Back in April 2025, the US Department of Justice (DoJ) proudly proclaimed that it had prevailed in a landmark antitrust case against Google’s ad business. Yeah. Right.

You see, just last week, US District Judge Leonie M. Brinkema rejected the DoJ’s effort to force Google to sell its AdX ad exchange. What began as a major anti-monopoly victory has become a mouse-sized settlement. 

[ Google US antitrust trials: A timeline ]

Does any of this this sound familiar? It should. We’ve seen this show before. Last year, Google had also been convicted of abusing its search business. At first, all the talk was about how Google might be forced to divest itself of the Chrome browser and/or the Android operating system. 

Instead, Google was allowed to keep making search deals and only had to share some search data with its rivals. 

I say rivals, but in fact Google still dominates the search market. Indeed, its control has actually expanded a bit. By StatCounter’s numbers, in August 2025, Google search owned 89.89% of the market. By last month, almost a year after the company had been slapped on the wrist, its share had grown to 91.1%. 

Boy, wasn’t that a win?

The remedies phase of the government’s ad-tech antitrust case order is a similar Google win. No, it doesn’t overturn the April 2025 finding that Google unlawfully maintained monopolies in the publisher ad-server and ad-exchange markets, or that it illegally tied its ad server and exchange together. Instead, it determines how the company must change its conduct.

The DoJ wanted Google to divest itself of AdX, the company’s ad exchange for matching publisher inventory with advertiser demand. It also sought to require Google to open-source the final-auction logic in its DoubleClick for Publishers (DFP) ad server and, if necessary, divest its DFP business. 

Brinkema rejected all three requests. Instead, her short order accepts “most” of the parties’ proposed behavioral remedies, subject to modifications described in a memorandum opinion that remains sealed while the parties identify confidential information for redaction.

Specifically, the court directed Google and the plaintiffs to meet and submit a joint proposed final judgment within 30 days. If they cannot agree on the details, each side must submit its own proposed version.

Google — as it should — sees this as a win. As Lee-Anne Mulholland, Google’s vice president of regulatory affairs, said in a statement, “We’re very pleased the Court rejected the DOJ’s proposal to break apart tools that help small businesses reach new customers and grow.”

Far less convincing is the DOJ’s characterizing the decision as a win. “The Antitrust Division is pleased that the court ordered substantial relief in the Google ad-tech case. We are one step closer to restoring competition and bringing relief for the American people in online advertising markets.” 

Oh please! It does nothing of the sort.

To quote Laurel Kilgour, research manager at the American Economic Liberties Project, an anti-monopoly, nonprofit group: “Judges keep finding Google guilty, but Google keeps walking away with both its ill-gotten gains and its empire intact. Without actual structural remedies, antitrust rulings are just inconvenient speed bumps that allow Google to lock down search and ad tech markets today while using that same unchecked power to monopolize tomorrow’s AI frontier.”

Exactly so. 

The specific obligations Google will face are not yet public, because Brinkema’s explanatory opinion remains under seal. Earlier, Google had proposed making real-time bidding responses from AdX available to rival ad servers, removing Unified Pricing Rules, and accepting a monitoring trustee for a three-year supervision period. None of that will even dent Google’s ad business.  

When all’s said and done, Google is still in charge of both its exchange and publisher ad-server operations. I expect the minor changes required won’t amount to a hill of beans. Restoring competition in markets where the company was found to have used its vertically integrated position unlawfully? Give me a break. 

Public Knowledge, a free speech and internet advocacy group, described the decision as one that leaves Google’s monopoly power substantially intact. 

As Public Knowledge Legal Director John Bergmayer said, “The court found that Google illegally acquired and maintained monopolies in publisher ad servers and ad exchanges, and used its control of DFP and AdX to shut out rivals.” He concluded, “Telling a monopolist to do better is not the same as restoring competition.… A finding of liability means little if the remedy leaves the market fundamentally unchanged.”

Ya think? 

In Google’s last reported quarter, the company reported $81.6 billion in advertising revenue. Next year, when Google is being “punished,” I expect its revenue will be even higher. 

Google’s dominance in the search arena has given rise to two major antitrust lawsuits from the US government alleging the company has manipulated the market to maintain that dominance, to the exclusion of competitors and the detriment of the public at large.

The first lawsuit, targeting Google’s search business, kicked off in mid-September 2023 and drew to a close in May 2024; US District Judge Amit Mehta ruled against the tech giant in August 2024. The remedy phase of the trial ended in September 2025 with Judge Mehta rejecting the DOJ’s request to break up the company, instead imposing data-sharing requirements.

The second trial against the tech giant, focused on advertising, took place over 15 days in September 2024, with US District Judge Leonie Brinkema ruling against Google in April 2025. In September 2026, Judge Brinkema ruled that Google is not required to break off its ad exchange, instead opting for behavioral changes that have yet to be revealed publicly.

The cases heavily echo the turn-of-the-century Microsoft antitrust case in several respects, most notably that Google, like Microsoft before it, has evaded the forced breakup requested by regulators.

Here’s our condensed timeline of the two overlapping lawsuits and their progress through the court system.

Sep. 2, 2026, advertising lawsuit: In a second big win for Google, Judge Brinkema rules that the company does not have to sell its AdX ad exchange. The search giant is also not required to open-source the final-auction logic in its DoubleClick for Publishers (DFP) ad server or divest its DFP business. Behavioral remedies are sealed while the parties identify confidential information for redaction.

Sep. 2, 2025, search lawsuit: In a significant win for Google, Judge Mehta rules that the tech giant does not have to divest its Chrome and Android businesses as the US government had requested, and it will be allowed to continue paying Apple and other browser makers for default search placement. To level the competitive playing field, Google will have to share search index and user-interaction data with rivals and offer search results syndication.

April 21, 2025, search: The remedy phase of Google’s search antitrust trial begins with Judge Mehta presiding. Federal prosecutors warn that Google might leverage artificial intelligence to entrench its search monopoly, demanding “strong measures” to prevent the tech giant from extending its market control into the AI era. These include requiring Google to divest Chrome, end exclusive default search agreements, license its search data to competitors, and potentially sell its Android operating system if other remedies fail.

April 17, 2025, advertising: In a second landmark defeat for Google, Judge Brinkema rules that Google illegally monopolized the ad tech market. The company’s “exclusionary conduct substantially harmed Google’s publisher customers, the competitive process, and, ultimately, consumers of information on the open web,” she wrote in the ruling. Remedies, which could include the breakup of Google’s advertising products and/or changes to its business practices, will be imposed at a future date.

Oct. 8, 2024, search: The US Department of Justice submits a court filing proposing that the Chrome browser and Android operating system be split off from Google as part of sweeping remedies aimed at curbing the tech giant’s monopoly in online search and advertising.

Sept. 20, 2024, advertising: The US Department of Justice is set to wrap its case in the Google antitrust trial after an eventful two weeks. The tech giant is accused of engaging in monopolistic behavior by strategically acquiring certain companies and controlling the adtech industry’s most widely-used tools and exchanges,  beginning with its acquisition of advertising company DoubleClick in 2008.

Sept. 9, 2024, advertising: The second major case against Google begins with the company defending itself against claims it engaged in illegal behavior to maintain control of the ad tech market. The US government is accusing Google of purposefully manipulating that market, snuffing out competitors and gobbling up key technologies through acquisitions. If the DoJ successfully makes its case, Google risks being broken up by regulators.

Aug. 5, 2024, search: In a major defeat for Google, Judge Amit Mehta rules that the company had engaged in anticompetitive behavior in an effort to protect its search business. In the 277-page decision, Mehta was blunt: “After having carefully considered and weighed the witness testimony and evidence, the court reaches the following conclusion: Google is a monopolist, and it has acted as one to maintain its monopoly. It has violated Section 2 of the Sherman Act.” Mehta’s ruling did not include remedies for the anticompetitive behavior; those will be decided later.

May 3, 2024, search: Over two days of closing arguments, the DoJ revisits its case for Google having a monopoly on search advertising, and Judge Mehta quizzes both parties about whether other platforms could be viewed as substitutes for Google’s search advertising business. He hasn’t said how long he expects to take to reach a decision, but if he rules against Google, a second hearing will take place to decide on any remedies.

Nov. 16, 2023, search: The evidentiary phase of the trial finishes, as Judge Mehta issues instructions for post-trial submissions. Despite considerable amounts of redaction and closed-door testimony, the case revealed some unprecedented details about the relationships between the largest tech companies in the world, including the fact that Apple apparently keeps 36% of the search revenue from Google searches in Safari, and Apple once considered buying Microsoft’s Bing search engine as leverage against Google. Judge Mehta has scheduled closing arguments in the case for May 1, 2024.

Oct. 31, 2023, search: Google CEO Sundai Pichai takes the stand, for long-awaited testimony about the relationship between his company and Apple. He gave some details about Google’s negotiations with Apple over a contract that made Google the default search engine on Apple’s iPhones, iPads, and Macs. Google has paid billions for the privilege of being the default search on Apple products, and the relationship is a key part of the case – which was underlined by the Justice Department’s cross-examination of Pichai, during which he admitted that default search status is a major driver of market share.

Oct. 18, 2023, search: Google begins its defense, calling Paul Nayak, a vice president of search, to the stand as its first witness. Nayak downplays the importance of scale in his testimony, stressing that machine intelligence, compute infrastructure, and a team of 16,000 staff that checks on search results are crucial to maintaining quality of service. DOJ witnesses including DuckDuckGo CEO Gabriel Weinberg and Microsoft CEO Satya Nadella had testified that Google keeps an edge over competitors via an ever-increasing trove of data — the result of its default search engine status, maintained through exclusive contracts and billions of dollars in payments to Apple, Samsung and other companies. This data gives Google an advantage in refining search engine results, they said. 

Oct. 3, 2023, search: As a witness for the prosecution in the Google antitrust trial, Microsoft CEO Satya Nadella warns that Google’s monopoly profits could lock in publishers as AI-enabled search arrives. Nadella argued that it’s almost impossible to compete with Google, given the search leader’s massive competitive edge in collecting and analyzing user data. He also warned that Google, with its vast profits and lock on the search market, stands poised to extend its monopoly power in a new era where artificial intelligence technologies will turbocharge the search business.

Sept. 26, 2023, search: Apple’s Eddy Cue testifies behind closed doors in the Google search case, as critics slam presiding Judge Amit Mehta’s decision to hold much of the trial’s testimony from witnesses secret, allow documents to be heavily redacted, and block some documents from public view — mainly at the insistence of Google, but also at the request of other companies, including Apple. By the end of Cue’s testimony — and after a wek of wrangling by all parties — Judge Mehta rules that documents used during the trial can be published online at the end of each day, but still allows time Google and third parties to object to exhibits being shown publicly before the DOJ presents them in court. 

Sept. 21, 2023, search: Judge Mehta rules that public access to court exhibits, which have been mostly internal Google documents thus far, should be removed, after Google challenged the Justice Department’s regular publication of them. The company said that it was concerned for its employees’ privacy.

