{"id":1341,"date":"2026-07-05T18:30:57","date_gmt":"2026-07-05T18:30:57","guid":{"rendered":"https:\/\/blog.franke-ip.com\/en\/?p=1341"},"modified":"2026-07-05T18:31:28","modified_gmt":"2026-07-05T18:31:28","slug":"when-the-description-reads-along-g-1-24-ai-assisted-drafting-and-the-firms-new-liability-risk","status":"publish","type":"post","link":"https:\/\/blog.franke-ip.com\/en\/when-the-description-reads-along-g-1-24-ai-assisted-drafting-and-the-firms-new-liability-risk\/","title":{"rendered":"When the Description Reads Along: G 1\/24, AI-Assisted Drafting, and the Firm’s New Liability Risk"},"content":{"rendered":"
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For decades, the description was the quiet part of a patent application. The music played in the claims; the description supplied background, embodiments, and fallback positions. As long as the claims were clear on their own, the exact wording of the description had few consequences in examination or litigation. Two developments are now unsettling this division of labor \u2014 and, of all places, they converge at exactly the same point. Legally, the EPO’s Enlarged Board of Appeal, with G 1\/24<\/strong>, has elevated the description to a permanent tool of interpretation. Technologically, artificial intelligence (AI) is increasingly taking over the drafting of that very text. For law firms, this creates a risk that is easily overlooked: the AI’s efficiency gain is concentrated exactly where the duty of care is rising the fastest.<\/p>\n\n\n\n

What G 1\/24 Actually Decided<\/h2>\n\n\n\n

With its decision of 18 June 2025, the Enlarged Board of Appeal put an end to a long-simmering divergence in EPO case law. The core holding: the description and drawings must always<\/strong> be consulted when interpreting the claims for the purpose of assessing patentability \u2014 not only once a claim, read on its own, appears unclear or ambiguous. The underlying case concerned the interpretation of a single term (“gathered sheet”) in a patent; the Board used it to settle a fundamental question about how Articles 69 and 84 EPC interact.<\/p>\n\n\n\n

Two points matter for practice. First, the decision harmonizes<\/strong> EPO practice with that of the Unified Patent Court and the national courts. What is written in the description will henceforth be read alongside the claims according to the same basic principle in examination, opposition, and infringement proceedings alike. The description thus moves from the periphery to the center of claim interpretation. Second \u2014 and precision matters here \u2014 the Board holds that the description must always be consulted<\/strong> for interpretation; it does not hold that the description may override an otherwise clear claim at will. The practical effect is therefore not a blank check to reinterpret every claim from the description. But it does shift the weight considerably: every definition, every use of a term, every statement about “the invention” can now influence how the claims are interpreted.<\/p>\n\n\n\n

This is reinforced by a further, still open issue. Referral G 1\/25<\/strong> raises the question whether the description must be adapted to the claims prior to grant. Both directions carry risk: leaving contradictions in place may dilute the interpretation; adapting the description risks impermissible extensions (Art. 123(2) EPC) and unintended shifts in the scope of protection. However G 1\/25 is decided, the message is already clear: the description is no longer neutral background text but an effective tool of interpretation.<\/p>\n\n\n\n

From Background Text to a Sharp Tool<\/h2>\n\n\n\n

This changes the character of drafting itself. In the past, the description could be written generously, redundantly, and with many variants \u2014 extra sentences rarely did harm. After G 1\/24, the opposite is true: every sentence now carries a potential interpretive effect. A definition that is broader or narrower than intended now counts. An offhand statement about the purpose or advantage of “the invention” can support a narrowing interpretation. An embodiment that promises more than the claim actually covers can become a point of attack. And terms used one way in one place and differently elsewhere create exactly the kind of inconsistency a court will now have to resolve \u2014 not necessarily in the patentee’s favor.<\/p>\n\n\n\n

The description has thus become an instrument that demands consistency, terminological discipline, and a precise awareness of the interpretive consequences of every word. These are exactly the qualities that AI-generated text systematically struggles with.<\/p>\n\n\n\n

