Record Trade Secret Filings in 2025: What's Driving the Surge and How to Protect Your Company

Quick answer: Federal trade secret filings hit a record 1,552 cases in 2025 — up 20% from 2024 — driven largely by employee mobility and a 92% jump in AI-related claims. Companies can reduce their risk by keeping NDAs current, restricting access to AI models and training data on a need-to-know basis, and building a real offboarding process.

The numbers are striking. According to the Lex Machina 2026 Trade Secret Litigation Report, federal trade secret case filings reached 1,552 in 2025, a 20% increase over 2024 and the highest annual total since the Defend Trade Secrets Act (DTSA) took effect in 2016. This isn't a one-year anomaly; it's part of a sustained, multi-year upward trend that shows no sign of reversing.

Two forces are driving the surge. The first is employee mobility. As competition for skilled talent in engineering, data science, and product roles has intensified, so has the frequency of employees moving directly to competitors, often taking institutional knowledge, client relationships, or technical know-how with them. Practitioners report that trade secret claims increasingly arise not from outside corporate espionage but from departures that look, on paper, like ordinary job changes.

The second driver is more specific to the current AI moment. AI-related trade secret filings jumped 92% from the first half of 2025. As companies race to build proprietary models, training pipelines, and algorithmic processes, the trade secrets at stake have shifted from traditional formulas and customer lists to model architectures, fine-tuning techniques and methodologies, and curated datasets.

The stakes are substantial. Cases that proceed to trial usually take over three years to resolve, and from 2023 to 2025, juries reportedly have awarded more than $716 million in actual damages and $510 million in punitive damages in trade secret cases.

What This Means for Your Company

For both growth-stage and established companies, this litigation trend is a reason to revisit trade secret protection now, rather than after a departure or a dispute has already occurred. A few areas deserve particular attention. Confidentiality and non-disclosure agreements should be current, specific to the categories of information the company actually considers proprietary, and signed by every employee and contractor with access to sensitive material. Access controls matter as much as paper agreements; if every engineer has broad access to proprietary model weights, training data, or source code regardless of their role, a company will struggle to argue in litigation that it treated the information as a genuine trade secret, since reasonable measures to maintain secrecy are a legal requirement, not just good practice.

Offboarding procedures deserve equal attention. A documented process for offboarding departing employess should be in place. This process should at a minimum confirm the return of company devices, revoke system access, and include an exit interview that reinforces confidentiality obligations. For AI-specific assets, companies should identify which elements of their AI systems are trade secrets, document how those elements are protected, and extend the same access and confidentiality discipline to vendors and contractors who touch training data or model infrastructure.

Finally, given the size of jury awards in recent years, companies should evaluate their insurance coverage for trade secret and IP litigation and understand what a dispute would cost to litigate to resolution.

Trade secret litigation is no longer a niche concern reserved for a handful of industries. With AI-related filings nearly doubling year over year, it has become a mainstream risk for any technology company. Wittliff Cutter Saba's litigation team regularly represents parties on both sides of trade secret disputes and stands ready to assist your company should the need arise.

Frequently Asked Questions

How many trade secret lawsuits were filed in 2025?

According to the Lex Machina 2026 Trade Secret Litigation Report, federal courts saw 1,552 new trade secret case filings in 2025 — a 20% increase over 2024 and the highest annual total since the Defend Trade Secrets Act took effect in 2016.

Why are AI-related trade secret claims increasing?

As companies build proprietary models, training pipelines, and algorithmic processes, the trade secrets at stake have shifted from traditional formulas and customer lists to model architectures, fine-tuning techniques, and curated datasets. AI-related trade secret filings jumped 92% compared to the first half of 2025 alone.

What should a company do to protect AI-related trade secrets before an employee departs?

Keep confidentiality and non-disclosure agreements current and specific to the categories of information the company treats as proprietary; restrict access to model weights, training data, and source code by role rather than granting broad access by default; and maintain a documented offboarding process that confirms the return of company devices, revokes system access, and includes an exit interview reinforcing confidentiality obligations.

Source: Lex Machina, 2026 Trade Secret Litigation Report.