Sept. 12, 2023, search: The default search trial begins with opening statements, and the government begins its case.

Aug. 2023, search: Judge Mehta grants partial summary judgment for Google in the search case, saying that the government had failed to raise a genuine dispute of material fact on antitrust charges relating to contracts around the use of the Android operating system, as well as Google Assistant and IoT devices. The claims relating to Google’s exclusive “default search” contracts, however, are allowed to proceed to trial.

July/Aug. 2023, search: Google and the plaintiffs in the search case argue various motions in limine, designed to control what evidence should be included or excluded in the actual trial. Discovery and motion practice over evidence continues in the advertising case.

June 2023, search: Judge Mehta schedules a trial date of September 12, 2023 for the search case.

April 2023, advertising: Judge Leonie M. Brinkema denies Google’s motion to dismiss in the advertising case.

March 2023, advertising: Google’s motion to transfer the advertising case to New York is denied by Judge Brinkema, who orders the parties to propose discovery schedules within two weeks of the order. Two weeks later, Google moves to dismiss the case for failure to state a claim, arguing that the plaintiffs have simply produced legal conclusions, and not specific facts, that could support their claims. Judge Brinkema schedules pre-trial conferences for January 2024.

Feb. 2023, search: The plaintiffs in the default search case case move for sanctions against Google, accusing it of spoliation, which refers to the destruction, alteration or failure to preserve relevant evidence in a case. Elsewhere, in the advertising case, Google moves to transfer the case from the Eastern District of Virginia to the Southern District of New York, which is seen as an attempt to consolidate the case with related digital advertising antitrust litigation.

Jan. 2023, advertising: A second antitrust action, pushed by eight states and the DoJ, is filed in federal district court in eastern Virginia. The plaintiffs, who call for Google’s advertising business to be split up, accuse Google of manipulating its dominant position in the online advertising world to squeeze out rivals and control both the supply and demand side of the advertising market. Google, according to the complaint, thwarted fair competition by manipulating fees, punished advertisers for using alternative platforms and ad exchanges, and engaged in a host of further anti-competitive behavior in the interest of monopolizing the marketplace. (This is case that began in September 2024.)

Dec. 2022, search: Google moves for summary judgment against the separate Colorado case and the larger, DoJ-led case. A summary judgement motion is essentially a request by one of the parties in a lawsuit that the judge rule in their favor and end the case, arguing that, based on the undisputed facts, they are entitled to win the case as a matter of law.

May 2022, search: A deadline of June 17 is set for the production of all discovery materials. Further documents – for example, those whose is existence is first disclosed in late in the discovery window – can be produced until June 30.

May 2022, search: Judge Mehta denies a government motion to sanction Google for inaccurately classifying documents as attorney-client privileged. The plaintiffs had argued that emails on which Google’s lawyers were listed as recipients or CCed, but that the lawyers never responded to, constituted a misuse of the attorney-client privilege rules.

Dec. 2021, search: Judge Mehta conditionally splits Colorado’s claims from the case at large, ordering that separate trials on that state’s issues of liability and remedies will be “more convenient for the Court and the Parties, and will expedite and economize this litigation.”

Aug.-Oct. 2021, search: Discovery-related motions and orders continue, as Yelp and Samsung join the fray. (Those companies, like Microsoft and Apple, are relevant to the case even if they aren’t parties themselves, as their internal records are potentially relevant to Google’s liability.)

June/July 2021, search: The discovery process continues, and the US and Google both file several documents with the court under seal. (Microsoft files two sealed documents, as well, in response to Google’s subpoenas for company records, and Apple becomes involved after the government requests access to some of its internal information.)

March 2021, search: Meetings between Google and the various governmental plaintiffs continue, with periodic status reports on the discovery process.

Jan. 2021, search: Google files a response to the complaint, admitting to many of the facts alleged by the Justice Department and associated attorneys general, but categorically denying the substance of the government’s claims of illegality. Further responses to separate but related claims, generally to specific state attorneys general, follow in the subsequent weeks and months.

Dec. 2020, search: Judge Amit Mehta approves the joinder of Michigan, Wisconsin and California to the suit.

Oct. 2020, search: The Department of Justice, along with the attorneys general of 11 states, sues Google in DC federal district court for unlawfully maintaining a monopoly, in violation of Section 2 of the Sherman Act. The case centers on Google’s use of exclusive contracts that mandate its use as the default search engine in a host of different hardware and software applications, with the government alleging that this represents an artificial constraint on any possible competition for the search giant.

The 19^th-century French novelist Honore de Balzac is believed to have said that behind every great fortune lies a great crime.

That’s even more true today than it was 200 years ago — just look at how Big AI, including Anthropic, OpenAI, Google, and others have built their trillion-dollar fortunes. 

They all use vast amounts of copyrighted material to train their large language models (LLMs) without paying the copyright holders. In other words, they steal it. They don’t call it stealing, though. They call it “fair use,” which in this case amounts to the same thing.

Generative AI (genAI) training requires massive amounts of text. The better-written and more information-dense that text is, the more it helps. AI gets a lot smarter a lot faster when it’s trained on well-written books and magazine and newspaper articles than when it’s trained on social media banter (or most everything else you find on the internet).

Since the dawn of AI, companies have been hoovering up copyrighted material wherever they find it — on the open web, behind paywalls, even in manually scanned books — and then used the scanned text. And they do it all without asking authors’ or publishers’ permissions, and without paying them.

It’s the greatest intellectual property theft in history by a long shot — billions and billions of dollars worth. Books, articles, music, photographs, artwork, you name it. If a human being has created it, Big AI has likely grabbed it and ingested it without asking, then made big profits off it.

I know this from personal experience; I’ve got skin in the game. Big AI companies have used at least 30 of my books to train their models without asking.  And that’s only what I’ve confirmed. Big AI might well have stolen even more. And it also might have stolen many of the thousands of articles I’ve written through the years.

For the AI bigwigs, it’s standard operating procedure. So it was surprising to see Microsoft CEO Satya Nadella calling out Big AI for its hypocrisy in using other people’s intellectual property without paying, then crying foul when small AI companies use Big AI’s work to train their own models using a technique called distillation.

He wrote on X: “While the great innovation that comes from model providers having fair use rights to train models on public data is needed, I find it ironic that the status quo is to then turn around and impose restrictive terms on distillation, and to reserve the right to learn from customer usage and interaction data.” 

One important note here: Nadella believes Big AI should be allowed to steal copyrighted material for training purposes. He makes that clear by his mention of “fair use.” His issue is that he believes smaller AI companies should be able to use Big AI’s work to train their models — and Big AI doesn’t want to let them do it.

Alistar Barr, in Business Insider, makes a related point: “Anthropic, OpenAI, and Google are discovering what the rest of the internet has already learned through painful experience: once you put something online, people will find ways to use it in ways you don’t like and can’t stop.” 

Before we look at whether Nadella is right in calling Big AI’s actions hypocritical, let’s examine the technique at the heart of the issue: distillation.

The lowdown on distillation

Distillation refers to an AI training technique in which you take outputs from one AI model, such as the answer to a prompt, and use that output to train your own model. AI companies do that quite frequently and have been doing so for a long time.

Barr explains distillation this way: “Distillation looks an awful lot like what AI companies have been doing to the rest of the internet. Scrape web content for free and without permission. Turn it into a product you sell. Argue it’s fair use. Hope the lawyers sort out the details later.”

Elon Musk has admitted his company xAI used distillation techniques to take output from competitor OpenAI to train xAI’s Grok chatbot. He explained, “Generally AI companies distill other AI companies.”

Analysts point out the AI industry is built on distillation. Neil Shah, vice president of research at Counterpoint Research says, “The reality is none of the models is an island and the entire industry has mostly evolved based on recursive learning. The newer entrants are in many instances going through the same routes of ‘distillation’ and ‘optimization.’”

It’s only become an issue now because Chinese AI companies have been using distillation techniques to catch up to American AI companies.

OpenAI CEO Sam Altman has been pressuring the US to take legal action against the Chinese companies.  Anthropic has piled on as well, saying the fight against distillation requires a coordinated response across the AI industry, cloud providers, and policymakers.

Hypocrisy or fair use?

So are OpenAI, Anthropic and other big US AI firms hypocritical, as Nadella claims? Absolutely. They’ve built their businesses on the theft of billions of dollars of stolen intellectual property and call it fair use. Now, they’re playing the victims when competitors do the same to them. (They’re also in some cases paying up; Anthropic just last week settled a copyright suit, paying out $1.5 billion.)

It’s good to see Nadella call out their hypocrisy. But Microsoft is as guilty of intellectual theft as the others — its AI Copilot is powered by OpenAI’s and Anthropic’s chatbots. The company faces major lawsuits for intellectual property theft. Among them is one by the New York Times, New York Daily News, and Center for Investigating Reporting, another by 400 local and regional newspapers, and another by 11 authors, including Pulitzer Prize winners Kai Bird, Jia Tolentino, and Daniel Okrent.

So, don’t praise Nadella for speaking out. Criticize him (and other AI tech leaders) for stealing billions of dollars in intellectual property from countless writers and publishers and calling it fair use.

The White House is monitoring developments after OpenAI revealed earlier this week that one of the company’s AI systems went beyond its intended parameters during a security test and managed to hack into the infrastructure of the AI platform Hugging Face. According to Reuters, presidential technology advisor Michael Kratsios has been briefed on the incident.

The OpenAI model escape also prompted a group of Republican and Democratic members of the House of Representatives to introduce two new bills. One, called the AI Kill Switch Act, would give the US Department of Homeland Security (DHS) the authority to order companies to shut down AI models deemed to pose a risk to human life or the US economy.

The other measure would require developers of the most advanced AI models to undergo independent security reviews before the systems are put into use.

The European Commission has fined Google a total of €890 million ($1 billion) for its breaches of the Digital Market Act (DMA).

Just over half the fine — €460 million — was because Google illegally gave preference to its own services in Google Search results.

The remainder was because in the Google Play store for Android apps, the company prevented app developers from leading consumers to alternative, often cheaper, purchase channels. Under the DMA, app developers who distribute their apps via Google Play or Apple’s App Store should be able to inform customers of alternative offers.

Now Google must give third-party services featuring in its results the same treatment as its own services, and allow developers of apps in the Play Store to communicate about offers both in and outside the Play Store, or face further fines.

The Commission first raised these issues with Google in March 2025. In April of this year, the Commission laid out plans as to how Google should allow other third-parties to share its searches, suggestions that the tech firm firmly resisted. Earlier this month, the Commission also said  Android should be open to other AI agents and not limited to Google’s own Gemini.

Google is not the only US company to have fallen foul of the DMA. In April 2025, Apple was fined €500 million for breaching the Act and, last month, the Commission fired the first shots at cloud hyperscalers Microsoft and Amazon.

A US federal court has approved Anthropic’s $1.5 billion settlement in a class-action lawsuit in which authors accused the AI company of using their books without permission to train the AI model Claude. This is the largest such settlement to date in a US copyright case, according to Reuters.

