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Alt Legal and Corsearch LiveThe AI Brandwagon: Why AI is becoming so popular for trademark practice

Alt Legal Team | January 24, 2024
4 min read

On March 19, 2024 at Alt Legal & Corsearch Live, Matt Rubin of Corsearch moderated a panel discussion between trademark attorneys Vivek Jayaram and Jessica Neer McDonald, “The AI Brandwagon: Why AI is becoming so popular for trademark practice.” During this session, the panelists discussed creation, clearance and protection of trademarks using AI, the impact of AI technology on the trademark industry, predictions about the future of AI technology, and more.

Download the presentation materials here.

Top 10 Takeaways

  1. Consider the fact that there is a difference between open and closed systems. In terms of an open system, when you type something into OpenAI or ChatGPT, the system learns from what you type in. In a closed system, which is a newer form of AI, one user or a group of users in a network will change the way that AI system works. [Matt]
  2. When using AI in trademark creation, it can be helpful for generating basic marks. AI tends to produce a lot of alliteration but sometimes comes up with really great combinations of words. Businesses can use ChatGPT to come up with ideas for word marks and logos. [Sam]
  3. Keep in mind that when using a closed system for trademark creation, there is a limited set of data that the system will be drawing on. Be sure to keep your questions very pointed and specific. [Jessica]
  4. Remember that just because something was spit out by AI doesn’t mean that you can use it. If the AI system produced a confusingly similar word mark or logo, you still have to clear it. The platform wouldn’t bear any responsibility for producing a conflicting mark or logo. It would not be considered infringement if the AI system generated an infringing mark; however it would be infringing if you were to use the mark or logo on a product. [Sam]
  5. When it comes to using AI for search and clearance, computers have always been a part of clearance searches, and AI will only make searching and clearance better and faster. AI will help to limit some of the irrelevant results that come back with traditional search and clearance, which will help everyone save time and money. [Sam]
  6. AI has a high potential to help lawyers save time and contain costs by helping to quickly translate information into “business speak” that is clear and understandable. [Jessica]
  7. There is great potential to use AI to predict likelihood of registration because there is so much data to look through. If you’re looking for past terms that are similar, crowded field arguments, or distinctions between goods and services, AI can help make that analysis. In the searching context, it can be a delicate dance if a mark is unavailable or references are too close and you don’t want something that is a discoverable report. Having something automatically generated that shows major conflicts isn’t going to be something that you want to have. [Sam]
  8. AI is an excellent tool for drafting goods and services descriptions. You can create your own GPT for this task, incorporating the ID manual. AI is especially useful when drafting descriptions for clients in the tech field who require IDs not likely to be found in the ID manual. AI is also very helpful for better understanding your clients’ industries and finding their competitors and trademarks. [Jessica]
  9. AI can be used to aid lawyers in the trademark prosecution process. AI can show users what an examiner has approved in the past and even calculate likely acceptance rates. For example, AI can help users understand how much evidence is necessary to get through a crowded field. [Jessica]
  10. In terms of the future of AI, it’s possible that AI will help users predict likelihood of case outcome when it comes to TTAB decisions, particularly when it comes to the examiner or judge. AI can also help scrape data that can be used as evidence of a famous mark when users ask prompts like, “What is the most famous brand of X product?” The usability of AI is developing very fast— faster than Web3 technology—and users are getting comfortable using AI very quickly. [Jessica, Sam]


Matt Rubin, Moderator, Corsearch

Matthew Rubin is based in New York and has been with Corsearch for nearly 19 years.  He is currently a Commercial Executive where he evangelizes their suite of products and services to new and existing customers, a department he has been a part of since 2019.  Matthew started at Corsearch in 2005 as a Trademark Researcher, eventually managing the North American Operations department. Since then he has led the customer-facing Product Support and Training team, educating customers on optimizing their use of Corsearch’s suite of services


Vivek Jayaram, Founder, Jayaram Law

Vivek Jayaram is an attorney. But as Founder of Jayaram Law, he’s also a successful entrepreneur, which gives him a sound base for advising other entrepreneurs, creatives, and the companies they run. From groundbreaking artists and Web 3.0 innovators, to unique international brands in fashion and new media, Vivek handles their intellectual property transactions and disputes, corporate deals, and acts as an outside general counsel.



Jessica Neer McDonald, Founder, Neer McD PLLC

Jessica Neer McDonald is the founder and head of the Miami-based intellectual property law firm, Neer McD PLLC. Since the start of her legal career, Jessica has primarily advised on trademark, copyright, and right of publicity issues.  In particular, Jessica also serves as Head of Global Trademarks for Midjourney, Inc. Through her interest in emerging technologies, she also founded Blockish IP, an intellectual property education resource focused on emerging technologies, such as blockchain and artificial intelligence.

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