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This week didn’t feel like “AI progress” so much as a fight over who gets to steer it. Pope Leo used his first encyclical to argue that governments should slow down and regulate AI before misinformation and weapons systems outrun human control, a signal that the legitimacy debate is moving well beyond tech circles. At the same time, the market kept sprinting: a burst of rapid-fire acquisitions across major labs showed how quickly AI is consolidating through talent deals, tooling buys, and quiet licensing structures.

Regulators, meanwhile, are trying to pin the outputs to the source. The EU’s AI Office is pushing forward on a transparency code for marking and labelling AI-generated content under the AI Act, while SpaceX’s IPO filing offered a rare, unusually candid look at how a frontier AI program frames regulatory risk and “orbital compute” ambitions. And with Andrej Karpathy landing at Anthropic, the frontier talent race is clearly still on.

This week’s article argues that the “AI adoption gap” is not the result of whether lawyers use AI (they do), but whether firms and vendors have done the unglamorous work that turns occasional logins into trusted, repeatable practice.

➡️ Pope Leo Urges Governments To Slow Down And Regulate AI | Reported by Reuters In his first encyclical, "Magnifica Humanitas," Pope Leo called on governments to slow and tightly regulate AI development, warning of misinformation and autonomous weapons advancing "beyond any human reach to govern them." The nearly 43,000-word document urges robust legal frameworks, independent oversight, worker protections, and child safety, and states AI must never be entrusted with lethal decisions. Anthropic co-founder Chris Olah attended the launch, acknowledging frontier labs face commercial pressures requiring outside scrutiny.
^{May 25, 2026, Source: Thomson Reuters}

➡️ Four AI Labs Make Acquisitions In Five Days As Consolidation Accelerates | Anthropic, Mistral, Google DeepMind, and Meta each absorbed an AI startup within five days, signaling a consolidation phase structured as talent deals and technology licenses rather than traditional acquisitions. Anthropic bought SDK infrastructure firm Stainless for over $300 million; Mistral acquired physics-AI startup Emmi; DeepMind licensed Contextual AI's team in an $80-90 million deal structured to avoid antitrust review; Meta acqui-hired Dreamer. The pattern follows Anthropic's $30 billion raise at a $900 billion valuation.
^{May 25, 2026, Source: Startup Hub}

➡️ EU Advances AI Transparency Code Under The AI Act | The European Commission's AI Office has held a third round of working group meetings on the Code of Practice for marking and labelling AI-generated content, supporting transparency obligations under the AI Act. Working Group 1 addressed marking and detection duties for providers, while Working Group 2 examined disclosure rules for deepfakes and AI-generated text. Industry flagged compliance burdens; civil society pushed for stronger safeguards. Workshops explored watermarking, provenance data, and a uniform EU label. The final draft is expected in early June.
^{May 22, 2026, Source: European Commission}

➡️ SpaceX IPO filing offers rare look at AI regulatory risk through xAI | SpaceX's S-1 securities filing, filed ahead of its IPO, provides one of the most detailed accounts yet of the legal and regulatory risks facing a frontier AI platform. The disclosures cover a broad spectrum of risk around xAI's Grok chatbot and detail plans for "Orbital AI compute": data centers built from millions of satellites to address AI's energy and environmental demands. With Anthropic and OpenAI still private, the xAI disclosures form an unusually comprehensive regulatory-risk inventory.
^{May 21, 2026, Source: Law360}

➡️ Andrej Karpathy Joins Anthropic To Deepen Its Frontier LLM Research | A new critique argues New York’s S7263, pitched as an anti-impersonation bill, would create sweeping liability for chatbots that give “substantive” legal information, without requiring any fake credentials or even concealment that the tool is AI. Because disclaimers wouldn’t shield providers and key terms aren’t defined, critics warn it could chill legitimate legal info tools (including lawyer-supervised use) and invite opportunistic lawsuits. The piece urges lawmakers to rewrite it as a narrower ban on clearly deceptive claims of licensure.
^{May 19, 2026, Source: Tech Crunch}

I spend most of my working week talking to the people building legal AI: founders, CEOs, the engineers and product leads who sit one layer down. I spent the years before that inside the profession those tools are sold to, as a competition lawyer moving between jurisdictions and watching software get bought, praised, and eventually abandoned. With enough time spent observing both sides, a pattern has started to surface.

Everyone has declared victory. And almost nobody is winning yet.

Look at the headline number and the celebration seems earned. The 2026 Legal Industry Report from 8am, drawn from more than 1,300 legal professionals, found that 69% of legal professionals now use general-purpose AI tools for work. This is more than double the 31% recorded for 2025, and a long way from the 27% recorded in 2024. For a profession that treats novelty with suspicion as a matter of professional instinct, that is a genuinely startling rate of change. Three years, and AI went from curiosity to near-default.

But adoption measured in mere logins is a flattering mirror. Look slightly past the headline and the same report shows something less comfortable: 54% of firms provide no training on responsible AI use and have no plans to start, and 43% have no AI policy and no intention of writing one. Individuals have raced ahead, but the institutions employing them have, for the most part, not moved at all.

That is the adoption gap. Not a gap between firms that use AI and firms that don’t (that argument is over) but a gap between using AI and using it well. And it raises a question worth sitting with rather than answering too quickly. When AI underdelivers in a law firm, whose failure is it: the firm that bought the tool, or the tool that was sold to the firm?

Starting with the uncomfortable half.

Most legal AI disappointment is not a technology problem. When AI pilots fail, they tend to fail in the background, and often it’s not because of weaknesses in the models, but because the firm underestimated governance, workflow design, and the unglamorous work of change management.

Click here to continue reading the full interview

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