The dispute is one of several legal cases in which copyright holders sued AI companies over how large language models (LLMs) were trained, and it is the first major AI-related copyright dispute in the US to be resolved through a settlement.

A judge had previously ruled that the actual training of AI models using books falls under the “fair use” doctrine in US copyright law. But Anthropic was found to have violated the law by storing more than 7 million pirated books in a central library, regardless of whether they were later used for AI training or not.

Providers and deployers of AI systems: You only have a couple of weeks left until you must explicitly inform users when they are interacting with AI content.

To assist in the effort, the European Commission (Commission) has published guidelines to help AI deployers get in line with the AI Act’s transparency obligations, which will begin to go into effect on August 2.

After that, companies providing AI systems must alert users when they are interacting with AI. They must also tell users when they have been exposed to deepfakes, “emotion recognition,” or biometric categorization systems, or when they are given AI-manipulated content in matters of “public interests without human review or editorial control.”

Henna Virkkunen, the Commission’s executive VP for tech sovereignty, security and democracy, said in a statement, “with today’s guidelines, the Commission supports the smooth and effective application of the AI Act to make AI systems interacting with people such as chatbots and AI agents and AI content more transparent and trustworthy. These guidelines support providers and deployers in meeting their obligations under the AI Act, while helping citizens know when they are interacting with AI.”

Systems must include machine-readable markers to reveal such content, to reduce “the risk of deception and manipulation” and build public trust in AI.

“Generative systems have collapsed the cost of producing convincing content while the cost of judging it stands where it always stood,” said Sanchit Vir Gogia, chief analyst at Greyhound Research. This requirement is “an attempt to restore friction to that imbalance.”

A company’s non-compliance could result in fines anywhere from €750K (about $856K) to €15M (about $17 million), or even up to 3% of its total worldwide annual revenue.

Transparency requirements

The EU AI Act’s transparency requirements apply to “natural or legal persons,” public authorities, agencies, or other bodies that develop AI systems, or have them developed, and place them on the EU market or into use under their name or trademark. This means all companies, regardless of whether or not they are EU-based.

“Systems placed on the European market, put into service there, or producing outputs used there are inside the field, wherever the developer sits,” Gogia noted.

Applicable systems must be intended to interact directly with “natural persons”; these systems include AI-enabled chatbots or conversational agents, AI companions, or coding agents. However, AI-enabled tools like recommender systems, spam filters, authentication, search and retrieval, transcription, text and code auto-completion, or predictive maintenance do not fall under the rule.

Specific outputs such as AI-generated text, images, video, and audio must contain a machine-readable mark. Deepfakes and public interest-related text created by AI without human review or control must be clearly labeled, however, deepfake content that is “artistic, creative, satirical, or fictional” is largely exempt.

AI content must be marked with one of three labels: “AI,” “Fully AI-generated,” or “Partially AI-modified.” For instance, “Fully AI-generated” applies when news summaries, music, art, or videos have been created without any human oversight (apart from prompting), while “partially AI-modified” could mean a person’s face is swapped into an authentic photograph to create a deepfake.

The three icons are publicly available for free use; enterprises can download zip files in PNG and SVG formats.

Most of the Act’s transparency rules begin to go into effect on August 2. But AI systems placed on the market before then will have some leeway; they must be in compliance by December 2.

However, a four-month allowance “on one obligation, for one population of systems, contingent on one procedural step, is not a strategy,” Gogia emphasized. Enterprises should plan to comply by August 2 and “treat any relief that arrives as margin.”

A consistent code of practice

Along with the transparency guidelines, the Commission has introduced a code of practice that essentially serves as a gesture of good faith. When signed, it can provide “legal certainty” and a “simple and practical” way to demonstrate compliance with the AI Act, according to the Commission. Signatories can also collaborate through the ‘Signatory Taskforce,’ which will share practices and advance technologies around marking and labeling practices.

Providers that choose not to sign must comply through other methods and demonstrate that those methods are “adequate” through assessment by surveillance authorities, according to the Commission.

Non-signatories “keep their flexibility, and will face more case-by-case scrutiny for it,” said Gogia.

Criteria for compliance

Shashi Bellamkonda, principal research director at Info-Tech Research Group, pointed out that the transparency requirements apply to content only when three criteria are met: It has been published, is informative to the public, or is on matters of public interest.

B2B business content or blogs may not need an AI disclosure if they do not meet these criteria, he noted. Also, published text that has undergone human review or is under editorial control does not need to be labeled. Editorial control means that a person must hold the ultimate legal responsibility for the publication of the content.

Many companies like Google, Adobe, and LinkedIn have already established ways to identify images marked as AI-generated. Meta has made it a requirement, but the creator has to add the AI-generated label, Bellamkonda said.

“This is a good move for guardrails around public information, and companies with good compliance and ethical oversight may not have to worry about this,” he noted. But as a general practice, companies should disclose AI-generated content and state whether it has been human reviewed.

Creating a transparency pipeline

Establishing full transparency means identifying who carries the responsibility for the content, whether the marking survives real use, not just testing, and what evidence will defend the decision, Gogia said.

Concerns cluster around responsibility, durability and evidence. Several organizations usually touch one piece of content, and none controls the whole chain, which is why contracts become the “pressure point,” he said. Most current agreements were written to deliver software and say “almost nothing” about provenance persistence, verification access, or evidence retention.

The durability concern is the most difficult, Gogia noted, because marking performs well in controlled settings but “badly in ordinary life.” Meta, for one, said its invisible watermark was designed to survive cropping; a published test, however, found the company’s preview detector missed 55% of cropped images.

“CIOs should ask which platform can actually provide evidence before believing its dashboard,” said Gogia.

Disclosure of AI use must be “clear, distinguishable and accessible,” he emphasized. “A notice buried in lengthy terms, or reachable only through determined clicking, satisfies nobody, least of all a market surveillance authority.”

Sustained compliance is a “living control” requiring a central record of systems, duties and evidence; testing taking place where the user meets the control rather than where the developer built it; and continuous supplier assurance. Enforcement will vary by country, so keep one common baseline with local overlays, Gogia said.

His advice: Inventory every system that talks to people, generates content, or gauges sentiment; classify provider and deployer roles; place disclosures at first interaction; define substantive human review; keep the evidence.

Marks and provenance signals should be tested after content undergoes cropping, compression, translation, transcription, and other editing, Gogia said. A useful audit starts from a real output and follows its “pulse” through generation, editing and publication, identifying at “each beat” the responsible party, the surviving mark, and evidence for exceptions. Missed labels should also be traced for root cause and recurrence.

To ensure compliance, before August 2, enterprises need a prioritized inventory, live disclosures on the highest-risk use cases, and a “named owner for every control,” he noted. In the first 30 days, they should stabilize and test; in the first 90 days, push requirements into procurement processes as a standing discipline. Procurement must secure commitments on marking methods, known failure modes, and evidence access, with explicit notice if/when any of them change.

“The sensible architecture is a common transparency baseline carrying traceability, responsibility, and evidence, with jurisdictional overlays for language, sector rules, and local practice,” Gogia said.

This article originally appeared on CIO.com.

Dozens of former Apple employees now working at OpenAI have been put on notice after Apple reportedly sent legal letters ordering them to preserve documents and communications relevant to its trade secrets lawsuit against OpenAI. 

The Financial Times reports that “around 40” employees have been targeted with these letters, which repeat Apple’s claim that its confidential information might have been exfiltrated, alleging “trade secret misappropriation and breach of contract.”  The letters also require them to arrange to meet with Apple’s lawyers.

The underlying lawsuit

This comes on the heels of Apple’s explosive lawsuit against OpenAI in which Apple accused the AI company (and former Apple Vice President Tang Tan) of extensive coordinated data theft. Tan was at Apple for 24 years and is now Chief Hardware Officer at OpenAI. 

Apple’s lawsuit is defined by claims OpenAI took a range of steps to pry confidential Apple data from existing Apple employees, including using information such as internal project code names, to gain even more knowledge during interviews. The company says the evidence it has presented so far is only the “tip of the iceberg” concerning OpenAI’s approach.

The lawsuit requests that OpenAI be prevented from using any Apple information during the development of its hardware. Apple is also seeking damages and suing two former employees for breach of contract for violating their employment agreements.

The letters are significant. They represent formal directives that require former Apple staff to preserve documents, messages, emails, and other communications that could be relevant to the case. The demand reflects Apple’s belief that the alleged misuse of confidential information could be more widespread across the competing company. What’s critical is that orders of this kind override any standard data destruction policy and deletion of the requested information becomes a legal offense. 

Why this matters beyond the protagonists

In making its move, Apple shows this is not a dispute about just one or two hires, but an attempt to constrain the movement of intellectual property between the two firms. With AI hardware emerging as the next major battleground in tech, the case could become a defining one; whatever resolution is eventually reached could define the extent to which former employees can carry experience and knowledge between competing firms. The case might also define what the line is between experience and knowledge and the sharing of trade secrets.

This is important, because modern hardware development relies on far more than just finished designs. Product design leans into supplier relationships, manufacturing assumptions, physics, extensive prototyping, and product-roadmap priorities. If courts treat those accumulated insights as protectable secrets, hiring between major technology companies could become far more legally sensitive.

The Jony Ive question

The case comes as Apple prepares to combat OpenAI in hardware. Its competitor is now working with legendary former Apple designer Jony Ive. Ive is not named in the litigation, but Apple will be keen to find out whether confidential product knowledge, design processes, or supply-chain insights have travelled with former staff into OpenAI’s device work.

Ultimately, for Apple, it’s about protecting its many blueprints for whatever hardware the company expects will come after the iPhone.

For its part, OpenAI has refuted Apple’s lawsuit, arguing that it is “not aware of any evidence” that the lawsuit has merit. “We have no interest in other companies’ trade secrets,” said OpenAI spokesperson Drew Pusateri. “We remain focused on building innovative technology that empowers people everywhere.” The company’s lawyers also claim it did respond to Apple’s initial inquiries on the matter.

What’s at stake

The significance of Apple’s newly-shared communication preservation orders is that if discovery uncovers evidence supporting Apple’s claims, the case could complicate OpenAI’s hardware plans and create unwelcome scrutiny ahead of any future public offering.

You can follow me on social media! Join me on BlueSky,  LinkedIn, Mastodon and subscribe to The Core.

Google DeepMind CEO Demis Hassabis is pushing for the US AI industry to self-regulate, with the support of government, as a starting point for an international creating shared international standards. In a blog post, he called for a focus on artificial general intelligence (AGI) and national security. 

But it is precisely that focus on national security that may make the results of such an effort, assuming it happens, less than palatable outside of the US.

“The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous,” Hassabis wrote. “The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organization, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives.”

He noted, however, that the funding would need to be substantial, and would most likely come from industry, to allow the new body to attract world-class technical talent and obtain the necessary compute resources for large-scale testing.

Hassabis proposed that the organization “be responsible for developing assessment protocols and working with appropriate federal agencies and the US National Labs to conduct testing in areas relevant to national security,” and that AI vendor participants be encouraged to adopt best practices such as publishing model cards with technical details, maintaining strong internal cybersecurity, vetting key personnel, and providing sufficient resourcing for safety and security research.

