August 18, 2026

Apple v. OpenAI: How the World’s Most Valuable Company Is Using Trade Secret Law to Defend Its Competitive Edge

Subscribe to Our Newsletter

Newsletter


Patrick Dempsey

|

August 18, 2026

On July 10, 2026, the most valuable company in the world accused the most talked-about company in the world of theft. Apple sued OpenAI in the U.S. District Court for the Northern District of California, alleging that OpenAI built its hardware ambitions on a foundation of Apple’s misappropriated trade secrets.¹ Few disputes touch as much of Certum’s Trade Secret Litigation Playbook at once: reasonable measures to guard a secret, identifying with particularity what was taken, and the human-centered points — recruiting and employee departures — where secrets actually walk out the door. Nearly every core theme in Certum Group’s Trade Secret Guide is in this case. And the lesson beneath it is worth sitting with: for the companies with the most to protect, trade secret litigation is not a last resort. It’s a front-line instrument of competitive strategy.


Background


The dispute sits at the intersection of two of the most closely watched storylines in technology. In 2025, OpenAI acquired io, the hardware venture founded by former Apple design chief Jony Ive and a group of other Apple alumni, for a reported $6.5 billion, and set out to build its first consumer hardware device, widely expected to compete directly with the iPhone.² To staff that effort, OpenAI hired aggressively from Apple. According to the complaint, more than 400 former Apple employees now work at OpenAI.³


Two of those hires anchor Apple’s allegations. Tang Yew Tan spent roughly 24 years at Apple, where he served as a vice president of product design responsible for the iPhone and Apple Watch, before becoming OpenAI’s chief hardware officer. Chang Liu spent about eight years at Apple as a senior systems electrical engineer before departing for OpenAI in 2026.⁴ Apple’s theory is not that a single rogue employee walked out the door with a file. It is that the movement of talent was accompanied by a coordinated effort, one Apple describes as operating “at every level," to extract and exploit the confidential information those employees carried in their heads and on their devices.⁵


The Allegations


The complaint reads less like a garden-variety departure dispute and more like a catalog of the exact conduct the Trade Secret Guide warns companies to watch for. Among Apple’s central allegations:


Apple claims OpenAI’s hardware leadership directed recruiters to use Apple’s confidential project code names during the hiring process, and instructed job candidates to bring “actual parts” and “CAD/design artifacts” to their interviews.⁶ It alleges that OpenAI circulated internal Apple documents marked “Need to Know” that coached departing employees on how to evade Apple’s exit-security procedures, including the “dreaded walkout,” and to alert OpenAI before signing their exit agreements.⁷


The specifics attributed to individual employees are what give the complaint its texture. Apple alleges that Chang Liu exploited an authentication bug to reach internal network storage after his access should have been cut off, messaging a colleague, “LOL, I found out I can access the [network storage], so funny,” and noting within hours of his departure that he “still ha[d] another computer.”⁸ And Apple alleges that io “exploited and used Apple’s secret, proprietary industrial design techniques,” misleading one of Apple’s own manufacturing partners about whether it was authorized to use a confidential metal-finishing technique.⁹


The trade secrets Apple says are at risk span the full arc of its product-development process: technical specifications for unreleased technologies, engineering presentations and prototype data, component and vendor selection processes, and the proprietary manufacturing techniques that turn a design into a shippable product.¹⁰ Notably, Apple’s opening ask is not a damages windfall. It is protection. Apple seeks to bar OpenAI from using or disclosing the information at issue, to compel the return of its confidential materials, and to preserve the evidence.¹¹ In other words, Apple is using the courthouse to do what its NDAs and exit interviews were supposed to do: keep its edge inside the building.


OpenAI’s Response


OpenAI has pushed back hard, and its answer is a preview of the fault lines any trade secret plaintiff should expect to fight over. On August 6, 2026, OpenAI moved to dismiss, characterizing the alleged conduct as “benign, lawful conduct” that Apple has mischaracterized, and arguing that its hardware executives simply followed standard industry recruiting practices.¹² As to Chang Liu, OpenAI contends he was “trying to help Apple” by assisting former colleagues who asked him to locate work information, not stealing anything.¹³


More pointed, and more instructive, is OpenAI’s argument that Apple’s own conduct undermines its case. OpenAI asserts that Apple allowed employees to use personal iCloud accounts for work and failed to properly revoke access when they left — noting that an Apple manager remained logged into Chang Liu’s personal iCloud account after his departure in order to transfer files.¹⁴ From that, OpenAI argues that Apple’s offboarding lapses created “confusion and unwanted access issues that Apple now characterizes as theft.” OpenAI also contends that Apple has not identified its trade secrets with adequate specificity, pointing instead to “generic categories of the product-development process.”¹⁵ OpenAI must file its full response by August 17, 2026, with oral argument on the motion set for October 1, 2026.¹⁶


Whatever the merits, OpenAI’s playbook is worth studying precisely because it is so conventional. Reasonable secrecy measures and identification of the trade secret with particularity are two of the elements every misappropriation claim rises or falls on, and they are exactly where a well-resourced defendant will apply pressure first.


