AI is now fully integrated into the trademark practice. Clearance searches, likelihood of confusion analysis, and monitoring are now faster, broader, and more data-driven than ever. Tools can scan federal, state, and common law sources, identify similar marks across industries, and flag potential issues under Section 2(d) of the Lanham Act.
What once required days of searching and judgment now happens in minutes.
At first glance, that should make trademark decisions easier. In practice, it has shifted where the real decisions are made.
The First Layer Is Now Standardized
AI has largely standardized the first step in the trademark process: identifying potential conflicts.
In many cases, the same marks are flagged, the same similarities are highlighted, and the same risks are surfaced.
The question is no longer whether a risk exists. It is whether that risk matters—and what to do about it.
Likelihood of Confusion: More Than a Data Point
AI tools can identify similar marks and even score their similarity, but likelihood of confusion is not a formula—it is a judgment based on case law interpretation and trademark prosecution experience.
It depends on factors such as relatedness of goods, channels of trade, and marketplace context.
Two marks may appear similar in a database, but coexist without issue or create immediate conflict.
Scenario: A Clearance Result That Looks Risky—but Isn’t
A search flags a prior mark with similar wording and overlapping goods or services.
AI categorizes it as high risk. But closer analysis shows the cited mark is weak because it exists in a crowded field, the goods or services move through different channels of trade, and marketplace context reduces confusion.
A data-driven view may suggest avoiding the mark. A contextual view may support moving forward.
Scenario: A Mark That Looks Clear—but Isn’t
A mark clears searches, but a common law user exists or branding creates overlap in perception.
The issue is not visible in the dataset but emerges from real-world use.
C&D Letters: Where Analysis Meets Strategy
AI can identify enforcement opportunities, but sending a cease and desist letter is not a binary decision.
It involves tone, business considerations, and likelihood of escalation.
Scenario: The Same Conflict, Different Approaches
Two companies identify the same potentially infringing mark.
One sends an aggressive demand. Another takes a measured approach considering coexistence.
The outcomes differ significantly—escalation versus resolution.
Prosecution at the USPTO: Still a Human Process
AI can predict likelihood of refusal and suggested responses. But trademark prosecution still involves examiner judgment and arguments.
Likelihood of confusion refusals are addressed through positioning, argument, and sometimes compromise with the Examining Attorney.
Conclusion
In 2026, identifying trademark risk is no longer the advantage.
The difference lies in how that risk is evaluated, positioned, and acted upon.
Outcomes are not determined by what is found, but by what is done next.
About The Authors
Daniel J. Holmander
Daniel J. Holmander is a registered U.S. patent attorney and Co-Chair of the Intellectual Property Group at Adler Pollock & Sheehan…
Cheryl A. Clarkin
Cheryl focuses her practice on counseling and advising clients on a wide range of U.S. and international intellectual property matters, including…