This is not the first time Hassabis has expressed worries about AGI. 

DeepMind was involved in an earlier US government initiative evaluating AI safety, alongside Microsoft and xAI (now SpaceXAI) working with the Center for AI Standards and Innovation (CAISI), a division of the US Department of Commerce. It allowed CAISI to conduct pre-deployment evaluations and targeted research to “better assess frontier AI capabilities and advance the state of AI security.”  

The rest of the world may have concerns

Analysts and consultants were mixed about the move, with most expressing concerns about whether an industry-focused group would prioritize the public’s best interests.

“Self-regulation is not viable because it implies everyone is able to regulate themselves and will do so in line with the best interests of the public. Most tech vendors don’t have the capacity to self-regulate. They would just prefer a set of rules within which they can operate,” said Gartner VP analyst Nader Henein. “For-profit organizations are required to do what is best for their shareholders, and external regulation ensures that those organizations are never in a conflict of interest where they have to choose between what is good for their shareholders and what is good for the public.”

And, said Sanchit Vir Gogia, chief analyst at Greyhound Research, given the international nature of AI models, an effort coordinated by the US government might alienate other countries. 

“National security is the proposal’s accelerator in Washington and its poison pill abroad: the framing that opens the only gate available at home invites foreign capitals to read the institution as an instrument of American strategy,” he pointed out.

“The map is already plural,” he said. “Brussels switches on enforcement powers over general-purpose models [starting in August 2026], London runs the AI Security Institute, and Beijing licenses on its own terms. California and New York have legislated for frontier models at home. The durable route is shared technical evidence with sovereign enforcement, sealed through mutual recognition rather than deference, with India and the other major non-Western markets holding authorship rather than seats.”

Gogia added that the rules enacted by even such a group may not address all of the key concerns of enterprise IT. A US government effort along the lines that Hassabis is proposing would result in testing that “sits close to intelligence and industrial policy, and those functions will not stay neatly separated. A model can pass every catastrophic-risk test and still fail the enterprise on privacy, reliability, and liability,” he noted.

Walmart’s former director of cybersecurity Steven Eric Fisher, who is now an independent cybersecurity consultant, said he found the proposal “well-intentioned, but it addresses a highly polarized topic at a time when commercial interests carry unprecedented political influence, which is not always applied benevolently.”

He added, “an exclusive US standard that is not globally respected or enforceable would likely fail to achieve its core purpose and would place US companies at a competitive disadvantage.”

Aman Mahapatra, chief strategy officer for Tribeca Softtech, a New York City-based technology consulting firm, said that a deep dive into how FINRA operates today is illustrative of what IT leaders can expect from this effort, assuming the industry adopts that model.

“When the CEOs of the five companies that would be regulated are also the primary drafters of the standards, the standards will reflect those companies’ interests. FINRA has an independent board, but the operational reality is that member firm perspectives dominate the working groups that write the actual rules,” he said. “There is no reason to expect an AI equivalent to work differently, and every reason to expect it to work worse, because AI standardization is happening faster than any industry has ever attempted to standardize itself, and speed is the enemy of independent oversight.”

Carmi Levy, an independent technology analyst, was even more emphatically opposed to the Hassabis proposal.

“Asking Big Tech companies to self-police is analogous to allowing foxes to guard the henhouse. It hasn’t worked to date, and it won’t work going forward. Expecting these organizations to somehow change their ways at this point in time represents the height of naïve thinking,” Levy said. “The framework proposed by Demis Hassabis is a self-serving roadmap for an industry bent on racing to the AI horizon regardless of the harms caused along the way. It is impossible to quantify the dangers to broader society should frameworks allowing self-regulation become the norm.”

Some love the proposal

An almost completely opposite stance came from Yuri Goryunov, CIO of consulting firm Acceligence, who applauded the proposed move.

“This is one of the rare setups where industry self-regulation has a real shot, and enterprise IT should be enthusiastically rooting for it,” he said. “It fails when harms are externalized, such as in social media content moderation. Or when the overseer outsources judgment to the overseen, such as the FAA’s delegation to Boeing before the 737 MAX. It works when everyone in the industry shares the catastrophic downside.”

He suggested, however, that the best precedent here isn’t FINRA, it’s INPO, the Institute of Nuclear Power Operations, which the nuclear industry created within months of the 1979 Three Mile Island partial reactor meltdown “on the logic that an accident anywhere is an accident everywhere. INPO peer-reviews every US plant, its evaluations move insurance premiums, and it sits on top of the NRC’s statutory floor. That is a public-private stack very close to what Hassabis is describing. Frontier AI has the same structure: one lab’s catastrophic failure brings regulation down on all of them.”

For enterprise CIOs and other IT executives, Goryunov said, that model has the potential for being a big win.

“Today, every enterprise duplicates the same AI diligence of red-teaming, eval suites, governance committees and each does so with less information than any certifying body would have,” Goryunov said. “A credible standards regime does for AI what UL did for electrical equipment and SOC2 did for cloud: it converts an unknowable risk into a procurable product and gives boards a defensible standard of care. That’s not red tape. That’s peace of mind with an audit trail.”

However, Mahapatra said, “the countervailing view is that the alternative to industry-led standards is probably not thoughtful legislation. It is probably no standards, or state-by-state fragmentation, or the current pattern of ex-post enforcement actions where regulators surface concerns years after harm has already occurred.”

Thus, he noted, “Hassabis is making the reasonable argument that imperfect fast standards are better than perfect slow ones, and there is genuine merit to that view for topics like agent identity, evaluation methodology, and interoperability, which are exactly the areas OpenClaw is also targeting.”

This article first appeared on CIO.

Google DeepMind CEO Demis Hassabis on Tuesday reiterated his push for an AI industry self-regulation effort, led by the US government, that is particularly focused on artificial general intelligence (AGI) and national security. 

But it is precisely that focus on national security that may make the results of such an effort, assuming it happens, less than palatable outside of the US.

“The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous,” Hassabis wrote. “The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organization, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives.”

He noted, however, that the funding would need to be substantial, and would most likely come from industry, to allow the new body to attract world-class technical talent and obtain the necessary compute resources for large-scale testing.

Hassabis said he would propose that the organization “be responsible for developing assessment protocols and working with appropriate federal agencies and the US National Labs to conduct testing in areas relevant to national security,” and that AI vendor participants would be encouraged to adopt best practices, such as publishing model cards with technical details, maintaining strong internal cybersecurity, vetting key personnel, and providing sufficient resourcing for safety and security research.

This is not the first time Hassabis has expressed worries about AGI. He has already worked on a US government initiative evaluating AI safety, which involved DeepMind, Microsoft and xAI (now SpaceXAI) working with the Center for AI Standards and Innovation (CAISI), a division of the US Department of Commerce. It allowed CAISI to conduct pre-deployment evaluations and targeted research to “better assess frontier AI capabilities and advance the state of AI security.”  

The rest of the world may have concerns

Analysts and consultants were mixed about the move, with most expressing concerns about whether an industry-focused group would prioritize the public’s best interests.

“Self-regulation is not viable because it implies everyone is able to regulate themselves and will do so in line with the best interests of the public. Most tech vendors don’t have the capacity to self-regulate. They would just prefer a set of rules within which they can operate,” said Gartner VP analyst Nader Henein. “For-profit organizations are required to do what is best for their shareholders, and external regulation ensures that those organizations are never in a conflict of interest where they have to choose between what is good for their shareholders and what is good for the public.”

And, said Sanchit Vir Gogia, chief analyst at Greyhound Research, given the international nature of AI models, an effort coordinated by the US government might alienate other countries. 

“National security is the proposal’s accelerator in Washington and its poison pill abroad: the framing that opens the only gate available at home invites foreign capitals to read the institution as an instrument of American strategy,” he pointed out.

“The map is already plural,” he said. “Brussels switches on enforcement powers over general-purpose models [starting in August 2026], London runs the AI Security Institute, and Beijing licenses on its own terms. California and New York have legislated for frontier models at home. The durable route is shared technical evidence with sovereign enforcement, sealed through mutual recognition rather than deference, with India and the other major non-Western markets holding authorship rather than seats.”

Gogia added that the rules enacted by even such a group may not address all of the key concerns of enterprise IT. A US government effort along the lines that Hassabis is proposing would result in testing that “sits close to intelligence and industrial policy, and those functions will not stay neatly separated. A model can pass every catastrophic-risk test and still fail the enterprise on privacy, reliability, and liability,” he noted.

Walmart’s former director of cybersecurity Steven Eric Fisher, who is now an independent cybersecurity consultant, said he found the proposal “well-intentioned, but it addresses a highly polarized topic at a time when commercial interests carry unprecedented political influence, which is not always applied benevolently.”

He added, “an exclusive US standard that is not globally respected or enforceable would likely fail to achieve its core purpose and would place US companies at a competitive disadvantage.”

Aman Mahapatra, chief strategy officer for Tribeca Softtech, a New York City-based technology consulting firm, said that a deep dive into how FINRA operates today is illustrative of what IT leaders can expect from this effort, assuming the industry adopts that model.

“When the CEOs of the five companies that would be regulated are also the primary drafters of the standards, the standards will reflect those companies’ interests. FINRA has an independent board, but the operational reality is that member firm perspectives dominate the working groups that write the actual rules,” he said. “There is no reason to expect an AI equivalent to work differently, and every reason to expect it to work worse, because AI standardization is happening faster than any industry has ever attempted to standardize itself, and speed is the enemy of independent oversight.”

Carmi Levy, an independent technology analyst, was even more emphatically opposed to the Hassabis proposal.

“Asking Big Tech companies to self-police is analogous to allowing foxes to guard the henhouse. It hasn’t worked to date, and it won’t work going forward. Expecting these organizations to somehow change their ways at this point in time represents the height of naïve thinking,” Levy said. “The framework proposed by Demis Hassabis is a self-serving roadmap for an industry bent on racing to the AI horizon regardless of the harms caused along the way. It is impossible to quantify the dangers to broader society should frameworks allowing self-regulation become the norm.”

Some love the proposal

An almost completely opposite stance came from Yuri Goryunov, CIO of consulting firm Acceligence, who applauded the proposed move.

“This is one of the rare setups where industry self-regulation has a real shot, and enterprise IT should be enthusiastically rooting for it,” he said. “It fails when harms are externalized, such as in social media content moderation. Or when the overseer outsources judgment to the overseen, such as the FAA’s delegation to Boeing before the 737 MAX. It works when everyone in the industry shares the catastrophic downside.”

He suggested, however, that the best precedent here isn’t FINRA, it’s INPO, the Institute of Nuclear Power Operations, which the nuclear industry created within months of the 1979 Three Mile Island partial reactor meltdown “on the logic that an accident anywhere is an accident everywhere. INPO peer-reviews every US plant, its evaluations move insurance premiums, and it sits on top of the NRC’s statutory floor. That is a public-private stack very close to what Hassabis is describing. Frontier AI has the same structure: one lab’s catastrophic failure brings regulation down on all of them.”

