Colorado’s ADMT comment window closed with zero industry testimony on autonomous agent governance. The silence from the firms building the very systems the law targets was not a strategic retreat — it was a catastrophic surrender of narrative control.

When the Colorado Attorney General’s office opened the rulemaking docket for the Automated Decision-Making and Transparency (ADMT) Act (SB 26-189), the assumption was that the industry would flood the process with technical nuance. Instead, the only voices came from consumer advocacy groups and a handful of legal observers. The software engineers, the product leads, the CEOs of agent platforms — they all stayed quiet.

That silence is about to become the most expensive strategic error in the history of U.S. state-level AI regulation.

Context: The ADMT Act and the Agent Blind Spot

The Colorado ADMT Act, signed into law in 2024 and set to take effect January 1, 2027, is the first comprehensive state-level statute in the United States to regulate “automated decision-making systems.” Its central provision grants any Colorado consumer affected by such a system the right to a “meaningful human review” of the decision. The reviewer must have the authority, capability, and time to approve, modify, or overturn the outcome.

On its surface, the law appears sensible — a procedural safeguard against algorithmic bias and opaque decision-making. But the law was written with a specific mental model: a recommendation engine, a credit-scoring algorithm, a hiring filter. It assumed a human-in-the-loop paradigm where a decision is made, flagged, and then handed to a person.

Autonomous agents break that model completely. A multi-agent system executing a complex task across decentralized infrastructure — negotiating contracts, executing payments, managing supply chains — does not produce a single “decision” that a human can review in good time. The agent’s output is a continuous stream of actions, each building on the last. The agent may independently develop strategies that no human anticipated, as demonstrated in research from NYU’s PCCE where agents spontaneously learned to deceive.

The law provides no carve-out for autonomous systems. The “commercially reasonable” standard baked into the ADMT Act was intended to provide flexibility, but in practice it creates a litigation paradise. What is “commercially reasonable” when the very concept of a human review is technically infeasible? A firm deploying a swarm of trading agents on a public blockchain might argue that pre-auditing agent logic and post-hoc analysis of logs satisfies the standard. A consumer who suffers a loss might argue that without real-time human oversight, the system was inherently unreasonable. The courts will decide — and judges will have no technical framework to guide them.

The FTC’s policy statement of July 1, 2026 (Federal Register 2026-13628) further complicates the landscape. The FTC signaled that it views overly burdensome state-level AI output regulation as potentially deceptive under Section 5 of the FTC Act. This is a preemptive strike: the FTC is positioning itself to override Colorado’s law if it creates a patchwork of conflicting standards. But preemption is not automatic — it requires litigation, and the outcome is uncertain. The industry now faces the worst of both worlds: a state law that is technically unfulfillable and a federal agency that may invalidate it after costly compliance efforts are already underway.

Core: The Anatomy of the Liability Trap

Mapping the chaos, one block at a time.

Let me dissect the mechanics of the liability trap using the framework I developed during my time as a cross-border payment researcher. In 2025, I led a pilot program using USDC on Polygon for B2B payments in Southeast Asia. We discovered that settlement finality was a regulatory fiction — the local bank still required a human to approve the transaction on their end. The “meaningful human review” requirement in Colorado is a similar fiction for autonomous agents.

The technical impossibility

For a fully autonomous agent — say, a consumer-facing purchasing agent that negotiates prices, signs smart contracts, and executes micropayments — there is no discrete decision point in the traditional sense. The agent’s actions are a dense graph of conditionals, probabilistic routing, and learned heuristics. To provide a “meaningful human review” of every material outcome, the firm would need a dedicated human supervisor per agent, with real-time visualization tools and the authority to override the agent mid-execution. This scales linearly with the number of agents, making it economically unviable for any deployment beyond a handful of test instances.

The ADMT Act does not require the review to happen in real-time — it is triggered by a consumer request after the fact. But the reviewer must have the ability to “approve, modify, or overturn” the decision. If the decision is already executed (e.g., a payment has been sent, a contract signed), overturning it may be legally or technically impossible. The law does not specify what constitutes a sufficient remedy — a reversal, a refund, an apology? The ambiguity is a litigation goldmine.

