Your AI is making decisions.
But are you able to verify what it did?
In a world where AI agents outnumber humans and make autonomous decisions at scale, proving what happened through verification is the non-negotiable foundation for trust. Enterprises, governments, and individuals will demand AI that verifies, not just claims, what it does with their data, their authorization, and their decisions.
Advanced AI Society is the industry association for companies building verifiable AI, a category of AI security. Our goal is to make verifiable AI publicly definable, commercially procurable, independently certifiable, and broadly insurable so that verification becomes the default for every AI system.
Every enterprise deploying AI is asking the same question: how do we know what the machine did?
Logs can be fabricated. Policies describe intent, not behavior. Contracts assign blame after the fact. None of these constitute independent evidence.
This is the Verifiability Gap: the absence of independent evidence of what AI systems actually do. It's the reason enterprises are stuck between constraining their agents and accepting unmanaged risk. And without that, trust evaporates.
What AI did
Actions, decisions, data accessed
The Verifiability Gap
No independent evidence
What you can verify
Logs? Policies? Contracts?
[ Proof-of-Control ] closes the gap
79%
of organizations deploying agentic AI can't observe what their systems actually did.
They're stuck between two bad options: constrain agents and lose value, or unleash them and accept unmanaged risk.
The Agent Risk-Value Matrix
Risk ↓
FAILED
Risk ↑↑ Value −
Agents unchecked. Nothing to show for it.
WITH Proof-of-Control
Risk ↓↓ Value ↑↑
Agents free + proved.
The only quadrant that works.
CONSTRAIN
Risk ↓↓ Value ↓↓
Safe, but agents can't do their job.
UNLEASH
Risk ↑↑ Value ↑↑
No way to verify what they did.
Risk ↑
Proof-of-Control sits at the intersection of the two fastest-growing categories in AI.
AI Data is the fastest-growing AI spending category at 155% CAGR. Proof-of-Control generates the evidence.
AI Security is the second fastest-growing at 74% CAGR. Proof-of-Control delivers the security.
141%
Increase in enterprise agentic AI spending
50%+
Enterprises deploying AI agents by 2028
#1
Cybersecurity trend: agentic AI security
Source: Gartner Forecast: AI Spending, 4Q25 · Gartner Top Strategic Technology Trends 2026
Founding members
“Since becoming a member, we've had new doors open up, starting with our Davos experience. Michael Casey who's been eight times, showed me the ropes, got me into events, and made the introductions that mattered. Without him and his cofounder Tricia Wang from the Advanced AI Society this experience wouldn't have been nearly as valuable.”
CEO, Edge & Node
The Proof-of-Control Initiative
Initiative Co-Chair
“I've spent years building the frameworks the industry relies on to secure AI. Agent Name Service secures Agent discovery, MAESTRO models threats. OWASP AIVSS scores risks. CSA's AI Controls Matrix defines expected practices, with 243 controls across 18 domains. Yet when an enterprise asks, ‘can you prove you have implemented a minimum set of deterministic and verifiable controls for an agentic AI system deployment?’, there is no standard to reference.”
“That is the focus of the Proof-of-Control Initiative. It defines how a minimum control set for agentic AI systems can be implemented, measured, and attested using mathematically verifiable evidence. That's why I'm co-chairing it. We're building the missing piece.”
Participants include all of our members and leaders from Fortune 100 companies, which will be announced soon.
Learn about the Proof-of-Control Initiative →Partners
We work alongside these organizations to advance verifiable AI.
Our Initiatives For Activating the Market
Buyer activation
Getting Proof-of-Control into the rooms where decisions are formed. Events, briefings, and vendor-neutral evidence that internal champions need to get through procurement.
Learn more →The Proof-of-Control Initiative
The first shared standard defining what independent verifiability means and how to evaluate whether a system delivers it. Co-chaired by Ken Huang with founding enterprise members.
Learn more →Insurance activation
Producing the three things insurers need to underwrite AI risk: enforceable standards, auditable evidence, and credible eligibility.
Learn more →Guided by leaders who've moved markets before.
Leadership
Advisors
Noah Ringler
Ex-head of AI
Dept. of Homeland Security
Paul Calatayud
5-time CISO
Investor, cryptographer
Brian Behlendorf
Co-founder, Open Source Initiative
Mozilla and EFF board
Clay Shirky
CTO, New York University
Bestselling author
Sunny Bates
TED brainstrust
Serial entrepreneur
Cyrus Hodes
AI Governance operator
Co-founder of Stability AI & AI Safety Connect
Ryan Kidd
ED of MATS
Noah Ringler
Ex-head of AI
Dept. of Homeland Security
Paul Calatayud
5-time CISO
Investor, cryptographer
Brian Behlendorf
Co-founder, Open Source Initiative
Mozilla and EFF board
Clay Shirky
CTO, New York University
Bestselling author
Sunny Bates
TED brainstrust
Serial entrepreneur
Cyrus Hodes
AI Governance operator
Co-founder of Stability AI & AI Safety Connect
Ryan Kidd
ED of MATS
Future of digital asset management, featuring an insurance roundtable for the Proof-of-Control Initiative and verifiable AI panels with our members.
Future of agentic AI, education, governance, and open-source collaboration — featuring our member Puddin.ai.
Digital Asset & Agentic Commerce Conference. Featuring our member Edge & Node, our partner W3.io, and Agent Graph.
Our member, Hedera, is bringing Council members, enterprises, and industry leaders together to outline the digital economy with a focus on verifiable AI infrastructure.
This is the moment the category gets defined.
Build Proof-of-Control technology?
Inquire about joining as a member→Deploying AI at enterprise scale?
Join the Proof-of-Control Initiative→Want to understand the category?
Request a briefing→Stay connected
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