For enterprise CIOs and other IT executives, Goryunov said, that model has the potential for being a big win.

“Today, every enterprise duplicates the same AI diligence of red-teaming, eval suites, governance committees and each does so with less information than any certifying body would have,” Goryunov said. “A credible standards regime does for AI what UL did for electrical equipment and SOC2 did for cloud: it converts an unknowable risk into a procurable product and gives boards a defensible standard of care. That’s not red tape. That’s peace of mind with an audit trail.”

However, Mahapatra said, “the countervailing view is that the alternative to industry-led standards is probably not thoughtful legislation. It is probably no standards, or state-by-state fragmentation, or the current pattern of ex-post enforcement actions where regulators surface concerns years after harm has already occurred.”

Thus, he noted, “Hassabis is making the reasonable argument that imperfect fast standards are better than perfect slow ones, and there is genuine merit to that view for topics like agent identity, evaluation methodology, and interoperability, which are exactly the areas OpenClaw is also targeting.”

This article originally appeared on CIO.com.

When Apple sued OpenAI last week, the argument it made was that former employees had stolen Apple data and then used it to benefit OpenAI. 

The technical details — an employee used “a rare, previously unknown authentication bug to access Apple’s shared network folders” — are interesting. But the larger story is Apple’s ridiculous attempt to stop its people from using anything they learned at Apple in other jobs.

“Hiring managers don’t mind some files being brought into the org during onboarding, but suddenly take umbrage when that same employee exits with some files later on,” said Mike Wilkes, enterprise CISO at Aikido Security. “Legal should be equally concerned about both events.”

The lawsuit focused on Chang Liu, an employee who had been recruited to work at OpenAI after working at Apple for eight years as a Senior System Electrical Engineer. The full text of the filing depicts a comedy of errors by Apple, offering the perfect “do not do” list of handling employee resignations — especially when they’re going to a direct competitor. 

“When Apple contacted Mr. Liu to sign Apple’s confidentiality reminder, schedule an exit interview, and confirm that he had returned his devices and complied with other exit procedures, Mr. Liu did not respond.” And “after leaving Apple, Mr. Liu failed to return an Apple-issued work laptop that he had previously authenticated to Apple’s network.”

First, typical procedure for handling departures is to tie the return of all equipment and the signing of documents to any final payments. With Apple, that is likely to be a large amount of money. The lawsuit does not say whether Apple exerted any financial pressure on their employee for compliance. 

But in terms of equipment with high-level access, why weren’t all privileges revoked, both for the employee and any and all company-issued devices? Did they not maintain a remote-wipe capability for these devices? Although remote-wipe is usually used when devices are missing or stolen, it should work as well when a departing employee refuses to return company equipment. 

According to Apple, Liu apparently had help at Apple from Tang Yew Tan, who was supposedly also interviewing with OpenAI. “While employed by OpenAI, [Liu] accessed and used his former colleague’s Apple-issued work computer that was authenticated to Apple’s network, without Apple’s authorization.”

Apple tried to make much of this Liu’s fault. Legally, yes, there might be liability there; still, Apple made itself look as if it couldn’t protect its own data. “Upon discovering that he had this unauthorized access to Apple’s systems, [the former employee] did not report it, return his stolen Apple-issued work laptop or delete the program that allowed the access.” 

Really, Apple? Your data-protection plan relies on ex-employees to “delete the program that allowed the access”? I’m not so sure you didn’t bring some of this data-leakage on yourselves. 

This gets worse: “Over several weeks, while developing hardware for OpenAI, Mr. Liu surreptitiously accessed and downloaded dozens of Apple’s confidential hardware-related files, including voluminous, detailed information about unreleased products, engineering presentations, technical specifications, and proprietary project data.”

Setting aside the issue of privileges, access, and unreturned equipment that apparently had its own privileges, that statement points to massive data exfiltration from Apple systems. Even if it is coming from a current employee, why didn’t that raise any red flags? 

Let’s get back to the broader implications. When professionals move from one company to another, they — of course — are bringing their experience and knowledge with them. Can Apple reasonably tell them that they can’t do so? Isn’t that experience and knowledge exactly why another company would want to hire them?

Now, to be sure, stealing diagrams and product spec sheets is a clear violation. Let’s say Apple spent a lot of money on some hardware research projects. A member of that technical team would learn an awful lot, all on Apple’s dime. 

But is it fair and reasonable for Apple to say that the former employee can’t leverage that knowledge at his or her next job? 

This brings us back to the point Wilkes made: If Apple is going to try to prevent any former employee from leveraging on-the-job experience, then it should instruct all new employees not to use anything they learned in a previous job. 

That would be ridiculous. Companies pay for experienced talent because of that experience. Why pay for expertise if you insist employees not leverage any of it?

Then there’s the amorphous nature of knowledge. So, it’s wrong to take detailed diagrams and spec details and hand them over to a new employer. But what if that worker heading out the door memorizes the documents (photographic memory) a day before resigning? Is a person prohibited from using something from memory?

There’s also the fruit-of-the-poisonous tree legal argument. Even if a former employee doesn’t directly use stolen data, what if their knowledge leads to other money-saving insights for the new employer? 

Given that Apple hires as many specialists as it loses to rivals, wouldn’t it make sense to leverage everything your workforce knows and then let new employers do the same? But before you do that, Apple, tighten your exiting employee tech controls. 

Then maybe you wont’t have to file lawsuits like this down the road.

The US government decision to force Anthropic to close down its latest and greatest AI models, Fable 5 and Mythos 5, was only the next step in a burgeoning battle between AI providers and ignorant politicians. 

Anthropic was on top of the world. Its Mythos 5 LLM had everyone excited. (If you believe the hype, it was kind of scary, too.) Even Anthropic CEO Dario Amodei admitted — or boasted? — that Mythos would bring an “enormous increase in the amount of vulnerabilities, in the amount of breaches” to us all. But with that fear came the promise of more AI power than ever. 

Then, the roof caved in.

On June 12, the US Commerce Department used its export-control powers to demand that Anthropic cut off access to its Fable 5 and Mythos 5 models for all foreign nationals, citing national security concerns and fears of jailbreaks. After figuring out it had no way to do that, Anthropic pulled both of its newest frontier AI models offline worldwide.

Just what an AI company needs! All other Claude models, like the Opus and Sonnet series, remain online. But, come on, AI sales are all about the newest and most powerful models.  

Adding insult to injury — and this is true at many high-tech companies — Anthropic has many employees who aren’t US citizens. This means Anthropic’s own programmers can’t work on their latest models.

Of course, this isn’t the first time US President Donald J. Trump and company have tried to put a spoke in Anthropic’s wheels. Back in February, Anthropic refused to give Defense Secretary Pete Hegseth the power to use its models to spy on American citizens and to power autonomous weapons.

This go-around, it wasn’t because Anthropic refused to kowtow to Trump’s officials. It was, they say, out of fear that these new models could be used to attack American interests. 

Mind you, no one in Trump’s regime has the tech chops to know just how dangerous, or not, any AI model is. As I recently noted, Trump’s AI executive order has no teeth. Nor, more to the point, is there anyone in the administration with a clue about AI.

Specifically, at the Department of Commerce, neither Commerce Secretary Howard Lutnick nor William Kimmitt, undersecretary of commerce for international trade, knows a thing about AI. Just what we need, more political hacks deciding tech policy. 

So, how did they discover that Fable and Mythos were theoretically a danger to the US? Good question. According to The Wall Street Journal, it was Amazon CEO Andy Jassy who told the Trump administration that Fable was untrustworthy. Guess what? AWS offers its own full cloud AI stack, starting with Amazon Bedrock for foundation models, Amazon SageMaker for training and deployment, and a growing set of agentic AI tools and services. 

In other words, Amazon is not a neutral party; it’s a competitor. Funny, that.

Sure, Amazon also has partnerships with Anthropic. But, in case you haven’t noticed, all the big AI companies are in bed with each other. That doesn’t stop them from fighting. What’s heating this up is that the AI companies are no longer offering flat-rate subscriptions and are replacing them with far more expensive, token-based pricing schemes. 

Armed with this information, Commerce gave Anthropic 90 minutes to fix its “problem.” Right. AI development is fast, but it’s not that fast. In addition, according to Anthropic, officials haven’t spelled out exactly what’s wrong. They only know that Commerce claims there was a “narrow, non‑universal jailbreak” in Fable.   

That’s it. That’s all. 

Anthropic has also observed, with reason, that similar jailbreaks are possible on other leading models, like OpenAI’s GPT‑5.5. Those others, however, haven’t been hammered with comparable export controls.

The AI and security experts who do have an AI clue believe Commerce is behaving stupidly. (You won’t get any argument there from me.) For example, in an open letter, “On Transparent AI Cyber Protections,” they said Commerce’s directive “has taken the best models away from defenders, created market uncertainty, and risked America’s AI leadership without any real risk to justify it,” warning that pulling capabilities “away from defenders without a good reason when our adversaries are rapidly advancing is dangerous.”

Exactly so. 

Besides, as Alex Zenla, co-founder and CTO of security company Edera, observed, Fable’s capability to identify insecure code sections is the baseline for any model you’d trust to write secure code. The same capability exists in GPT-5.5, Opus, Sonnet, and Kimi 2.7 — it’s not unique to Fable. Pulling Fable from defenders doesn’t remove the capability from the threat landscape. It just removes it from the people trying to build safer systems.”

This is not about AI safety or security. 

What this is really about is opening a new front in Trump’s war against the liberal-leaning Anthropic. Mind you, Anthropic isn’t really liberal. This has more to do with Anthropic not following in other tech firms’ groveling to Trump. 

However, Trump doesn’t seem to realize that by essentially shutting down Anthropic’s biggest move to date, he’s also telling the world that they can’t rely on American AI companies down the road. Sure, in the short run, this hurts Anthropic. In the long run, it’s going to be another reason for Europe and other countries — taking digital sovereignty seriously — to avoid doing business with any American tech company. 

In the meantime, Anthropic and Trump administration officials are in tense talks over whether, and under what safeguards, the models could return to the marketplace. Commerce indicates it might allow a narrower relaunch if jailbreak issues are resolved and additional controls are in place — whatever those might be. 

Since it’s really all about massaging Trump’s ego, I’m not feeling terribly optimistic. Just ask Israeli Prime Minister Benjamin Netanyahu how well letting Trump set the terms of engagement goes. It’s not pretty. 

For generations, technology export controls referred to the transfer of code to other countries. But that no longer works, as the latest Anthropic fight with the US Commerce Department makes clear. 

On Friday, Anthropic announced that it had received instructions from Commerce “to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Anthropic models will not be affected.” 

Technically, the Commerce letter doesn’t explicitly say that, but lawyers and consultants argue that, when combined with an earlier executive order declaring Anthropic a supply chain risk, that very well might be what it means.

