Responding to bipartisan Congressional demands for continuous agent verification and third-party oversight, Advanced AI Society announced on September 17th, 2026 that it has joined the Linux Foundation and LF Decentralized Trust. The move comes alongside the release of Proof-of-Control v1.0, a working draft now open for public feedback through October 30, 2026 at advancedaisociety.org/proof-of-control.

The new standard addresses what the alliance calls the Verifiability Gap: as autonomous AI agents execute tasks faster than human oversight can monitor, traditional audit cycles become inadequate. Proof-of-Control, developed with input from over 80 global security leaders across enterprise sectors, enables independent verification of agent actions without requiring trust in the operator's claims. By hosting the standard within the Linux Foundation's neutral commons, the alliance ensures that verification mechanisms remain transparent and vendor-independent.

The core principle underlying the initiative is that verification cannot be controlled by the entity being verified. Instead, unaffiliated third parties, alongside agent developers and deployers, must retain the ability to openly inspect agent execution. This approach extends open-source principles into what the alliance describes as the agentic stack—the infrastructure layer where autonomous systems operate—making inspection and verification standard practice rather than optional oversight.

Built by our members and over 80 global security leaders, Proof-of-Control brings production-proven verifiable AI technologies together into a unified open standard. Safety checks and traditional audits are necessary, but when AI agents act in milliseconds, an annual or even quarterly stamp of approval isn't enough. Trust requires continuous monitoring anyone can inspect. Launching at LF Decentralized Trust prevents a single company from owning the referee.

Tricia Wang, Co-Founder and CEO of Advanced AI Society

Ken Huang, Co-Chair of Proof-of-Control, explained the technical approach: Proof-of-Control requires agents to have their authority defined before execution begins, produces evidence during runtime that the agent remained within those boundaries, and makes that evidence auditable across the entire agent lifecycle. This transforms what would otherwise be an unverifiable claim into inspectable proof.

An agent's runtime log is just a claim until anyone can verify it for themselves. Proof-of-Control turns open verification into standard operating practice: it requires an agent's authority to be defined before it acts, produces evidence at runtime that it stayed inside that authority, and makes that evidence auditable across the whole agent lifecycle.

Ken Huang, Co-Chair of Proof-of-Control

Trusting AI agents requires decentralized mechanisms that no single vendor can control or alter, making LF Decentralized Trust the natural home for this moment's urgency.

Daniela Barbossa, General Manager, Decentralized Technologies, Linux Foundation, and Executive Director, LF Decentralized Trust

Dr. Hart Montgomery, CTO of LF Decentralized Trust, drew a parallel to cryptographic practice: when non-deterministic machines make decisions in milliseconds, human inspection becomes infeasible. Only automated verification tools can operate at the required speed. As a lab within LF Decentralized Trust, Proof-of-Control applies the evidentiary standards established by projects such as AnonCreds and Trust Over IP to the domain of autonomous agents, enabling developers to verify machine authority without relying on proprietary black boxes.

Public Launch Event

Advanced AI Society and LF Decentralized Trust will co-host a public launch briefing on Wednesday, September 23, 2026, titled "Who's Watching the Machines? Launching Open Verification, the Proof-of-Control Standard for the Agentic Era." The event will feature alliance leaders, builders, deployers, and policy experts. Registration is available at advancedaisociety.org/announcements/webinar1.

Industry and Expert Backing

The initiative has attracted support from leaders across healthcare, finance, cybersecurity, and critical infrastructure sectors. Charles Iheagwara, Global Head of AI & Cybersecurity at AstraZeneca and Distinguished Review Board member, stated that the pharmaceutical industry operates on a broken trust model based on vendor assertions rather than evidence, which becomes untenable when patient safety and intellectual property are at stake.

We're running on a broken trust model, vendor assertions instead of evidence. That doesn't work when patient safety and our intellectual property are on the line. We need open verification: a transparent, inspectable way to know what these agents actually did. That's the gap Proof-of-Control closes, and it's why I've joined this effort at Advanced AI Society.

Charles Iheagwara, Global Head, AI & Cybersecurity, AstraZeneca; Distinguished Review Board of Proof-of-Control, Advanced AI Society

As AI agents become more powerful and ubiquitous, knowing who they belong to, and what they are authorized to do, will be critical. Proof-of-Control is an important part of that.

Bruce Schneier, Cryptographer, Technical Advisor & Distinguished Review Board on Proof-of-Control, Advanced AI Society

J. Christopher Giancarlo, former Chairman of the U.S. Commodity Futures Trading Commission and Senior Advisor to Advanced AI Society, emphasized that financial markets and regulatory frameworks depend on trust grounded in verifiable, audit-ready evidence. Extending this discipline to autonomous AI agents in an open manner provides the agentic economy with a foundation that institutions can rely on, particularly as AI systems assume real economic authority in digital financial markets.

Financial markets and regulatory frameworks rely upon trust that is firmly grounded in verifiable, audit-ready evidence. Bringing that same legal and structural discipline to autonomous AI agents in the open gives the agentic economy a foundation of trust that institutions can actually rely on. Proof-of-Control provides the machine-verifiable proof necessary as AI systems assume real economic authority, especially in digital network financial markets.

J. Christopher Giancarlo, former Chairman, U.S. Commodity Futures Trading Commission (CFTC); Senior Advisor, Advanced AI Society

As agents become more capable, more numerous, and faster, 'human in the loop' doesn't cut it anymore, too generic, too vaguely specified, and vendor self-regulation is too compromised. Agents need to be logged and the logs need to be open for claims about their behavior to be validated.