Where the AI-Drafted Description Tips Over<\/h2>\n\n\n\n

AI can produce descriptions in a fraction of the time previously required \u2014 fluent, extensive, plausible. That is tempting, because the description is the most text-heavy and seemingly most mechanical part of drafting. But it is precisely the typical weaknesses of generative models that strike at the risks G 1\/24 has sharpened:<\/p>\n\n\n\n

Terminological inconsistency.<\/strong> Language models aim for variation and fluent phrasing, not rigid term fidelity. A model will use the same term slightly differently in different places, or introduce synonyms that carry a subtly different meaning. In a world where the description is always consulted for interpretation, that is no longer a cosmetic flaw \u2014 it is an interpretive trap.<\/p>\n\n\n\n

Unsupported assertions and pseudo-embodiments.<\/strong> AI tends to fill gaps “sensibly” \u2014 with advantages, mechanisms of action, or variants that are not technically supported. Such passages can steer claim interpretation in an unwanted direction, and \u2014 should G 1\/25 confirm a duty to adapt \u2014 become a source of Article 123(2) problems when later deleted.<\/p>\n\n\n\n

Scope bias.<\/strong> Generative models, when in doubt, produce more text, not less. But more text means more surface area for contradictions, overreaching definitions, and incidental commitments \u2014 in other words, more of exactly what a court now consults.<\/p>\n\n\n\n

Imported phrasing patterns.<\/strong> AI draws on training data full of other parties’ patents. It adopts “characterizing” phrases, implicit disclaimers, or purpose-bound language that quietly shifts the scope of protection \u2014 phrasing an experienced drafter would have deliberately avoided.<\/p>\n\n\n\n

Definitions with a life of their own.<\/strong> A model likes to write its own definitions into the description. If such a definition \u2014 narrower or broader \u2014 departs from the intended claim meaning, it now has a direct effect on interpretation under G 1\/24.<\/p>\n\n\n\n

The insidious part is that these errors don’t look like errors. AI text reads competently and fluently. The inconsistency is not hidden in an obvious blunder but in the interplay of passages that each look innocuous on their own \u2014 and only reveal their effect once an infringement dispute arises.<\/p>\n\n\n\n

The Firm’s Liability Risk<\/h2>\n\n\n\n

For a law firm, this bundles into a specific risk. The patent attorney is responsible; they sign the application, and they are liable if an unnoticed inconsistency in the description narrows the client’s scope of protection or brings a patent down in litigation. That responsibility cannot be delegated to a model.<\/p>\n\n\n\n

The real core of the issue is a paradox. AI saves the most time exactly where G 1\/24 demands the greatest care. The description used to be the part one could most safely “let run through” \u2014 and it is now the part that demands the most precise, interpretation-aware scrutiny. The apparent efficiency gain is therefore deceptive: whoever merely skims the AI-drafted description hasn’t worked faster \u2014 they have simply pushed the risk, invisibly, into the future: into examination, opposition, and infringement proceedings.<\/p>\n\n\n\n

On top of that, the necessary review is not the fast kind of review. Checking an AI-drafted description for interpretive consequences means reading the entire text against the claims: for consistent terminology, for definitions, for overreaching statements about “the invention,” for unsupported embodiments. That comparison is cognitively demanding and often no faster than drafting it oneself \u2014 sometimes slower, because someone else’s plausible-sounding phrasing first has to be deconstructed to recognize its interpretive effect. The AI’s time advantage shrinks in direct proportion to the care that G 1\/24 now requires.<\/p>\n\n\n\n

This is not an argument against AI. It is a precise mapping of its risk: the description is the place where AI’s characteristic weaknesses meet the stakes that G 1\/24 has raised. This is exactly where it is decided whether a firm has mastered AI \u2014 or whether AI has written a liability problem into the file.<\/p>\n\n\n\n

What Firms Should Do Now<\/h2>\n\n\n\n

The analysis points to concrete safeguards that preserve AI’s efficiency gain without increasing liability:<\/p>\n\n\n\n