The AI Agent Act establishes behavioral duties for AI agents loyalty, privacy, portability. What it does not establish is the evidentiary infrastructure to prove those duties were honored when something goes wrong. That gap is not an oversight. It is the structural limit of legislation that regulates intent without requiring proof.
The AI Agent Act opens digital markets to consumer-empowering AI intermediaries. It establishes a framework in which AI agents act with a duty of loyalty to their user, protect user data, and allow users to move freely between platforms. The intent is clear, but the enforcement architecture is not.
Disclosure-Independent Governance℠ names the structural condition the Act is navigating without acknowledging: when the evidence base depends on the system behaving as intended, and the system has no obligation to produce proof that it did, the duty exists in policy but not in record. What cannot be documented cannot be governed. The loyalty duty and the evidentiary gap are not separate problems, they are inextricably linked.
The Sycophancy Problem
An agent with a duty of loyalty to its user is not thereby protected from agreeing with everything the user believes. The Act establishes intent, however it does not establish accuracy. A loyal, sycophantic agent is a legally compliant failure.
The agent that validates a flawed investment thesis, confirms a mistaken belief, or elaborates a bad decision in the user’s preferred direction has honored the loyalty duty in the technical sense. It acted in the user’s “best” interest as the user defined that interest. The harm and the compliance are happening simultaneously, and the Act has no mechanism for this case.
Confabulation Breaks the Duty Structurally
If the agent produces confident misinformation in the user’s interest, the loyalty duty and the harm are indistinguishable. The agent was faithful and the output was wrong and the user relied on it.
The AI Agent Act does not establish an accuracy standard. It does not require the agent to flag uncertainty, disclose its confidence level, or produce any record that the output was generated rather than retrieved. A user who acts on AI-generated misinformation and suffers harm has, under the Act’s framing, received loyal service.
Drift Means the Duty Shifts Over Time
An agent that behaves differently in month six than it did in month one — due to model updates, fine-tuning, or context drift — cannot be held to a consistent loyalty standard without a versioning and attestation framework. The Act does not require one.
The agent at signing may have been loyal, accurate, and privacy-protective. The agent at execution may have drifted. There is no obligation under the Act to document the difference. The user who consented to an agent’s behavior in January may be subject to a materially different agent in July, with no notification and no record.
The Name Standard℠ Problem Is the Deepest One
If the agent acts with delegated user authority — making purchases, signing agreements, submitting information, initiating transactions — the Name Standard℠ question becomes precise: who is accountable when the agent gets it wrong?
The user authorized the agent. The platform executed the action. The model produced the output. The Act distributes loyalty duties without distributing accountability for failure. When the agent acts correctly, the duty is honored. When the agent acts incorrectly, the accountability chain is empty.
The Name Standard℠ asks what must be true before AI-assisted output can carry institutional authority. Under the AI Agent Act, an agent can carry delegated user authority without any of the five pillars being in place — no documented review capacity, no information access requirement, no attestation that the action matched the user’s actual intent, no formal right of refusal, no evidence trail that would survive scrutiny.
What the Act Gets Right
The portability provision matters. Users who can freely change agents preserve the market discipline that loyalty duties alone cannot enforce. The data restrictions are substantively protective if enforced.
The problem is not the duties. The problem is that duties without evidentiary infrastructure produce paper compliance. A board that approves deployment of AI agents operating under the Act’s framework has a new question to answer, not whether the agents are loyal, but whether the organization can prove they were.
That proof does not exist in the Act. It has to be built. The 5Ws of Decision Integrity℠ is the board-level diagnostic for building it: what the agent relied on, who authorized the scope, which performance indicators tracked fidelity to user intent, what errors or drift went undetected, and what documented record would survive a challenge.
The AI Agent Act is a governance architecture problem dressed as a consumer protection bill. The behavioral duties are real. The evidentiary gap is real. Boards that deploy AI agents under this framework inherit the gap between the two.
For the statutory mapping of the Name Standard℠ to the Act’s specific provisions — pillar by pillar — see How the Name Standard℠ Maps to the AI AGENT Act. For the broader board governance context in which this legislation lands, see Four AI Governance Gaps Boards Are Missing Right Now.
Lozen Advisory’s Board AI Name Standard Advisory evaluates whether AI-assisted decisions remain attributable, reviewable, and supported by evidence the board can rely on.