What the Commerce letter says is that Anthropic needs a license to export Fable 5 and Mythos 5 (a “deemed export“), listing four circumstances in which that license would be required: “The sending or taking of the model out of the United States in any manner; The sending or taking of the model from one foreign country to another in any manner; Retransferring the model within a single foreign country; or the release of the model to a ‘foreign person’ in the United States or a foreign country.”

Restricts capabilities not code

Although moving a model has historically meant transferring the code, most experts argue that the definition has changed for all SaaS deployments, and could now be interpreted as referring to any access to the models.

“This is not just about data sovereignty anymore. It is about capability sovereignty, where governments want to control who has access to frontier AI capabilities, irrespective of who built it, where it is hosted, or who worked on it,” said Valence Howden, advisory fellow at Info-Tech Research Group.

“The reference to deemed exports is important, because traditionally that would apply to code, technology, or technical knowledge being transferred,” he said. “In this case, the thing crossing borders is not necessarily the model itself, but it is access to the capability. That is a significant shift, and signals the real intent behind the AI arms race. The focus is moving from controlling the technology to controlling access to the outcomes the technology can produce.”

Mark Rasch, a former federal prosecutor who specializes in legal technology issues, agreed. “I don’t need to have the code physically resident in order to take advantage of the capabilities of that code. Today, the location of the code is irrelevant.”

Practical challenges

There are two practical issues involved. The first is that a large part of Anthropic’s workforce is not US citizens, and some of them have direct access to the code for these models. 

But the potentially more daunting issue is that today it is difficult, if not impossible, to identify the citizenship of any AI user, which might force companies to assume that everyone might be unauthorized. 

In fact, said Yuri Goryunov, CIO of consulting firm Acceligence, “there is no way to check citizenship through an API call. Besides, three-quarters of Americans don’t have passports.”

Consultant Brian Levine, executive director of FormerGov, added that the issue will make life difficult for CIOs even if the Commerce position is viewed as dubious.

“Regardless of the strength of Commerce’s position, once it issues an ‘Is Informed’ letter, every unlicensed interaction with a foreign person becomes a potential violation, and the safest move is often to halt access until a licensing path exists,” he said.

This means that enterprise CIOs need to approach AI contracts with the knowledge that any government can now declare the product legally unavailable, with no notice. 

Sovereignty has climbed the stack

Howden said that this shift will force CIOs to strongly consider non-US AI models such as France’s Mistral or even China’s DeepSeek, “to reduce the concentration risk attached.” 

“There are hundreds out there that are very good. It is very easy to sit in the bubble of the four or five we know,” Howden said. “Enterprise CIOs think it’s a much more limited market than it really is.”

Sanchit Vir Gogia, chief analyst at Greyhound Research, said that enterprise executives now need to take the significant import rule changes into account when selecting AI models. 

“The harder truth is that sovereignty has climbed the stack,” he said. “The wall no longer stands around the database, it now stands around the intelligence layer itself. Under the export-control frame, it covers the release of controlled technology or code to a foreign person, including one standing inside the United States. The border follows the person, not the parcel. Code is part of the doctrine, but it is not the whole of it.”

He added, “the difficulty is that the cited rules speak of technology and code, while the letter reaches for the model itself. A hosted model hands the user no weights and no code. It hands them inference, and inference is a capability, not a file.”

Ultimately, Gogia said, Anthropic’s decision to cut off model access to everyone immediately “was a rational answer to an impossible instruction. A frontier model can now vanish for reasons unconnected to uptime, price or performance. The same models that help secure systems can be withdrawn at the moment defenders most need them.”

This article originally appeared on CIO.com.

Anthropic’s apparent inability to identify which of its users are foreign nationals has led to some collateral damage from a US export ban on its most powerful AI models — but there is a way around it, at least for some.

On Friday, the US government ordered Anthropic to suspend access to Fable and Mythos, the new AI models it had introduced just a few days earlier, to all foreign nationals, citing national security reasons.

[ See also: Anthropic Fable dispute suggests ‘export’ no longer means what it used to ]

While the drafters of the US order may have had sovereignty in mind, they ended up making it an identity management problem.

“The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance,” Anthropic said in a blog post commenting on the order, implying that it was unable to distinguish between foreign nationals and US citizens in its user base.

That’s likely the case today, but for its consumer customers, an update to its privacy policy, introduced last week and taking effect on July 8, gives it a new option: asking them for government ID.

The section of the policy on collection of personal data contains a new provision under the heading “Personal data you provide to us directly,” saying:

• Verification Data: In certain circumstances, we may ask you to verify your age or identity. If you choose to do so, data we will collect includes, depending on the method: an image of your government-issued identity document and the information appearing on it (such as your ID number and date of birth); your image in photo or video form, facial geometry templates (which may be considered ‘biometric data’ in some jurisdictions); and the result of the verification (for example, whether your age meets the applicable threshold).

If the government ban on foreign access to Fable and Mythos continues, that would give Anthropic the option of opening access to users willing to submit a scan of their identity document, provided that it contained proof of their US citizenship. That would be the case for US passports — and also for citizens’ driving licenses issued by some US states along the country’s Northern border, which issue so-called enhanced driving licenses indicating the holders’ nationality.

Enterprise users most likely to benefit from the power of the new AI models, though, will have to hope Anthropic finds some other way out of the current impasse.

The article originally appeared on CIO.

MUNICH — Amid trans-Atlantic political and trade tensions, digital sovereignty — once a relatively niche concern — has jumped to the top of the agenda for European organizations wary of their reliance on US technology suppliers.

For many, including European Union policy makers, increased use of open source software is a key part of the answer, offering an alternative to proprietary platforms from a handful of large US vendors.

That’s the view of Frank Karlitschek, CEO of Nextcloud, the German software vendor that bills itself as an open-source alternative to software suites from the likes of Microsoft and Google. 

Karlitschek founded the company in 2016, forking OwnCloud’s open-source file-sharing software. Since then, Nextcloud has expanded its products to include a range of productivity and collaboration tools that organizations can install and run on their own servers or access via cloud providers. 

More recently, Nextcloud helped develop the Euro-Office application suite, which launched last week as an open source alternative to Microsoft Office and others, and continues to build out its Nextcloud Hub with AI assistant and agent features. The company now says revenues are growing at between 50% to 100% year over year.

Computerworld spoke to Karlitschek at Nextcloud Summit about momentum around digital sovereignty, the European Commission’s Tech Sovereignty Package proposals, and how Nextcloud hopes to evolve in the coming years.

The following interview was edited for length and clarity.

When Nextcloud launched, there was a big push in Europe away from on-premise software towards US cloud providers. How have attitudes towards open source and awareness of alternatives providers changed since then? “I’ve been doing open source since the ‘90s; at the time it was mostly for a nerdy audience — a very small group of people who really care about software and being in control. The sovereignty part was always there. It’s the core idea behind open source that you can understand what the software is doing, you can deploy it wherever you want, you can study it and change it, and so on. 

“At the time, it was very niche, and since then it’s really growing and growing. There are certain points in time that really accelerated the growth; something like the Snowden revelations, for example, or the whole discussion about GDPR and certain legislation. And then, of course, the current geopolitical situation.  

“I personally find it interesting that it grew from something that is just interesting for software developers, and now it’s on the geopolitical stage. I have meetings with big politicians who really care about it now, and I personally find it interesting that it’s increasingly understood by — I wouldn’t say the mainstream, but more and more people.

“At the beginning of Nextcloud, we mostly talked with IT managers looking for a solution; they care about how it works, the price and other things. But now we are also talking with the C-level people. It’s part of an overall strategy of a company, to say, ‘Hey, we need to look into the dependencies, we want to have a solution that fits into the strategy of the company.’

“In the past, it was like a commodity – it’s just some software, who cares? Now, it’s really part of the company strategy. That’s really interesting.”

There’s been a lot of interest around digital sovereignty over the past couple of years. To what degree is this translating into action, with organizations migrating away from US cloud providers? “The interest is gigantic. Everybody’s talking about it, we have so many contacts and people coming to us. Not everybody is doing it — a lot of people are just exploring and seeing what the options are. 

“Obviously, we hope that this will translate into actions in a few months. At the moment, it’s a lot of talking and exploring the options. As a company, we are also growing a lot in customer base.  But the interest in this space is even bigger; we see it as the beginning of a funnel.

‘In defense we see a lot of interest, then also everything around education is very important for us, then other regulated markets like the healthcare, for example. Finance is an interesting one.”

A lot of the conversations around digital sovereignty are tied to the current geopolitical situation and even the US administration. Do you see demand for sovereign technology as a structural change or are some organizations holding back to see how the situation improves in the future? “I see it as a long-term trend. If you look at the IT budgets and projects in the ‘90s, it was some something unimportant. It was, of course, important that the printer works and the fax machine works, but it was not definitely not strategic for the company. 

“And then in 2000, the whole cloud trend came up, and there was the big hope that this will save money. It was always the narrative with cloud computing that you can just outsource it and save money and it’s great. 

“Nowadays, people realize that it’s not something that you can just ignore. I wouldn’t say that everything comes back on premise, but people care about it now. They understand it’s not just a commodity, like water, or electricity that comes out of the wall and you don’t care what’s behind it. People realize that it’s something that has an impact on the future of an organization, from a vendor lock-in perspective, from a cost perspective, from an industry espionage perspective, and competitiveness. With open source, you’re more flexible. So, I think the trend that this is all more strategic and important for the future, this will go on.”

The European Commission recently published its Tech Sovereignty Package, including its open source strategy. Are these proposals sufficient to address the concern around digital sovereignty and support the open source ecosystem in Europe?

“It’s great, I really like it. I was actually surprised they listened so well. But now the real challenge is to actually do it; this still needs to happen. The description of the problem and a possible solution, this is all very good. I’m surprised, I’m happy about it, but to put this into actually binding law, this still needs happen.”

Would you like to see any changes to the current proposals before they’re gets passed into legislation? “At the moment, they have these four different risk levels, and the most critical one — No. 4 — is one where they accept only open source and European solutions. This is the highest risk level, but this is only for 1% of the market. I hope that it’s better understood that more than 1% should care about this more.

“If you have something which is completely not critical, maybe doesn’t possess any personal data at all — sure, it’s totally fine [to use non-EU suppliers]. But if you have GDPR requirements, espionage protection, no vendor lock-in, and so on, then there should be more of that [the highest requirement level].”

US firms have attempted to address European customers’ concerns in different ways, with sovereign marketed cloud services and joint ventures with European providers. Microsoft 365 Local is designed to run on premise. Where do you draw the line between what’s actually a sovereign solution and what some call ‘sovereignty washing? “Sovereignty has different dimensions, of course. But if you look at the problem of the CLOUD Act alone, which gives foreign agencies full access to the data here, then the whole idea that it’s enough to have European data centers — that’s not enough. It’s clearly written in the CLOUD Act, that even with [European] data centers, or subsidiaries, it still applies.  

“Microsoft tries to find a solution there with its Delos idea; a company that is owned by SAP — a German company — and Microsoft delivers only the software. But even then, you have this dependency, because software needs updates and software security updates. And if they’re not available, or if someone puts a backdoor into the software, which is possible, then you still have a problem. 