Clay Shirky, Vice Provost for AI and Technology in Education at New York University

Bob Blessing-Hartley, CTO of Shielded Technologies, noted that the company's Midnight project was built on the principle of not requiring anyone to take claims on faith. Proof-of-Control extends that standard to AI agents.

Midnight was built on the premise that you shouldn't have to take anyone's word for it. Proof-of-Control brings that same standard to AI agents, and we're glad to support it.

Bob Blessing-Hartley, CTO, Shielded Technologies

Anoop Nannra, co-founder and CEO of Oko Labs, drew a connection between blockchain infrastructure and agent verification. After years at Cisco building provable security frameworks that eventually underpinned cyber assurance and blockchain practices, he sees Proof-of-Control as performing the same function for agents at the network layer, allowing machine risk to become measurable, priceable, and insurable at agent velocity.

At Oko Labs, we are building blockchain into the fabric of the internet, which lets verification live in the network itself. I spent years at Cisco making security provable enough to underwrite first through a cyber assurance captive and then the blockchain practice and Proof-of-Control does that exact job for agents. Prove control at the network layer, and machine risk becomes something the market can measure, price, and insure at agentic velocity.

Anoop Nannra, co-founder and CEO, Oko Labs

As AI agents begin making decisions that affect people's healthcare and money, 'trust us' isn't a sufficient security model. We need open, continuous ways to prove what an agent was authorized to do and what it did: which healthcare decisions were made; how data was collected and used, and what was billed, when, and why; which is why Emme is participating in Proof-of-Control.

Erynn Petersen, CEO, Emme

When an AI agent can move money, institutions need more than a persuasive explanation: they need defined authority and evidence they can check. Solv supports the development of Proof-of-Control as an open standard that helps separate what an agent was permitted to do from what the evidence shows it did.

Patrick Duffy, Founder and CEO, Solv Labs

Noah Ringler, former AI Policy Lead at the U.S. Department of Homeland Security and Senior Advisor to Advanced AI Society, characterized open verification as moving from a commercial preference to a national security imperative when agents operate within critical infrastructure. Security teams and auditors should not have to accept an agent's post-hoc explanation of its actions.

When AI agents operate inside critical infrastructure, open verification moves from a commercial preference to a national security imperative. No security team or auditor should have to take an AI agent's word for its own actions after the fact. Proof-of-Control delivers the open, verifiable evidence required to keep critical national systems safe, transparent, and accountable.

Noah Ringler, former AI Policy Lead, U.S. Department of Homeland Security; Senior Advisor, Advanced AI Society

Jim Schwoebel, Director of Research at Advanced AI Society and CEO of Quome, used an aviation analogy to illustrate the stakes: deploying autonomous agents without open verification is comparable to flying an airplane without brakes or a flight recorder. When agents execute thousands of actions per second, unverified errors do not remain localized but compound exponentially into systemic crises. The Open Verification Lab at Advanced AI Society was established to provide developers and security teams with open, tamper-evident tools, standards, and research.

Deploying autonomous agents without open verification is like flying an airplane with no brakes and no flight recorder. When agents execute thousands of actions a second, unverified errors don't just stay local, they compound exponentially into systemic crises. We established the Open Verification Lab at Advanced AI Society to give developers and security teams the open, tamper-evident tools, standards, and research needed to keep autonomous execution safe and within human control.

Jim Schwoebel, Director of Research, Advanced AI Society, CEO of Quome

Michael Casey, Co-founder of Advanced AI Society, framed open verification as essential infrastructure for safely delegating authority to machines. Decentralized cryptographic systems must enable agents to prove they remained within their boundaries without forcing individuals, governments, or enterprises to expose sensitive data. While unchecked machine execution presents existential risk, open verification transforms it into an opportunity to delegate humanity's largest challenges safely.

To safely delegate real authority to machines, we need decentralized cryptographic infrastructure that proves an agent stayed within its boundaries without forcing individuals, governments, or enterprises to expose private, sensitive data. Unchecked machine execution presents an existential civilizational risk, but with open verification, it becomes our greatest opportunity to delegate humanity's biggest challenges safely. Housing Proof-of-Control at LF Decentralized Trust gives society the open, tamper-evident foundation required to make trust in AI possible.

Michael Casey, Co-founder, Advanced AI Society

Bettina Warburg, Co-Founder of Advanced AI Society, connected the initiative to her decade-long investment in digital asset primitives. Open, decentralized protocols have created new ways to establish and exchange value. As autonomous agents begin operating across businesses and daily life, society needs shared, verifiable reality: evidence of what agents control, what occurred, and which actions can be attributed to them.

I've spent the past decade investing in digital asset primitives because I believed open, decentralized protocols could give us new ways to establish and exchange value. Today, I see those same foundations taking on a broader role. As autonomous agents begin to act across our businesses and daily lives, we need a shared, verifiable reality: evidence of what they control, what happened, and which actions can be attributed to them. Proof-of-Control extends the work of decentralized infrastructure into the age of machine agency.

Bettina Warburg, Co-Founder, Advanced AI Society

Public trust cannot be built on closed-door audits or hand-picked stamps of approval. When autonomous agents make real-world decisions that affect people's lives, communities and public institutions shouldn't have to take a hired auditor's word for what happened. Open verification ensures machine accountability remains a public good rather than a walled garden.

Sheila Warren, Co-Founder, Advanced AI Society

Advanced AI Society is an alliance dedicated to making trust in AI possible. The organization builds the open verification ecosystem for AI security, uniting market leaders and deployers with insurers, policymakers, and civil society to standardize, deploy, and scale verifiable AI. More information is available at advancedaisociety.org/

Source: The Next Web