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As artificial intelligence (AI) becomes increasingly embedded in modern innovation, securing patent protection for AI-based inventions presents both new opportunities and growing challenges. The United States Patent and Trademark Office (USPTO) has issued updated guidance on evaluating AI technologies, but legal uncertainty remains—particularly around what qualifies as patent-eligible subject matter.
Join Robert Plotkin, Software Patent Lawyer & Founding Partner at Blueshift IP, LLC, Jeffrey W. Gluck, Ph.D., Partner at Panitch Schwarze Belisario & Nadel LLP, and Orlando Lopez, Ph.D., Partner at CM Law PLLC, will delve into the USPTO’s evolving approach, explore the implications of recent case law including Recentive v. Fox, and share practical tips for drafting and prosecuting stronger AI-related patent applications. From examining what constitutes “non-generic” AI to adapting claim strategies for emerging AI structures, this session will equip patent practitioners, innovators, and in-house counsel with the tools to navigate this rapidly shifting landscape.
Key issues that will be covered in this course are:
- USPTO’s current approach to AI patent eligibility
- Differences between USPTO guidance and Federal Circuit requirements
- Insights from Recentive v. Fox and its implications on AI patent claims
- Understanding when AI is considered “generic” vs. non-generic under patent law
- Strategies for identifying differentiating elements in AI-based inventions
- Best practices for drafting application- or domain-specific claims to demonstrate “practical application”
- Approaches to claiming AI as part of a larger method or system
- Drafting considerations for training AI models
- Updating your boilerplate language in AI-related patent specifications
- Treatment of AI performing calculations or decision-making vs. generic computer implementation
- The status and significance of USPTO Example 39 (neural network training claims)
- How to properly disclose and claim non-generic AI components
- Avoiding common drafting pitfalls in AI patent applications
- Practical tips for maximizing patent protection in the evolving AI space