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Why Filing AI Patent Volume Fails Without Core Technical Necessity and Business Alignment
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On August 24, 2026, patent attorney and computer scientist Robert Plotkin joined host Gene Quinn on the IPWatchdog Unleashed podcast to analyze strategic mistakes in artificial intelligence patent prosecution. Plotkin warned against using raw filing counts as a metric for innovation, explaining that effective AI portfolios require clear alignment between business objectives and technical necessity. The discussion detailed how aggressive, AI-assisted omnibus applications risk public dedication and trade secret loss, while subject matter eligibility challenges under 35 U.S.C. § 101 frequently obscure underlying requirements of enablement and written description.
During the August 24, 2026 episode of IPWatchdog Unleashed, Gene Quinn interviewed Robert Plotkin, author of The Genie in the Machine and AI Armor, regarding the legal standards and prosecution strategies shaping AI innovation. Plotkin stressed that software instructions and hardware implementations form a single technological spectrum, arguing that treating software as inherently less technical distorts patent examination. Addressing 35 U.S.C. § 101, Plotkin noted that tribunals often rely on patent eligibility as an improper shortcut instead of evaluating claims under statutory provisions for written description, enablement, novelty, and non-obviousness. He further cautioned against broad omnibus provisional filings (particularly those generated via automated tools), warning that disclosing dozens of unrefined embodiments without filing claims can dedicate subject matter to the public and destroy trade secret protection.
The influx of AI-related patent applications has led many corporate IP departments to prioritize portfolio volume over targeted coverage. This rush has intensified scrutiny under U.S. patent eligibility jurisprudence, where examiners frequently reject functional claims under Section 101 without conducting claim construction in light of the specification and prosecution history. Concurrently, the deployment of generative AI tools in patent drafting has lowered filing barriers, making omnibus provisional specifications common. However, under U.S. disclosure doctrines, listing expansive, general-purpose platform implementations without identifying specific technical solutions can undermine subsequent utility applications under 35 U.S.C. § 112, leaving applicants with neither enforceable patent claims nor trade secret exclusivity.
For patent owners and prosecution counsel, relying on application volume creates significant legal exposure. To ensure validity during post-grant challenges or enforcement, applications must anchor claim terms to specific technical capabilities developed because off-the-shelf solutions were unavailable. When filing provisional applications, practitioners must avoid indiscriminate disclosures of secondary technical features that are not ready for claiming, as unclaimed disclosures jeopardize trade secret status and risk dedication to the public.
For Korean corporate filers and multi-jurisdictional IP managers targeting the U.S. market, this strategic alignment is critical. Asian technology companies frequently measure IP team performance by filing metrics, leading to large U.S. portfolios that rely on general software descriptions. Korean applicants targeting U.S. protection must ensure that technical solutions tailored for KIPO prosecution under Article 47(2) of the Korean Patent Act (which strictly enforces added-matter limits) are similarly supported in U.S. specifications by detailed algorithmic and structural execution steps. While KIPO's amendment rules tightly restrict post-filing modifications to the original specification, U.S. practice requires early, precise positioning under Section 112 to withstand abstractness challenges under Section 101.
Patent offices and courts will continue to evaluate whether broad AI software claims meet statutory disclosure standards. IP counsel should immediately conduct a disclosure audit across pending AI provisional filings to segregate proprietary trade secrets from patentable technological improvements. Before authorizing new filings, prosecution teams should implement a mandatory threshold check: identify the exact proprietary capability that required internal development over off-the-shelf tools, establish its specific commercial objective (such as product blocking or licensing leverage), and structure the specification around its concrete execution details.