What This Means


It is easy to read a case like this as celebrity litigation between two of the most valuable enterprises on earth. The more useful reading is that trade secret law has become core infrastructure for how modern companies protect competitive advantage. Apple did not respond to a $6.5 billion competitive threat with a press release or a patent portfolio. It responded with a trade secret complaint, because in a business where the crown jewels are unpatented know-how — manufacturing techniques, vendor relationships, unreleased designs — the Defend Trade Secrets Act and its state-law counterparts are the sharpest tools available.


The case also throws the Trade Secret Guide’s central lessons into relief. The value of a trade secret program is only as good as the “reasonable measures” behind it; OpenAI’s opening move is to argue that Apple’s own iCloud and offboarding practices were not reasonable at all. The ability to describe what was taken, with specificity, is not a formality. It is frequently the whole ballgame at the pleading stage. And the human element — recruiting, exit procedures, the “dreaded walkout” — is where secrets actually leak, long before anyone reaches a courtroom. Companies that treat these as compliance checkboxes learn the hard way, in a complaint, that they were the strategy all along.


For those of us who evaluate disputes for a living, Apple v. OpenAI is also a reminder of why high-stakes trade secret matters are among the most compelling on the plaintiff’s side. The conduct is often concrete and documentable, the competitive stakes are enormous, and, as the Federal Circuit’s recent decision in Versata Software v. Ford underscored, the damages framework can reach the full value of what the misappropriation delivered to the wrongdoer, not merely a discounted license fee. That combination is exactly what makes these cases worth pursuing, and worth backing.


Apple’s complaint will be tested, as it should be, and the allegations remain just that — allegations. But the strategic signal is already unmistakable. When the most valuable company in the world wants to defend its future, it reaches for trade secret law. Certum Group’s Trade Secret Guide is built to help plaintiffs and their counsel do the same, whatever their size, and this case is a live illustration of why that playbook matters now more than ever.


Certum Group can help. If you are evaluating a trade secret dispute or want to talk through options for funding or de-risking one, get in touch.


Footnotes


¹ Complaint, Apple Inc. v. OpenAI, Inc., No. 5:26-cv-07078 (N.D. Cal. filed July 10, 2026); see Apple sues OpenAI over alleged trade secret theft, TechCrunch (July 10, 2026).

² The wildest allegations in Apple's trade secrets lawsuit against OpenAI, TechCrunch (July 13, 2026).

³ Id.

Apple sues OpenAI over alleged trade secret theft, TechCrunch (July 10, 2026).

Apple sues OpenAI alleging trade secret theft, says scheme was "at every level," CNBC (July 10, 2026).

The wildest allegations in Apple's trade secrets lawsuit against OpenAI, TechCrunch (July 13, 2026).

⁷ Id.

⁸ Id.

⁹ Id.

¹⁰ Apple sues OpenAI over alleged trade secret theft, TechCrunch (July 10, 2026).

¹¹ Id.

¹² OpenAI Asks Judge to Toss Apple's Trade Secrets Lawsuit, Claims Journal (Aug. 7, 2026).

¹³ Id.

¹⁴ OpenAI says Apple's own security practices undermine its trade secrets case, TechCrunch (Aug. 6, 2026).

¹⁵ Id.

¹⁶ OpenAI Asks Judge to Toss Apple's Trade Secrets Lawsuit, Claims Journal (Aug. 7, 2026).


Certum Group Can Help

Get in touch to start discussing options.

