03/03/2026
How are generative AI tools reshaping the patent landscape? Our very own Dr. Ashley Sloat was asked by Thomson Reuters to do a deep dive on this topic. After four months of hands-on experimentation and analysis of over a dozen tools from industry pioneers, she has some thoughts on the state of the space!
As with seemingly every industry right now, there's a lot of hype around what AI means for the future of legal services. But what's real *now*? And what should firms be considering to ensure they're riding the wave, as opposed to being swept away by it?
In very little time, the patent law practice space has already become saturated with new AI tools targeting every stage of the workflow, but careful consideration is needed to ensure alignment with practice needs, focus areas, and staff expertise. In this article, Ashley shares her findings on:
⦿ Driver Versus human-in-the-loop (HITL) tools Drafting Tools
⦿ Iteration functionality.
⦿ Collaboration features.
⦿ Customizability.
⦿ Claim generation and structuring.
⦿ Figure drafting and labeling.
⦿ Security and confidentiality.
⦿ Drafting efficiency and quality, including specification support, transparency regarding drafting choices, and performance.
⦿ Technical area focus.
⦿ Jurisdictional support.
⦿ Workflow compatibility and ability to replace existing tools, including other available modules outside of patent drafting.
⦿ Prior art integration.
Cost-effectiveness.
⦿ Support and documentation, such as user guides, tutorials, and training.
⦿ Stage of development.
The article is now available for free via the Reuters Practical Law Journal. 👀👇🏼
A discussion of the current landscape of generative AI (GenAI) patent drafting tools, including the differences between fully automated driver tools and human-in-the-loop (HITL) tools, as well as essential tool evaluation criteria such as efficiency and quality, security and confidentiality, customi...