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Chinese intelligence services have demonstrated AI tools autonomously executing 80 to 90 percent of intrusion workflows. Meanwhile, more than 80 percent of workers in the United States use unapproved AI systems, with 40 percent doing so daily, bypassing security oversight entirely. This dual invisibility—into both adversary AI and internal AI usage—makes it impossible for organizations to trust that AI deployments will behave as intended. Security teams cannot verify what data employees feed into tools or how autonomous systems make decisions. Without observability, enterprises cannot confidently scale AI adoption, even when competitive pressures demand it.

From: How 2026 Could Decide the Future of Artificial Intelligence | Council on Foreign Relations.

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Western leaders often frame US–China competition as a zero-sum sprint to build the biggest, smartest AI models. This fixation on frontier breakthroughs misses the real determinant of power: the ability to deploy AI at scale, across the everyday machinery of the economy, earning public trust along the way. On this front, China may already be years ahead. Beijing treats AI as infrastructure.

From: America is Running the Wrong AI Race • Stimson Center.

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The more autonomously an AI system can operate, the more pressing questions of authority and accountability will become. Should AI agents be seen as “legal actors” bearing duties, or “legal persons” holding rights? In the United States, where corporations enjoy legal personhood, 2026 may be a banner year for lawsuits and legislation on exactly this point. Other societies are already approaching the debate differently—grounding AI’s status in collective frameworks, or spiritual rather than consciousness-based lenses.

From: How 2026 Could Decide the Future of Artificial Intelligence | Council on Foreign Relations.

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The prevailing implicit formula—financial health = education + literacy—is a myth. Consumers don’t want financial education—they want tools.

From: (9) The Illusion of Financial Health Programs: Mindset Matters More Than Literacy.

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The Argentinian government, under President Javier Milei, haas put forward legislation to create a dedicated legal framework for AI. This legislation includes the creation of the “non-human corporation“. That is, legal personhood for entities operated by AIs.

 

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The U.S. government earlier this year said it will place any bitcoin it seizes into a strategic reserve. I suppose a crypto reserve sort of makes as much sense as a gold reserve, at least until people lose interest in crypto and/or the power goes off. But there is a problem with the basic idea here: these bitcoins don’t belong to the United States. Assuming that the criminal complaints are proven, then this money is the fruit of crimes committed against millions of victims, and should be returned to them, whether in the form of bitcoin or whatever, not stashed away in Washington.

From: A record Bitcoin haul & crypto comes to the Pitcairn Islands – Coda Story.

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Uber’s approach to this problem is illustrative. They developed a Standardised A2A (Agent-to-Agent) Client on top of the A2A protocol. This client automates the Secure Token Service (STS) JSON Web Tokem ( JWT )exchange and propagation of the actor chain, ensuring the secure path is also the easiest path for developers to implement A2A calls.

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Analogous to the popular term service mesh, the AI Agent Mesh is the data plane where AI agents communicate with each other to complete tasks assigned to them. Within the Agent Mesh and for outbound calls (such as to MCP tools), AI agents rely on JWT tokens minted by the Security Token Service for authentication.

From: Solving the Identity Crisis for AI Agents.

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The U.S. government earlier this year said it will place any bitcoin it seizes into a strategic reserve. I suppose a crypto reserve sort of makes as much sense as a gold reserve, at least until people lose interest in crypto and/or the power goes off. But there is a problem with the basic idea here: these bitcoins don’t belong to the United States. Assuming that the criminal complaints are proven, then this money is the fruit of crimes committed against millions of victims, and should be returned to them, whether in the form of bitcoin or whatever, not stashed away in Washington.

From: A record Bitcoin haul & crypto comes to the Pitcairn Islands – Coda Story.

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I hadn’t heard the term “shadow AI” before, but I think it’s a very useful addition to the tech lexicon. I came across it while reading about a first-of-its-kind filing by a US bank (CB Financial, the parent of Community Bank) concerning an incident where an employee fed customer data into an unapproved AI application. A law firm called it the first filing to blame a material cybersecurity incident on “shadow AI”, meaning AI tools that employees use without their employer’s approval.

It goes without saying that the use of shadow AI is already widespread and I don’t doubt that people use it all the time. But what do they use it for?

 

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KPMG partner fined £5,000 for using AI to cheat on AI test
A senior member of the Big Four accountancy firm in Australia uploaded training material on artificial intelligence to an AI platform to answer exam questions

From: KPMG partner fined £5,000 for using AI to cheat on AI test.

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Our data shows that AI use at work is a little messy.

There are gentle tailwinds in the workplace: LLM licenses are bought, training sessions are offered, encouragement from the C-suite is given. But the headwinds are stronger: IT and AI governance; a restricted, limited version of the LLM; reputational risk; fear of AI in general, losing jobs to AI, contravening company policy, looking like you’re cheating.

As a result, “shadow usage” is common. One user reports: “I’m closing tickets 2x faster, my code reviews have fewer issues, and I got praised in my last performance review. But here’s the thing: nobody knows I’m using AI.”

Another wrote: “I built an AI agent to replace myself secretly. Like 50% of the jobs. I used to bring it up to management the way to do it, so the entire org got the benefit. They end up not buying my idea…now I [am] just doing all of these secretly [sic] and spend the spare time on my own side business.”

We see AI mostly being used to achieve modest, uncontroversial wins, some applications in sales and very few where business processes are being fundamentally rethought.

From: How People Are Really Using AI in 2026.

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