AI Patent Drafting 101

What IP teams need to know

AI patent drafting, enabled by recent breakthroughs in large language models (LLMs), poses an exciting new possibility for IP teams. Here’s what they should know when considering AI patent drafting.

Get a Demo
by-role-ip-leader

The potential and the appeal behind AI patent drafting

LLM-tech

LLMs have opened the door to AI patent drafting being a reality

While previous legal software often over-promised and under-delivered, the current generation of legal AI is based on a genuine technical breakthrough. What’s more, this leap has taken place in the very area where the legal tech of yesterday fell short: the ability to “read” and “understand” text, its context, and relevance, while also being built on modern, flexible IT architectures. Literacy is an essential feature for any legal software tool to add value to the IP process. AI today achieves that feat on a massive scale — Open AI’s GPT is trained on nearly the entire internet. And purpose-built AI systems designed to perform specific tasks like speeding drug discovery or credit card fraud detection can reach a level of comprehension that far exceeds ChatGPT.

leading-ai-tech

Why AI patent drafting is an enticing opportunity for IP teams

Despite a brighter economic outlook for businesses and increased patent filing in 2025, IP teams are still facing enormous cost pressures. This trend is likely to only continue — or even pick up — as AI changes expectations around how much companies can get out of their employees. Meanwhile, innovation complexity continues to surge with software becoming even further embedded in more and more products, the advent of AI-driven inventing, and the increasing strategic importance of trade secrets in addition to patents. It’s no wonder that most IP teams are now actively experimenting with AI solutions for discrete IP tasks like prior art search, evidence of use analysis, or patent drafting. Patent drafting is the most visible task in the IP lifecycle, so it makes sense that it’s the AI use case that’s generating the most hype.

WHITEPAPER (15 MIN READ)

The specific tasks and areas of opportunity AI unlocks for IP

Most conversations around AI for IP lack detailed substance. Download our latest whitepaper for actionable insight into what adoption looks like for IP teams.

Read Whitepaper
LinkedIn-Dismantling-The-All

The IP tasks AI is proven in now outweigh AI patent drafting in ROI

AI patent drafting is a tempting opportunity, but not the best place to start for IP automation

The savings opportunity of AI and automation for IP departments is real, but in exploring it, we encourage teams to look past the current buzz surrounding AI patent drafting. Just because patent drafting is the most visible part of the IP process doesn’t mean it’s the best place for IP teams to start automating. The full potential and limits of AI’s language capabilities in more advanced IP tasks like drafting and claims charting are still being tested. Drafting a set of claims that’s going to protect a company’s million- to billion-dollar crown jewels is currently still best left to human attorneys. Automating other less prominent areas of IP like:

  • Communicating back and forth with inventors
  • Prior art search
  • Provisional patenting, or
  • Annuity management
Can be just as meaningful to budgets in aggregate, and done with more ease and less risk — i.e. higher ROI. In fact, Tradespace has been seeing its customers save anywhere from $1,000-3,000 per invention disclosure by using AI for patent preparation.

patent-drafting

How AI drives efficiency elsewhere in the IP value chain

There’s one thing besides patent drafting that AI excels at this very moment: quickly gathering and synthesizing the information that IP attorneys use to make their decisions. Think of AI as a powerful paralegal or research assistant — one that has limitless capacity to autonomously:

  • Synthesize lengthy, complex materials into clear, concise invention disclosures
  • Enrich incomplete disclosures based on historic inventions and public documents
  • Suggest new use cases and markets for technologies
  • Compare new inventions against vast amounts of historic disclosure data from your portfolio
  • Summarize potential references
  • Compare and contrast inventions to existing specifications
  • Summarize Office actions and other USPTO communications
  • Summarize email conversations with outside counsel or inventors
  • Describe competitors’ or potential licensees’ products and IP in a given technology area
Identify patterns and/or bias in disclosure and filing decisions. In short, there are plenty of other IP tasks AI can automate besides the most high-stakes and complex one of patent drafting.

AI-Drives-Efficiency
WHITEPAPER (15 MIN READ)

Why transformation has never been more possible in this new era of IP

With the rise of AI, IP teams have the chance to thrive amidst historic rates of innovation and resource constraints.

Read Whitepaper
OG-IP-Strategies

Tradespace offers IP teams a smart alternative to AI patent drafting

Tradespace is an AI-backed, enterprise-grade, end-to-end IP platform that doesn’t merely speed up execution, but improves outcomes as well. By using all the available information to steer users directly to a conclusion, it drives metrics for higher-level workstreams like:

inventions-icon

Disclosures created

with our Inventor Portal that cuts the disclosure submission process down to minutes for inventors, leaving IP teams with rich ready-to-read disclosures

business-icon

Licensing campaigns completed

with complete AI-crafted campaigns, from marketing materials to contact information, for underutilized IP and unexpected use cases

But don’t just take our word for it

Read about how Tradespace is giving time and insight back to customers

Read more

Sign up to take Tradespace’s AI invention evaluator for a test drive yourself

Sign up