What is a Trade Secret?
The exact definition of a trade secret is governed by state law and, therefore varies from state to state. Generally, a trade secret is information which:
1) derives economic value from not being generally known; and
2) is the subject of reasonable efforts under the circumstances to maintain its secrecy
A trade secret may be a customer list, algorithm, method, recipe, technique or anything that gives a company a competitive advantage over its competition. Even if other companies discover the trade secret on their own, it is still a trade secret if it meets the above criteria.

Why Trade Secrets Matter More Than Ever
From proprietary algorithms to go-to-market strategies, trade secrets are the lifeblood of tech companies. The problem? What was previously sufficient security to protect trade secrets no longer is. AI can now guess, sift, and reverse-engineer what used to be locked up tight.
If you’re thinking “This won’t happen to us,” you are missing the point. It already is.
In one case, Google’s own engineer was caught exfiltrating confidential AI chip designs and cloud architecture data—allegedly to help Chinese firms build competitors. He copied over 1,000 files, disguised them as PDFs in Apple Notes, and moved them to a personal cloud account—all while working at Google. That is not just a breach. That is a wake-up call.
How AI Is Being Used to Steal Trade Secrets
AI isn’t just a target—it’s a weapon. Here’s what modern AI can do:
- Uncover competitors’ product pipelines
- Determine competitor’s next moves before they know them themselves
- Reverse-engineer code and algorithms
- Extract confidential patterns from public data
- Determine competitors’ vendors and clients from online relationship data
- Enable insiders to siphon data without detection
This is no longer theoretical. We’ve seen it in the quarter of a billion-dollar Uber vs. Waymo fight. We’ve seen it in pharma, manufacturing, and finance. It is getting bigger and it is not going away.
What is Not Working
Many companies still rely on outdated protections:
- Broad access permissions
- Weak encryption
- NDAs with no teeth
- Siloed data governance
These will not stop an AI-enhanced attacker—or even a careless employee—from leaking your most valuable assets.
What You Should Be Doing Instead
If you want to avoid being the next headline, here is what to focus on:
1. Lock Down Your Data Access
- Use least-privilege policies
- Revoke unnecessary permissions—fast
- Monitor behavior for anomalies
2. Vet Your AI Tools
- Know what data goes in
- Know what is coming out
- Never train AI on confidential datasets without strict controls
3. Protect the AI Itself
- If your AI models are proprietary, treat them like trade secrets
- Limit access, encrypt everything, and document every step
4. Prepare for Litigation
- Draft contracts that account for AI-generated trade secrets
- Work with counsel to ensure NDAs and IP clauses hold up in court
- If a breach happens, move fast—evidence disappears quickly
5. Align with ISO 42001
- Build governance frameworks that anticipate AI risks
- Conduct ongoing risk assessments
- Implement ethical review procedures for AI use
The Legal Landscape Is Not Ready
Current U.S. laws, like the Defend Trade Secrets Act, offer some protection. But enforcement is tricky. AI makes it easier to steal and harder to prove. Even if you catch the thief, they may already be halfway around the world—or working for your competitor.
Cross-border enforcement? Good luck. And transparency regulations for AI are now clashing with companies’ need to keep certain processes secret.
Final Thought
Trade secret theft used to be a risk. In the AI era, it’s a guarantee—unless you act now. Update your defenses. Rethink access. Build a legal and technical strategy that reflects how fast AI is moving.
The companies that win the AI race will not just build the best tools.
They will be the ones who know how to protect them.
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