Picture a familiar scene inside a fast-moving company. After months of internal debate, your organization finally deploys an “agentic” AI assistant—something far more capable than a simple drafting tool. This system does not just summarize emails or suggest edits. It compares vendors, negotiates renewal terms within preset parameters, fields inbound procurement questions, and even interacts directly with purchasing portals. It has access to your shared inboxes, your Slack channels, and your vendor management platform. In early tests, it performs beautifully. It responds quickly, writes confidently, and reduces turnaround time from days to minutes. People begin to rely on it. They trust it. They allow it to communicate externally with minimal supervision because it has proven so efficient.
Please note this blog post should be used for learning and illustrative purposes. It is not a substitute for consultation with an attorney with expertise in this area. If you have questions about a specific legal issue, we always recommend that you consult an attorney to discuss the particulars of your case.
Then one day, buried in a routine email thread with a long-standing vendor, the assistant replies: “Confirmed. We accept the attached order form and the updated terms. Please proceed.”
No executive signed anything. No one consciously clicked “accept.” There was no ceremonial moment of approval. But in that instant, your company may have entered into a binding contract. And depending on what those “updated terms” contained—an indemnity clause you cannot honor, a pricing structure that violates regulatory caps, or a data-processing commitment that breaches privacy law—you may also have entered into an agreement that is unauthorized, noncompliant, or even illegal.
This is the agentic trap: the point at which your AI system stops behaving like a drafting assistant and starts acting like a legal representative.
The danger does not lie in artificial intelligence per se. It lies in autonomy combined with outward-facing authority. When a system can communicate externally in ways that appear deliberate, informed, and authorized, the law may treat those communications as attributable to the organization itself. The unsettling truth is that contract doctrine has been quietly preparing for this scenario for decades. The frameworks that govern electronic commerce, automated transactions, and agency law were not written yesterday. They were written precisely to prevent parties from escaping obligations simply because a machine was involved.
To understand why “the AI did it” is not a reliable defense, one must look first to the statutory architecture of electronic contracting. In the United States, Congress enacted the Electronic Signatures in Global and National Commerce Act (E-SIGN) to ensure that contracts could not be denied legal effect solely because they were electronic. The statute explicitly recognizes the role of “electronic agents,” defined as computer programs or automated means used to initiate actions or respond to electronic records without human review at the time of action. E-SIGN makes clear that a contract cannot be deemed unenforceable simply because its formation involved such an agent. The text of the statute is unambiguous: the presence of automation does not strip a transaction of legal consequence.1
Most states have adopted a complementary framework through the Uniform Electronic Transactions Act (UETA), which similarly contemplates automated transactions and electronic agents interacting with one another. UETA provides that contracts may be formed by the interaction of electronic agents, even if no individual reviews or intervenes in each step of the process. In other words, if two systems exchange messages that meet the requirements of offer and acceptance, a contract can arise, even if no human pauses to scrutinize each communication in real time.2
These laws were designed in an era of online shopping carts and automated ordering systems. Yet their logic applies with equal force to today’s generative, conversational AI. If your AI assistant sends a message manifesting assent to definite terms, and the counterparty reasonably relies on that assent, courts will not be eager to invalidate the agreement simply because the words were produced by code rather than by a human hand.
The real legal fulcrum, however, is not electronic contracting law but agency law. The moment your AI system communicates externally in a manner that suggests it can bind the company, the doctrine of apparent authority enters the picture. Apparent authority arises when a principal—here, your organization—through its own conduct leads a third party reasonably to believe that an agent has authority to act on its behalf. The doctrine protects the reasonable expectations of third parties who rely on the signals the principal sends into the marketplace.3
Notice what the doctrine does not require. It does not require that the principal subjectively intended to confer authority. It does not require a written delegation of power. It focuses instead on outward manifestations. If your AI replies from an official company email address, includes a corporate signature block, refers to itself as “our procurement assistant,” and engages in back-and-forth negotiation over terms, a vendor may reasonably infer that it possesses authority commensurate with its role. That inference can be enough.
Apparent authority is powerful precisely because it is grounded in fairness. The law asks: from the perspective of the counterparty, was it reasonable to believe this representative could bind the company? If your organization created the conditions for that belief—by granting the AI access, branding, and autonomy—the risk shifts to you. The law does not generally require third parties to investigate the internal architecture of your technology stack to confirm whether a human was supervising each message.
This is where the trap tightens. Companies often focus on the capabilities of their AI—its accuracy, its speed, its cost savings—while neglecting how it appears to outsiders. Language matters. Titles matter. Access matters. An assistant that drafts internal memos poses little contractual risk. An assistant that sends polished external emails stating, “We agree,” occupies a very different legal posture.
In practice, accidental contracts are rarely dramatic. They do not resemble formal signing ceremonies. They arise through ordinary business communications. An email stating “We accept your proposal” can be sufficient to form a binding agreement if the essential terms are clear. A message confirming renewal at a specified price can create enforceable obligations. Even a short phrase such as “Approved—please proceed” may constitute acceptance if it follows a definite offer.