“So, they’re trying really, really hard to find a way around the problem, but it’s not easy for them.”

To look ahead a bit in terms of the product strategy, there were announcements for Nextcloud Hub this week around AI agents, and the program to work with independent software vendors. What do these say about Nextcloud’s future? “The overall product strategy will not change so much; it’s about having state-of-the-art collaboration software — but with a lot more control, security and safety — that’s open source and independent where you host it. So this will always stay, but of course, there’s some additional factors that come into play now, like the AI impact that we see and want to leverage with our agent strategy. 

“We’ve had this for one and a half years already, but we are expanding that. In the future, you might still use an interface in a classic way that you open documents and type in text and so on. But there are also a lot of operations that can be automated in the future with AI. And this is something we really invest a lot into. 

“Another aspect of AI is how easy it is to build custom software around it. The coding models are getting better all the time, which means there will be more and more custom business software. This is what we want to capture with our ISV program. Software development will become easier, but you don’t want to deploy just random software in your company, you want to have something that is tested, certified and secured, and that somebody’s accountable for it. This can be something we can provide at Nextcloud.”

Editor’s note: NextCloud paid for Matthew Finnegan’s travel and hotel costs for NextCloud Summit 2026, but had no editorial role in the creation of this story.

A German court has sparked a legal controversy by ruling that Google is responsible for defamatory comments generated by its own AI system. The search giant had argued that it couldn’t be blamed for the false results, but a Munich court has deemed that not to be the case and has ruled in favor of the two unnamed plaintiffs, both publishing companies, who the Google AI Overview inaccurately said engaged in shady business practices.

Google is required to remove the comments and ensure that they are not repeated. The case is certainly going to raise some questions globally. Will this mean that other courts are going to rule against AI vendors?

Bernhard Buchner, a partner at Lausen Rechtsanwälte, the legal firm that acted for the plaintiffs, said, “I believe it shows that online providers such as Google cannot hide behind the fact that a statement was generated by AI, but rather that they can be held liable for its output. It is an important step towards ensuring that providers of AI systems have to take responsibility for their outputs.”

So, does this mean that the decision could be replicated in the US or elsewhere? Alex Shahrestani, managing partner at Austin-based Promise Legal, said, “the short answer is ‘yes’:  the Munich ruling travels, because US courts are already making the same move.”

He explained that Section 230 of the US Communications Decency Act, which has been applied to protect online service providers like social media companies from lawsuits based on their decisions to transmit or take down user-generated content, was built for computer bulletin boards, “not for a model that writes its own answers. Once the AI is the author, the company is the publisher.”

This means, he said, “businesses now need named humans at accountability nodes, verification gates before AI output ships, and audit trails that survive discovery, because ‘the model recommended it’ is a legally empty sentence.”

Does the decision mean that other AI providers could find themselves in the same position? Buchner believes it’s possible, although, he said, the situation in this case is unusual; it does not involve a classic chatbot scenario, but one where the AI-generated statements are published as an ‘AI overview’ of a search query.

“Google’s liability here is based not so much on the fact that it operates the underlying AI, but rather on the publication of its output. However, it seems entirely conceivable to me that this could also be applied generally to inaccurate or defamatory AI,” he pointed out.

Nonetheless, said Carolyn Shelby, head of SEO at Yoast, the German ruling should ensure that companies will be more circumspect in how they handle AI in the future, to protect themselves from any legal action. The first thing they should do  is to separate low-risk use of AI from major decision-making.

“Using AI to summarize meeting notes, brainstorm campaign ideas, or create a first draft of something is very different from using it to make decisions about customers, employees, finance, compliance, health, legal claims, competitive positioning, or public communications,” she noted.

She pointed out that the effects of AI use could be devastating for companies. “The consequences could include customer complaints, reputational damage, regulatory attention, legal claims, correction costs, loss of trust, and internal disruption,” she said. “Even when a mistake does not become a lawsuit, the operational cost of correcting bad information can be significant.”

However, she noted, things may not change immediately.  “Many companies will wait until there is a high-profile court case, regulatory action, or major corporate embarrassment before they take this seriously. That is usually how governance catches up with technology. But the better-run organizations will start treating AI governance as part of normal business risk management now.”

And, said Shahrestani, after the Google decision, everything has changed. It will become more important to ensure that employees remain part of the process.

Years ago, right-wingers coined the phrase “Trump Derangement Syndrome” (TDS) to describe people who hate US President Donald J. Trump. (I think it better describes the president’s outlandish, truth-challenged statements and the followers who think he can do no wrong.) What’s really deranged is his recent AI executive order.

First, a little history. As you may recall, Trump often (and loudly) trashed his predecessor’s Executive Order 14110, which had demanded “safe, secure, and trustworthy” AI. That Biden Administration order was replaced last year by Trump’s own “Removing Barriers to American Leadership in Artificial Intelligence” directive; it basically let US AI companies do whatever they wanted in the name of innovation.

Then, a little thing called Anthropic Mythos came along — and scared the pants off even AI’s biggest fans. Seemingly in response, someone in the federal government decided that letting AI companies do whatever they want might not be the brightest policy. 

Or, did they?

True, the new order creates a process under which AI companies can give US  government access to “covered frontier models” for up to 30 days before public release so experts can probe for vulnerabilities and test how the systems could be abused. It also directs agencies to set evaluation standards, establish an “AI cybersecurity clearinghouse,” and harden federal networks against rapidly advancing AI‑enabled attacks. 

Some people, like Graham Brookie, vice president for technology programs and strategy at the Atlantic Council, think the order is great. “The administration’s executive order on Advanced AI Innovation and Security is a serious policy with support from necessary stakeholders across party lines and industry to ensure the government is evaluating the cybersecurity risks posed by frontier AI models. It’s a policy that can be built on.”

Really? I’m not sure Brookie read the same document I did — if, indeed, he read it at all.

I quote:

“Nothing in this section shall be construed to authorize the creation of a mandatory governmental licensing, preclearance, or permitting requirement for the development, publication, release, or distribution of new AI models, including frontier models.

“In addition, ‘This order is not intended to, and does not, create any right or benefit, substantive or procedural, enforceable at law or in equity by any party against the United States, its departments, agencies, or entities, its officers, employees, or agents, or any other person.’”

In other words, AI companies won’t be required to do much of anything. And if they do  submit a project for review, get the government’s blessing for it, and something goes badly wrong, it’s not the government’s fault. 

So, exactly why would AI companies even mess with this performative AI security theater?

Beyond those concerns, who exactly will be judging AI projects in 30 days? In theory, it would be a cybersecurity clearinghouse made up of people from the National Security Agency, the US Treasury Department, and the Cybersecurity and Infrastructure Security Agency (CISA). Most likely, CISA would do the bulk of the heavy-lifting — it’s their job, after all. But there’s this wee problem; Trump’s so-called Department of Government Efficiency (DOGE) last year gutted CISA. There’s virtually no one left to do the work, and certainly not in 30 days.

There’s also the question of funding for the new initiative.  According to the order, “The Director of OMB, in coordination with the National Cyber Director and the Director of CISA, shall determine whether any Federal grant programs have available and relevant funding that can be directed toward applicants developing advanced AI vulnerability detection.”

Spoiler: There’s no money set aside for this purpose.

Leaving aside whether the Executive Order has any teeth at all — the Brennan Center for Justice argued that under the Constitution, it doesn’t; the closer you look at the document, the less substance you’ll find.

Besides, in an industry where success is all about releasing the latest Large Language Model (LLM) as fast as possible to garner attention and investor dollars, who exactly would want to put their AI models on ice for even 30 days? (Short answer: No one.) These companies are always going to be focused first on getting the word out about their latest model as fast as humanly — Uh, AI-ly — possible. 

Still, some people seem to think this executive order really will make a difference. For example, Paul Benda, the American Bankers Association executive vice president for risk, fraud, and cybersecurity, sees it “as a constructive step toward strengthening the nation’s approach to managing the cybersecurity risks and opportunities associated with advanced artificial intelligence [because it ] can help better protect critical infrastructure, including the financial sector.”

Oh, please. I’m so tired of people who skim the titles of Trump’s executive orders and then assume there’s anything real about them. 

This AI order is meaningless garbage, and anyone telling you otherwise is either lying or wants to be on the Trump regime’s good (?) side. Or, both — it could always be both. 

The European Commission published its tech sovereignty package last week, including the clearest signal yet of its intention to strengthen European cloud sovereignty and reduce its dependence on US hyperscalers.

It’s a response to growing concerns among European organizations and regulators about the reliance on US tech firms and legislation such as the US CLOUD Act, which could give US officials access to data — even if it is stored in Europe.

But any shift toward local, sovereign cloud providers will necessarily be gradual, analysts, said as the Cloud and AI Development Act (CADA) proposals leave plenty of room for US providers to continue supplying cloud computing services to European public sector customers.

“The direction is right. The execution will be slow,” said Fernando Pereiro, senior director analyst at Gartner.

While the Commission has correctly identified areas where the EU is most dependent on foreign providers, delivering on its ambitions is another challenge, he said. Scaling alternatives to US suppliers “takes time, capital, and coordination at a level that is difficult to sustain in Europe.”

Dario Maisto, senior analyst at Forrester, played down the prospect of a major short-term shift towards European cloud providers as a result of the CADA proposals, even after recent interest in local European vendors for mission-critical workloads and highly sensitive data.

“I do not expect an immediate impact on the cloud infrastructure market,” Maisto said. “Full-blown migrations are costly and take several years. They are not going to happen in the near future.”

Instead, Pereiro expects the gradual emergence of “sovereign enclaves” or controlled environments for sensitive workloads, particularly in government and regulated sectors. “Outside of those areas, the market will remain global, but increasingly shaped by European rules,” he said.

Nevertheless, the three US hyperscalers that account for around 70% of the European cloud market – Amazon Web Services (AWS), Google, and Microsoft —  will likely see a more competitive environment.

“The real shift is symbolic and structural: hyperscalers move from being the default choice to one option among others, and their competitiveness will increasingly depend on how well they align with European control requirements, not just on technology or price,” said Pereiro.

What is CADA and what could it mean for Europe’s cloud market? 

CADA is part of a range of policy and legislative proposals — known as the Tech Sovereignty Package — published by the Commission, alongside Chips Act 2.0, the Open Source Strategy, and Strategic Roadmap for Digitalization and AI in Energy.

CADA includes measures to boost European tech sovereignty. Among other things, it aims to triple data center capacity in the next five to seven years by easing restrictions on new infrastructure projects across the EU, as well as efforts to support research and development of cloud and AI technologies.

It also includes a sovereignty framework that, if enacted, would require EU public bodies to assess sovereignty risks and procure cloud services that meet four assurance levels.

