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生成AIにどこまで任せるか?

28/6/2026

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生成AIおよびAIエージェントの発展により、知的財産業務の多くは自動化または高度な補助の対象となりつつありますが、知財業務は、未公開発明、営業秘密、出願戦略、他社権利リスク、契約上の権利帰属など、企業の競争力そのものに関わる判断を含むため、AI活用は、『人間が最後に確認する』という抽象論では十分とはいえません。知財業務におけるAI活用は、AIに判断を委ねることではなく、知財判断のプロセスを分解し、Can / Trust / Own の三軸で『任せられる範囲』を設計することでしょう。
AIに仕事を任せるための三つの評価軸である Can / Trust / Own を使い、AI時代の知財部門が採るべき業務設計について、生成AIに深掘りさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
How Much Should We Entrust to Generative AI?
With the rapid advancement of generative AI and AI agents, many intellectual property (IP) tasks are becoming candidates for automation or sophisticated AI-assisted execution. However, IP work involves decisions that directly affect a company's competitive advantage, including unpublished inventions, trade secrets, patent filing strategies, third-party IP risks, and contractual ownership of rights. Consequently, simply stating that "a human should perform the final review" is no longer a sufficient principle for AI governance.
The effective use of AI in IP is not about delegating judgment to AI. Rather, it is about decomposing the IP decision-making process and deliberately defining what can be entrusted to AI by applying the three dimensions of Can, Trust, and Own.
Using these three evaluation criteria for delegating work to AI—Can, Trust, and Own—I asked generative AI to conduct an in-depth analysis of how IP departments should redesign their workflows in the AI era.
Please note that the research and analysis generated by AI are based solely on publicly available information. They may not necessarily reflect actual practice and may contain inaccuracies. Readers are therefore encouraged to interpret the findings with appropriate caution.

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