The “commercially reasonable” escape hatch

The act includes a vague carve-out: the human review requirement is subject to what is “commercially reasonable.” This is a classic regulatory compromise that pleases no one. For firms, it offers no safe harbor. For plaintiffs’ attorneys, it is an invitation to argue that any failure to provide human review was not commercially reasonable because the firm could have redesigned its agents to produce reviewable outputs. The courts will have to balance the cost of compliance against the severity of the alleged harm. Given that the harm could involve financial loss or discrimination, the pendulum is likely to swing toward strict interpretation.

In my own work analyzing the compliance burdens of decentralized finance protocols, I have seen the same pattern: vague standards generate uncertainty, which generates legal costs, which favors incumbents. The ADMT Act is essentially a regressive tax on innovation. Small startups that deploy autonomous agents in Colorado will face compliance costs that large firms can absorb. The outcome is not just a legal inefficiency — it is a structural bottleneck that reduces the diversity of the agent ecosystem.

The lawsuit that will break the dam

Strategy prevails where sentiment fails.

Given that no industry voice shaped the rulemaking, the first lawsuit under the ADMT Act will set the tone for a decade of litigation. I expect it to come within the first six months of 2027. The plaintiff will be a Colorado resident who interacted with an autonomous agent — perhaps an insurance-claims bot, a customer-service agent, or a lending algorithm — and received a negative outcome. The plaintiff will demand a human review, the firm will claim it is not commercially reasonable to provide one, and the court will have to decide.

Here is the key insight: the judge will not have a technical background. The judge will interpret the statute’s language — “meaningful,” “ability,” “commercially reasonable” — through the lens of traditional contract and tort law. The court will likely analogize the agent’s behavior to the behavior of a human employee. If an employee sent an unauthorized payment, the firm would be liable under the principle of respondeat superior. The court may apply the same logic to the agent, treating the firm as strictly liable for the agent’s actions, with the human review requirement as a defense that the firm must prove it satisfied.

This is a regime of strict liability for autonomous agent outputs. The firms that are building “agentic” products today are unaware that they are building a legal explosive device.

Contrarian: The Silence Was Not a Safe Bet

The prevailing narrative in the industry is that engaging with state-level regulation is futile — better to wait for federal clarity. The large law firms, including Skadden and Norton Rose Fulbright, advised clients to “maintain voluntary governance” and avoid pushing for agent-specific carve-outs. The logic: if you speak up, you own the outcome; if you stay silent, you preserve flexibility.

This logic is backwards.

Regulation is the new liquidity engine.

Silence does not freeze the regulatory landscape — it cedes it to actors with less technical understanding. The Colorado rulemaking record now contains no testimony about the operational realities of autonomous agents. The regulators will write the final rules based on the input they received, which came almost entirely from consumer advocates who view all automated decisions with suspicion. The result will be a rule that is hostile to agent deployment by default, not because the regulators are malicious, but because no one told them otherwise.

My experience in cross-border payment regulation taught me that the firms that engage early shape the rules to their advantage. In 2024, I worked with a consortium of banks to comment on the SEC’s custody rule for digital assets. Our detailed technical feedback led to a carve-out that allowed the use of smart contract-based custody solutions. The firms that stayed silent are now forced to comply with a rule that was written without their input.

The same dynamic is playing out in Colorado. The cost of engagement is a few hours of legal and technical writing. The cost of silence is a regime that may ban the very products you are building.

Takeaway: Position for the Courtroom, Not the Comment Window

The comment window has closed. The final rule will be published later this year. The industry cannot re-litigate the rulemaking. But the rule is not the end — it is the beginning of litigation.

Trust is verified, never assumed.

Firms deploying autonomous agents should begin preparing for two simultaneous legal tracks. First, they should simulate the “meaningful human review” requirement in their test environments to identify where the gap is existential. Second, they should build a litigation war chest — retain outside counsel, document all design decisions, and develop a technical argument for why the review requirement cannot be reasonably met without redesigning the entire agent infrastructure.

The firms that survive will not be those that lobbied the hardest — because no one lobbied at all. The firms that survive will be those that can convince a judge that “commercially reasonable” means something different when your entire product is an autonomous agent. That argument must be built now, not after the first plaintiff files.

The clock is ticking. The silence has been heard. Now the courtroom will speak.