Recent Content

By Certum Group Team August 13, 2026
Certum Group is pleased to announce that Chris Seidl has been named to the 2026 IAM Strategy 300: The World’s Leading IP Strategists list. IAM Strategy 300 is a global ranking of IP strategists who are leaders in developing and implementing strategies to maximize the value of IP portfolios. IAM identifies individuals through extensive research annually. Chris leads Certum’s IP finance strategy, including IP licensing, litigation funding, and acquisitions. This is the fifth consecutive year Chris has been included on the IAM Strategy 300 list.  Click here to see the complete rankings.
By Certum Group Team August 4, 2026
Artificial intelligence is quickly changing how legal work is researched, drafted, reviewed, and delivered. But while AI can improve efficiency, it also creates serious risks, including inaccurate analysis, fabricated citations, and potential court sanctions.  In this webinar, Certum Group brings together legal and business experts to discuss how lawyers can use AI to strengthen their work without compromising accuracy, professional judgment, or accountability.
By Certum Group Team July 29, 2026
Artificial intelligence is transforming all corners of the economy, and the legal profession is no different. At first it seemed the stories about AI and the law were all negative, as many lawyers , even those at some of the most prestigious firms , found themselves sanctioned for filing briefs with hallucinated cases. More recently, the news cycle has turned, as existing law firms embrace AI and new firms sprout to deliver AI-first legal services. Just recently, top lawyers from Kirkland & Ellis and Quinn Emanuel each left to launch their own law firms. Meanwhile, Kirkland, the AmLaw 1 firm, announced it would invest $500 million to develop its own proprietary AI system. [ Click here to read a Bloomberg article by Certum’s Will Marra on what Kirkland’s AI announcement means for the future of third-party legal finance.] This can be dizzying for many lawyers. Clients want them to use artificial intelligence. Competitor law firms are using AI. But the risks of misusing AI are high and can even include sanctions and media coverage that gives lie to the old adage that “all news is good news.” A Transformative New Tool To help lawyers navigate this landscape, Certum Group recently hosted a webinar to help lawyers navigate the landscape. Our featured speaker was Michael Showalter , founder of Showalter PLLC, a litigation firm built around AI tools, and a former appellate lawyer at Gibson Dunn and Wiley Rein. The conversation was led by Suneal Bedi , Certum’s Scholar in Residence who is a professor at Indiana University’s Kelley School of Business. This was the first in a series of conversations that Professor Bedi will lead designed to help Certum’s clients navigate the toughest challenges they face today. In the webinar, Showalter demonstrated the power of AI by sharing several moments that “blew his mind” over the past year: A first draft of a law review article that was better than what he’d get from most junior lawyers. T urning a project that once took 100–150 hours into roughly only 15. A flawless table of authorities, table of contents, and cite-check on a brief, produced in about ten minutes. He noted he’d never once received a flawless table of authorities from a human paralegal. Sophisticated legal reasoning; identifying an overlooked antecedent argument in a forthcoming Yale Law Journal article showing the tools do real analysis, not just “automatable” formulaic work. He now estimates he accomplishes in a single day what would have taken him 40 hours of work back in 2022. Three key takeaways emerged from the webinar. To Be a Good Lawyer With AI, First Be a Good Lawyer AI cannot replace legal judgment, but it can amplify it. Lawyers should not outsource the job of lawyers to an AI model. They should treat the models instead like highly capable but error-prone junior associates. This means they should ensure the model has sufficient context about the legal issue they’re asking it to address. And you should give senior-lawyer leadership and oversight to its work. You should also treat AI errors as inevitable, the same way junior lawyers will inevitably make mistakes. Be vigilant to when the model gets something wrong, fix the error, and do what you can to avoid the error from recurring in the future. And you should iterate constantly. AI workflows cannot be completed in a single prompt. Lawyers should consistently redline and comment on the AI’s outputs to refine and perfect the work product. Guard Against Hallucinations and Errors Lawyers are rightly concerned about the prospect that AI may rely on fabricated cases. The webinar offered some candid commentary on this issue: First, the technology has changed dramatically between 2024 and 2026. The incidence of hallucinated and fabricated cases is much rarer today than in the past, partly because the frontier labs have focused on addressing this problem. Second, verification tools now exist. Tools like Veritas now exist to compare every quote in a brief against its primary source, catching errors rather than predicting text. Third, senior oversight remains non-negotiable. Lawyers should not assume an AI will accurately describe a case any more than they should assume a junior associate will do so. Lawyers should read and review every case they cite for accuracy and reliability. Meet Your Clients’ Expectations and the Courts’ Requirements Finally, it is clear that the market is shifting towards the expectation that lawyers will use AI. Even the most sophisticated clients are now demanding that their clients use AI. And they are relying on the existence of AI to push down rates and demand that simpler tasks get outsourced to artificial intelligence. For example, Sebastian Niles, the President and Chief Legal Officer of Salesforce, recently published an article arguing that the integration of AI into law firms should be a baseline expectation. [Harvey AI’s CEO, Winston Weinberg, was recently the keynote speaker at an NYU Law School conference co-organized by Professor Bedi and Certum’s Will Marra. Click here to learn more about the takeaways from that conference.] At the same time, courts have stepped in to closely police how law firms are using AI. Some courts are even amending local rules to regulate the use of AI in legal filings. To be a great lawyer today and tomorrow, lawyers need to stay on the cutting edge of artificial intelligence. Clients demand it, and courts do too. Lawyers should continue to educate themselves about how to best use AI to improve and amplify their work, but not to replace it.