Apple’s Sues OpenAI: Trade Secrets, NDAs, and AI Training Data
TORONTO, ON –
Apple’s lawsuit against OpenAI is a reminder that in 2026, businesses are no longer just protecting confidential information from being leaked—they’re also trying to prevent it from being absorbed into AI systems, reused in product development, or turned into a competitive advantage without permission.
For Apple, the point is simple but important: trade secrets do not lose value just because the technology around them has changed.
Whether the issue is internal product plans, design concepts, source code, technical documentation, or strategic business information, the legal risk begins the moment sensitive material leaves the controlled environment it was supposed to stay in.
Trade secret
n. — /trād ˈsēkrət/
Confidential business information that gives a company a competitive advantage and is protected because it is not generally known.
Diverge helps artists, creators, and influencers protect their work, negotiate smarter, and build their business without giving up control of the value they create.
What Apple’s lawsuit is about
Apple filed suits against OpenAI and two former employees on July 10, 2026, alleging misappropriation of trade secrets tied to Apple’s device efforts. Apple claims its former employees disclosed confidential information taken from the company, and which was then used by OpenAI in connection with AI-related product development. That makes this case especially significant because it’s not only about anti-competitive behaviour, but also how that information may have been used to help build something new.
In traditional trade secret cases, the concern is often disclosure, theft, or unfair competition.
In the AI era, the concern can extend further: was the information merely reviewed, or was it fed into a model, used to shape outputs, or incorporated into a system that can now reproduce the underlying commercial advantage at scale?
Why trade secrets are worth protecting
Trade secrets remain one of the most practical forms of protection for businesses because they cover valuable information that is not public and that derives economic value from being kept secret. For tech companies, that can include algorithms, business methods, product roadmaps, engineering processes, client lists, and internal development workflows. In an AI and product development context, those assets are often the most sensitive part of the business because they reveal not only what a company is building, but how it is building it.
The challenge is that trade secret law depends heavily on secrecy. Once information is broadly disclosed, mishandled, or shared without adequate safeguards, not only is secrecy compromised, but the owner may also lose some of the protection that made it valuable in the first place. That is why it’s essential for internal controls, access limits, and contract language to form part of the legal strategy.
NDAs are just the start
A non-disclosure agreement is still one of the first lines of defence, but it is not enough on its own. Diverge Legal’s IP guidance emphasizes the importance of tailored NDAs, non-solicitation provisions, and unambiguous contractual language designed to protect trade secrets and sensitive commercial data. What’s most important is whether confidential information is clearly defined, how it may be used, who can access it, and what happens when a relationship ends.
That matters even more when employees, contractors, or vendors move between companies. A strong NDA should prohibit not only direct disclosure, but also indirect misuse—including copying, summarizing, uploading, or relying on confidential information in tools that can retain or learn from it. If a contract is silent on AI, that silence can become a problem fast.
Where AI changes the risk
The newer legal issue is unauthorized training data or algorithmic ingestion. This refers to sensitive information being used to train, fine-tune, improve, or inform an AI system without the owner’s permission. That can happen intentionally, but it can also happen through poor internal practices, vague vendor terms, or through employees entering confidential material into public tools that may retain or reuse the data.
Businesses should not assume that a general confidentiality clause will automatically prevent data from becoming AI fuel. This is why modern contracts need AI-specific language to restrict this type of unauthorized use and disclosure.
Diverge Legal’s recent contract guidance recommends expressly stating that “training,” “research,” or “internal purposes” exclude use in machine learning pipelines, model development, or competitive product creation without prior written consent.
Why product development raises the stakes
Product development is where these issues become especially dangerous because the line between inspiration and misuse can sometimes be blurry. If a company is developing hardware, software, or a new digital product, then access to internal planning documents, prototypes, technical architecture, or user insights can provide a direct roadmap to a competitor’s next move. In a fast-moving AI environment, that roadmap can be even more valuable if it gets embedded into a model or used to accelerate its development cycles.
That is why businesses should think of trade secret protection as both a legal issue and operational risk. The legal documents matter, but so do off-boarding procedures, access revocation, data segmentation, document retention policies, and restrictions on what employees and vendors can input into AI tools. Without those controls, companies may discover too late that their “confidential” information was never truly contained.
Practical steps businesses should take
Companies do not need to wait for a lawsuit to strengthen their protections. In fact, it’s best practice to regularly undertake internal reviews to adequately safeguard proprietary data.
Identify what information is actually being treated as confidential, then decide who can access it, how it is stored, and whether it can ever be used in AI systems.
Update NDAs, contractor agreements, vendor contracts, and employment documents so they expressly address AI training, data retention, model improvement, and derivative use.
Create internal rules for product teams, including training staff not to paste confidential information into public AI tools, limiting use of external platforms for sensitive work, and documenting which systems are approved for which tasks.
If a dispute does arise, these steps can help a business show it took reasonable steps to protect its information, which is a much stronger position than relying on generic NDAs alone.
Protect what you build
Apple’s lawsuit is a timely reminder that trade secret protection has entered a new phase. Businesses still need the traditional tools—NDAs, access controls, and confidentiality obligations—but they also need to draft for the realities of AI, where information can be copied, processed, and transformed in ways that were not common even a few years ago.
For companies building products, this means confidentiality language must now be AI-aware. If your contracts do not clearly prohibit unauthorized training use, your “secret” may be far more exposed than you think.
Diverge Legal helps creators, brands, and businesses navigate the rules behind the business of content. We focus on helping clients protect what they create, structure smarter deals, and build with confidence in a fast-moving digital world.
If you’re ready for representation that understands the difference between a data point and your dream, contact us.
Read these next
More about DIVERGE
Diverge is not just a legal service provider. We’re your partner in building a legally sound and sustainable content creation business. We understand the unique challenges creators face and offer tailored solutions to protect your intellectual property, ensure regulatory compliance, and minimize legal risks.
Whether you’re an established influencer or an emerging creator, Diverge is here to help you focus on what you do best, while we take care of the legal complexities.
Reach out to Diverge today to learn more about how we can support your content creation journey.
Follow @diverge.legal on social media or subscribe to our newsletter below for more tips on protecting your creative rights and thriving in the creator economy.
Important Notice: The information in this article is provided for general informational purposes only and is not intended as legal advice. Reading this content does not create a lawyer-client relationship. Always seek professional legal counsel tailored to your specific situation. No part of this article may be reproduced or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, or stored in any retrieval system of any nature, without the express written permission of Diverge Legal.
