By SSR Patent Team
The Office of the Controller General of Patents, Designs and Trade Marks (CGPDTM) has issued Guidelines for the Use of Artificial Intelligence in Patent Examination on August 11, 2026. The document is notable less for what it permits than for the discipline it imposes. It treats artificial intelligence as an instrument of assistance and refuses to let it stand in for the statutory and quasi-judicial functions of the Examiner and Controller. For practitioners, the interest lies in the granularity: the Guidelines catalogue, in unusual detail, both the tasks for which AI may be deployed and the failure modes that make independent human verification indispensable.
What the Guidelines Are — and Why They Matter Now
The Guidelines sit within a wider Government of India posture on responsible AI — they expressly invoke the NITI Aayog Responsible AI approach — and translate that posture into the specific setting of patent examination, a function the document rightly describes as document-intensive, technically complex, legally evolving and time-sensitive. Their stated object is to support efficiency and quality while preserving confidentiality, accountability, consistency and the independent application of mind. Their scope extends across screening, classification, search, translation support, drafting support, technical comparison and knowledge retrieval.
Two structural features repay attention. First, the Guidelines distinguish public AI tools — general, consumer-facing systems trained on broad datasets — from private AI tools operating in closed environments, and record that the Patent Office’s subscribed search databases already carry in-built private AI better suited to the patent context. Second, they are candid about limitation: an entire section enumerates fourteen distinct risks, from hallucination and omission of critical detail to classification drift, black-box opacity and bias in training data.
|
Prosecuting or defending a patent in India? The texture of examination is changing. Our patents team can advise how these Guidelines bear on a live application or a pending opposition. Speak to us before your next response falls due. |
The Central Principle: AI May Assist, It Cannot Adjudicate
The organising idea is a line between assistance and adjudication. AI is positioned to assist, and not replace, the Examiner or Controller. Any AI-assisted output that could influence search or examination must undergo manual review and validation. Critically, the officer remains fully responsible for every official act involving AI, and the Guidelines state in terms that the use of AI does not dilute or transfer that responsibility. An AI output may be adopted only after the officer is personally satisfied as to its correctness, relevance and appropriateness.
For a practitioner, that principle is not merely aspirational. It is the standard against which an AI-influenced office action can be measured. If a First Examination Report rests on a classification, a prior-art mapping or a citation that the officer has not independently verified, the Guidelines supply the vocabulary — and the internal benchmark — for saying so.
Where AI Is Permitted — and the Strings Attached
The Guidelines set out twelve typical uses, each paired with its risks and mandated safeguards. The pattern is consistent: AI may accelerate the preliminary work; the officer must own the conclusion.
Classification, Search and Prior Art
AI may suggest candidate IPC/CPC classifications, generate search vocabulary and concept clusters, and — through the Office’s subscribed private tools — assist with prior-art retrieval. The Annexure demonstrates, with worked examples, that classification output is model-, prompt- and parameter-sensitive: the same claim run through different tools produced materially different, and sometimes irrelevant, classifications. The safeguard is verification against authenticated IPC/CPC sources and a considered reading of the claims with the complete specification. Final search results, the Guidelines insist, must be selected on the officer’s independent judgment rather than accepted from the system.
Claim Analysis, Novelty and Inventive Step
AI may extract claim features and offer preliminary novelty or inventive-step mapping — but this is the category the Guidelines treat with the most caution. A worked example is instructive: the same claim and the same prior art, put to the tool under differently framed prompts, yielded confident conclusions of both novelty and lack of novelty. The document’s warning is that one-to-one claim mapping demands consideration of explicit and implicit disclosures, drawings and context, and is therefore prone to significant error and omission. Any AI mapping is an assistive input only; the conclusion must rest on the officer’s own analysis.
Drafting Support and Translation
AI may polish grammar, structure and readability of a draft the officer has already prepared, and may give a rough understanding of foreign-language documents. The strings are precise: language support must not spill into substantive reasoning; machine translation relied upon for an objection must be checked and its use recorded in the reasoning on patentability; and every citation the tool proposes must be independently verified in the original source before use.
|
Received an FER that doesn’t add up? Where an examination report leans on a shaky classification, an over-broad search or an unverified citation, there is a principled basis to push back. Ask our patents team to review it. |
Claim Clarity and Sufficiency of Disclosure
AI may also assist in flagging preliminary clarity concerns in a claim — for instance, ambiguous quantitative or structural language that could attract an objection under Section 10(4) — and in surfacing possible gaps in the sufficiency of disclosure, such as missing implementation detail or an unsupported best-mode requirement. The Guidelines are explicit that both are treated as preliminary issue-spotting only: the legal determination of whether an objection is well founded, and the drafting of any resulting objection in the Office’s own style with the applicable statutory provisions, remains entirely for the officer.
The Confidentiality Line: Unpublished Applications and Public AI Tools
Among the clearest commands in the document is that unpublished patent application contents, confidential office records and internal deliberative material must not be entered into public AI tools. Claims, descriptions, prior-art notes and hearing notes are singled out. The concern is disclosure: material entered into an external system may travel beyond the approved environment, with obvious consequences for the novelty and integrity of an unexamined application. The permitted path is confined to approved internal or secure authorised environments. For applicants, this is a meaningful institutional safeguard — and one that intersects directly with wider data-protection expectations.
What the Office May Not Do: Six Prohibited Uses
The Guidelines list six prohibited uses. In substance: entering unpublished or confidential material into public AI tools; using AI as a substitute for the officer’s application of mind on substantive questions — novelty, inventive step, industrial applicability, sufficiency, clarity, unity; issuing office actions, FERs, hearing notices or decisions solely on AI output without adequate oversight; citing AI-suggested case law, prior art or literature without independent source verification; incorporating AI content into official communications without review, correction and adoption; and relying solely on AI for decisions affecting the rights of applicants, patentees or third parties — with opposition proceedings expressly named.
|
Opposition on foot? The Guidelines single out opposition proceedings as a setting where AI cannot be the sole basis of decision. That has strategic weight. Our team advises on pre-grant and post-grant opposition strategy in this new environment. |
Governance, Record-Keeping and Accountability
The administrative measures are, for the most part, enabling rather than mandatory — framed as steps the competent authority may take. They include recording the material use of AI (tool, nature of use, date), with the possibility that such records are disclosed to stakeholders to build confidence in the process; an AI Governance Committee drawn from the Examination Division, IT and QMS to approve tools, classify permitted and prohibited uses and revise the Guidelines periodically; structured training on AI’s limitations and on identifying hallucinations and fabricated citations; and provision for independent audit, impact assessment and incident reporting. An Annexure sets out an officer’s checklist and a declaration on AI use in work-product delivery.
What This Means for Applicants, Patentees and Opponents
For those whose rights are examined, the Guidelines are less a technical curiosity than a shift in the environment in which patents are won and defended. They create room to interrogate AI-influenced actions against a published internal standard; they protect the confidentiality of unexpected quarters of an unpublished file; and they place opposition proceedings under particular scrutiny. Whether and how to invoke any of this turns on the specifics — the stage of the matter, the technology, the reasoning on the face of the report — which is precisely where experienced counsel earns its keep.
|
Talk to S.S. Rana & Co. From filing strategy to FER responses and opposition, our patents team can help you navigate examination in the age of AI. Get in touch to discuss your portfolio. |