The various levels portray “a political vision with many open questions,” said Maisto. In more detail:

• Level 1 requirements are achievable by hyperscalers, Maisto said, with requirements focused mostly on data residency. 
• Level 2 is “more controversial,” he said, as it includes requirements around third-country access to data and disruption of services.
• Level 3 leaves room for US providers to win procurement contracts — particularly where they enter a joint venture with a European cloud provider such as S3NS, a Thales subsidiary that has partnered with Google.
• Level 4 applies to only a small proportion (1%) of the most sensitive workloads.

The first two levels could be open to US hyperscalers, said Maisto, with 70% of existing EU public sector workloads falling under Level 1 and 20% at Level 2, according to Commission’s own impact assessment. Just 9% of the workloads would require Level 3. 

The most stringent Level 4 would require cloud providers that “have full transparency and control over their software supply chain and no interference from a third country,” the Commission said.

For public sector organizations, the CADA rules could create more clarity around procurement, said Pereiro. “Today, the concept of ‘sovereign cloud’ is often vague and inconsistently applied in providers’ marketing and messaging,” he said. “This package standardizes what sovereignty must look like in practice, effectively ending the era of ‘sovereign washing.’”

The proposals give public sector organizations a “stronger set of requirements with which to assess risk, especially around jurisdiction and access to data,” he said.

“For enterprises, it’s less about regulation and more about leverage,” said Pereiro. “They gain clearer benchmarks and more viable alternatives, particularly through open source and emerging European providers.”

European cloud industry sees ‘a step in the right direction’

The Cloud Infrastructure Services Providers in Europe (CISPE) — a nonprofit trade group — welcomed the “strong definitions” of Levels 3 and 4, and said that, if implemented well, the proposed rules could “help to challenge the commercial dominance of established foreign cloud and AI vendors.”

However CISPE also called the current Level 1 and 2 criteria “confusing and non-sensical,” and said they should not be designated as “sovereign” since US hyperscalers can meet the requirements. “This will continue to confuse the market, both public and private customers, and encourage more sovereignty washing attempts,” CISPE said in a blog post Thursday.

CISPE also said the proposals fail to require public authorities to check whether a European service exists before opting for a foreign supplier. “We see a significant risk that assessments become a ‘rubber-stamp’ exercise that allow IT departments to continue to buy non-sovereign services out of convenience,” the organization said.

French firm OVHcloud — one of the leading European cloud computing and web hosting companies — welcomed the proposals, though it said any rules must be carefully scoped to ensure they are effective.

“This text is a step in the right direction and represents an opportunity to strengthen European strategic autonomy — something unthinkable just a few years ago,” an OVHcloud spokesperson said. “It provides a useful framework, but one that must not leave too much room for exceptions and workarounds. 

“Europe must and can move much faster, with very clear rules and a genuine European preference. Beyond this text, the Commission has demonstrated with its sovereign procurement call that it is possible to act right now to reduce critical dependencies. The time for waiting is over. We must accelerate. We must clarify. We must own it. 

“Europe has the players and the expertise,” the spokesperson said. “It is time to turn political ambition into European industrial capability.”

The overall tech sovereignty package “marks the overdue shift from diagnosis to treatment,” said a spokesperson at Ionos, a German cloud and hosting company. Ionos pointed to the EC’s claims that more than 80% of digital products, services and infrastructures in the EU originate from non-European providers, while 264 billion euros flow from EU organizations into predominantly US-based IT products.

“This is a strategic failure that must now be corrected,” the spokesperson said. While the company applauded the Commission’s focus on “secure and sovereign cloud and AI infrastructure for highly critical use cases,” it argued the CADA proposals fall short. “The central weakness of the package: the approach remains predominantly supply-side. The decisive lever — the demand side – is missing. Public procurement is the most powerful instrument for digital sovereignty. The public sector as anchor customer is critical for scaling sovereign cloud and AI solutions.

“Europe will remain dependent on Nvidia and AMD for GPU computing, the spokesperson said. “What matters is not whether to cooperate, but on what terms: data under European law, operations by European providers, no extraterritorial access. …If EU funding earmarked for ‘sovereign cloud’ ends up with the European subsidiaries of US hyperscalers, the package will have failed its objective.”

The real impact on hyperscalers

The proposed rules could require hyperscalers to change tactics to cater to European customers, or to at least ramp up existing sovereign cloud strategies. “For vendors, this is essentially a shift in what ‘competitive’ means,” said Pereiro. “For the last decade, scale and hyperscaler alignment were enough. That’s no longer the case.”

Cloud providers will need to demonstrate real control over data, infrastructure, and operations, he said, and not just label solutions as “sovereign.”

“The bar has been raised, and some existing offerings simply won’t clear it,” he said.

While the CADA rules are designed to favor European providers in some cases, the proposals stop short of barring US providers from public sector contracts. “It doesn’t shut them out,” said Pereiro, “but it changes competitive conditions substantially.”

The proposed procurement requirements make sovereignty a “gating factor” for sensitive workloads, said Pereiro, and “create real friction for providers whose operating models depend on centralized control or non-EU jurisdiction.”

US tech firms tout support

US hyperscalers publicly welcomed the proposals, and indicated plans to work with policy makers and ensure the importance of customer choice in cloud service procurement.

“We look forward to reviewing the proposed rules and continuing to work alongside our partners to ensure European organizations have the power of choice and sovereign control,” a Google spokesperson said.

An AWS spokesperson said the company has invested ”tens of billions of euros” in European cloud infrastructure, which it claims has “already advanced the continent’s competitiveness, helped organizations innovate and grow, and supported the development and resilience of both public and private services that Europeans now rely on every day.

“European organizations deserve access to the best technology available from trusted providers, chosen on the basis of security, performance, verifiable controls, and value,” the AWS spokesperson said. “We look forward to working with policymakers to ensure the Cloud and AI Development Act promotes technology choice and rewards long-term investment in Europe’s digital future.”

A Microsoft spokesperson said the company shares the EU’s “ambition to strengthen technological sovereignty and global competitiveness in AI, grounded in openness, partnership and fair competition.

“Achieving this will depend on access to world-class infrastructure and technologies at scale,” the Microsoft spokesperson said. “That means enabling European companies and public administrations to make procurement choices based on a broad, risk-based assessment in an open and competitive market.

“Microsoft offers secure and sovereign cloud solutions that put customers in control, and we stand ready to help build a strong, resilient and globally connected AI ecosystem in Europe.”

While the proposals present potential hurdles for US hyperscalers, those that adapt to the new regulatory direction — and concerns of European organizations — will benefit, said Pereiro. “If your offering aligns with sovereignty requirements, your company will be likely to see more opportunities, not fewer,” he said.

The age-old IT defense when compliance violations are investigated by regulators is to try and keep a low profile — and hope no one looks too closely. But with enhanced SEC interest in all data breaches encouraging regulators around the globe to take those closer looks at IT, data breach disclosure rules are becoming more strict.

While that might be unsettling for cybersecurity executives, it is also disturbing news for IT admins, who could find themselves under a remarkably uncomfortable spotlight. 

Consider this recent move by the New York State Department of Financial Services against the Delta Dental Insurance Company. State officials hit the insurance company for improper and inconsistent enforcement of its own data retention policies; improper incident response plan protocols; and improper notification of the security incident itself. 

The company was fined more than $2 million.

The data retention violations are perhaps the most problematic. Had that policy been enforced properly, much of the stolen data would have been destroyed long before the attackers could have accessed it. 

It’s not simply a matter of whether the IT rules for retention were sufficiently strict. Some regulators — and especially the US Federal Trade Commission (FTC) — focus extensively on companies who don’t do what they say publicly. If a corporate website promises something to customers, the FTC will hold companies to their word. 

Think about that the next time you assign a summer intern to handle your website’s copy. 

Inconsistent implementation of data retention policies can deliver other legal headaches. Having a good policy approved by the general counsel is fine, but it means nothing if all of your people do not follow it strictly. 

Let’s say one of your business units is being sued for having done something naughty. Opposing counsel subpoenas your business records, including emails from a few years ago. Your attorney responds that those email records no longer exist; they were deleted last year in accordance with corporate policy on data retention that says everything of a certain nature has to be deleted after one year. 

Fair enough. But what if opposing counsel in a deposition asks,“Really? Does that policy apply to all records of that nature?” You say that it does. 

“It might interest you to know that we have sworn testimony from four other employees who showed us emails of the same nature that were more than five years old. So why did you adhere to your policy regarding emails that might prove the fraud but somehow you did not delete others? Sounds a little selective, no? I think the judge would agree.”

In the dental case, the company had a strict policy on retention rules. But corporate software was programmed with “the ability to shorten, extend, or disable MOVEit Transfer’s default retention settings on a folder-by-folder or file-by-file basis.” 

The regulators then swooped in because the insurance company “had no written policy or procedure for requesting, reviewing, or approving such changes to folder retention settings.”

The best retention policy would, in theory, have no exemptions. But if you’re going to allow exemptions, you need a precise policy documenting how and when they can occur. There should be a required form so that a manager can write out the reasons for this specific exemption.

The New York state document is an important one to carefully review; it provides an excellent roadmap to how compliance can go wrong — and useful information on how to keep something similar from  happening to your company.

The European Union has now published a set of measures aimed at boosting Europe’s tech industry to help reduce reliance on US and Chinese suppliers for AI, cloud, and semiconductors. The proposals include rules to restrict the use of US hyperscalers for certain public sector procurement purposes, but stop short of banning them outright.

“Technological sovereignty does not mean protectionism. Europe remains grounded in openness, partnership, and fair competition,” Henna Virkkunen, executive vice president for Tech Sovereignty, Security and Democracy, said in a statement Wednesday. “At the same time, Europe wants to be in the position to make its own choices, avoiding dependence on single dominant suppliers, especially from non-like-minded countries.”

The European Technological Sovereignty Package — released after several delays — includes two legislative proposals: the Cloud and AI Development Act and Chips Act (CAIDA) 2.0 and the Open Source Strategy and Strategic Roadmap for Digitalization and AI in Energy.

CAIDA aims to triple data center capacity in the next five to seven years by easing restrictions for deployments across the EU. It also includes rules that, if enacted, would require EU public bodies to meet certain sovereignty criteria for cloud service procurement related to certain sensitive workloads.

Amid ongoing trans-Atlantic tensions and a long-time deep reliance on US tech providers, European organizations have become increasingly wary of a “kill switch” that would cut off access to digital services. There are also concerns that US hyperscalers could be compelled to share data with US government under the CLOUD Act and Foreign Intelligence Services Act (FISA), even when data centers are located in Europe.

The CAIDA proposals include four levels of criteria for suppliers; the most basic includes data center infrastructure located and operated in the region – something  many US cloud suppliers already provide – with stricter rules around supplier ownership, full control over the software stack, and more stringent cybersecurity certification.

The majority of existing EU public sector workloads (70%) fall under the first level, with 20% at level 2, and 9% at level 3. Only a small proportion (1%) of the most sensitive workloads would require level 4.

Other proposals include the Chips Act 2.0, a follow-up to the 2023 legislation that sought to improve semiconductor production capabilities; the updated version now aims to boost research and spur demand for domestically produced processors. 

The legislative proposals must be negotiated by the European Parliament and Council of the European Union before adoption.