an internal record, but an internal record alone does not tell the applicant whether AI influenced the objection, examination report, search report, or order that affects the application.
Whenever AI materially contributes to a substantive examination step, the Patent Office should disclose that contribution when it issues the document containing the AI assisted work. An applicant should not have to discover during an appeal or judicial proceeding that an AI system identified the prior art, framed an objection, analysed technical material, or generated language that entered the official record. Disclosure at the examination stage allows the applicant to understand how the Office arrived at its position, identify any error arising from the use of AI, and respond while the application remains under consideration.
A disclosure that merely states that AI was used will not serve this purpose. The disclosure should identify the tool and, where relevant, its version, state the task assigned to it, describe the documents or information supplied to it, preserve the prompt or instruction used, and record the output it produced. Where the officer used AI for prior art assistance, the record should identify the documents located through that process. Where the officer used AI for drafting, it should preserve the generated draft and state whether the Examiner or Controller accepted it, modified it, rejected it, or used it only as a starting point.
Confidentiality may require the Patent Office to restrict access to unpublished applications, internal records, or legally protected material, but confidentiality should not become a reason for concealing an AI contribution that materially affected the applicant. The Office can protect sensitive information while still disclosing the nature of the task performed, the role played by the AI system, and the manner in which the officer treated its output.
Disclosure to the applicant must operate alongside a complete internal audit trail. The Patent Office should securely retain the prompts, inputs, outputs, tool details, prior art results, generated drafts, and the officer’s treatment of those materials whenever AI materially influences examination. This record will allow supervisors and the AI Governance Committee to identify recurring errors, compare the performance of tools, review compliance, and reconstruct the examination process when an order is questioned.
The audit trail allows the Patent Office to supervise and investigate the use of AI, while disclosure allows the applicant to understand and answer the AI assisted work at the stage when it affects the application. Together, they give practical meaning to the Guidelines’ promise of human oversight by creating a record that shows what the AI did, what the officer verified, and how human judgment entered the final decision.
Closing Thoughts
The Guidelines for the Use of Artificial Intelligence in Patent Examination Procedures are a necessary and timely step. They recognise that AI has already entered patent examination and attempt to place some structure around its use, but the real test will begin with implementation, because rules that appear sound on paper may produce very different results when Examiners and Controllers use AI across thousands of applications involving different technologies, claims, prior art records, and legal issues.
The Patent Office can reduce that risk by involving stakeholders from the beginning, restricting AI use to a controlled and traceable tool environment, preserving the duty of every officer to apply an independent mind, requiring meaningful disclosure whenever AI materially contributes to an objection, examination report, draft, or order, and maintaining a complete audit trail that allows the Office to reconstruct how the AI system was used and how the officer dealt with its output.
None of these safeguards requires the Patent Office to resist technology or slow its adoption. They simply recognise that efficiency cannot become the sole measure of success in patent examination. A faster examination process will serve little purpose if applicants cannot understand how an objection arose, if supervisors cannot identify recurring errors, or if courts cannot determine whether the final decision came from independent statutory reasoning or from language generated by an AI system and later adopted without sufficient scrutiny.
AI can undoubtedly make patent examination more efficient, and in several areas, it may also improve consistency and reduce routine work. But the value of that assistance will depend on whether the Patent Office keeps the boundary between machine assistance and human decision making clear and visible. A sound beginning will remain sound only if that boundary does not disappear as AI becomes more deeply embedded in examination practice.
References
- Office of the Controller General of Patents, Designs and Trade Marks, Government of India, Guidelines for the Use of Artificial Intelligence in Patent Examination Procedures, published 7 August 2026, IP India – Download the Accessible Version Here.
Disclaimer
This article is based on the author’s personal understanding of the subject. Others may hold different opinions or understandings. This article is intended for general information and does not constitute legal advice. Readers should consult an attorney before acting on any legal issue. An AI application was used to generate parts of this article based on user inputs and prompts.
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