Electronic commerce has conditioned courts to treat email exchanges as legitimate vehicles of contract formation. The fact that an AI system composed the message does not alter its external appearance. To the vendor receiving the email, it looks like a communication from your company. And under E-SIGN and UETA, that may be enough.
The more subtle and troubling dimension of the agentic trap is not merely that a contract may form. It is that the contract may bind the organization to terms it was never authorized—or legally permitted—to accept.
Consider heavily regulated environments. In federal procurement, for example, the government is generally bound only by officials possessing actual authority, typically designated contracting officers. Unauthorized commitments can trigger complex ratification procedures and internal compliance consequences.4 While private entities are more readily bound through apparent authority, the public-sector context illustrates how strictly authority can matter. If an AI system purports to bind an entity subject to statutory delegation limits, the result may be an unenforceable agreement, accompanied by significant administrative fallout.
Outside the public sector, illegality may arise from the substance of the terms themselves. An AI assistant optimizing for speed and resolution may agree to pricing structures that violate regulatory caps, indemnification clauses that contravene statutory limits, or data-sharing provisions that run afoul of privacy regimes such as the GDPR or sector-specific health privacy laws. It may accept noncompete language prohibited in certain jurisdictions or warranty provisions that create consumer protection exposure. The system’s objective function—close the loop, resolve the thread, maintain goodwill—does not inherently align with statutory compliance.
There is also the problem of overpromising. Generative systems often write in a tone of confident assurance. They may guarantee performance outcomes, commit to service levels, or promise refunds or indemnities in an effort to be helpful and conclusive. Those assurances can become contractual terms. A casual sentence inserted to smooth a negotiation may evolve into a binding obligation that exceeds what the organization can operationally deliver.
The risk intensifies when agentic systems are integrated directly into vendor portals. Once an AI has credentials permitting it to submit forms, click acceptance boxes, or route digital signatures, it can consummate transactions at machine speed. Clickwrap agreements have long been upheld when assent is manifested through an affirmative act such as clicking “I agree.” Courts have repeatedly treated such electronic acceptance as enforceable.5 If your AI clicks, the law may regard that click as yours.
It is tempting to assume that because no human consciously intended to enter into the agreement, the contract lacks mutual assent. But contract law evaluates assent objectively, not subjectively. The question is not what you privately intended. It is what your outward actions conveyed. If your system sent a message or executed a digital acceptance that objectively signaled agreement to definite terms, the absence of a human keystroke may not rescue you.
The modern shift toward autonomy compounds this issue. Today’s agentic systems are not narrow scripts executing rigid instructions. They are adaptive, conversational, and empowered with discretion. Security analysts increasingly describe them as “nonhuman identities” within enterprise environments—entities that require credential management, permission scoping, and behavioral monitoring akin to that applied to human employees. When such systems are granted broad operational authority without equally robust governance, they can function as de facto representatives of the organization.
The law, however, does not pause simply because technology has grown sophisticated. Agency doctrine evolved in a world of traveling salespeople and regional managers. Its central premise—that principals are responsible for the reasonable reliance their manifestations create—translates seamlessly into a world of digital agents. If anything, the speed and scale of AI amplify the stakes. A human employee might send one errant email. An AI system can replicate the same pattern across dozens of vendors before anyone notices.
Avoiding the agentic trap does not require abandoning automation. It requires designing deployments with legal consequences in mind. The first and most critical safeguard is linguistic control. Systems that communicate externally should be constrained from using language that manifests assent. Phrases such as “we accept,” “we agree,” “approved,” or “please proceed” can carry legal weight. Reframing communications as drafts or recommendations pending human confirmation can materially reduce risk.
Equally important is architectural design. Human-in-the-loop approval gates are not merely compliance theater; they are structural barriers against unintended contract formation. When a message contains pricing terms, scope descriptions, renewal language, or references to attached agreements, it should trigger mandatory human review before transmission. Automation can accelerate drafting and analysis without crossing the line into autonomous acceptance.
Permission management also demands attention. Many organizations default to granting expansive access because it simplifies integration. Yet read-only access combined with internal drafting privileges can capture much of AI’s efficiency benefit without empowering it to consummate transactions. The principle of least privilege—well known in cybersecurity—applies with equal force to legal authority.
There is also a signaling dimension. Titles and descriptions matter. Referring to a system as “our procurement officer” or “legal agent” invites reliance. Framing it explicitly as an “assistant that prepares drafts for review” clarifies expectations. Apparent authority is shaped by how you present the representative to the world. Reducing ambiguity about its role reduces the risk of reasonable reliance.
Internal process design is equally critical. Routing all AI-drafted external communications through centralized ticketing or approval systems creates traceability and oversight. Maintaining comprehensive audit logs preserves evidence in the event a dispute arises. E-SIGN emphasizes the importance of retaining electronic records in a form capable of accurate reproduction for later reference.1 Robust logging is therefore not merely an operational convenience but a legal necessity.
Despite best efforts, incidents may still occur. When an AI system appears to have accepted terms or executed a transaction, organizations should treat the event as a potential legal incident. Preserving logs, isolating the communication, notifying internal stakeholders, and engaging counsel promptly can mitigate downstream consequences. In some contexts, prompt repudiation or clarification may limit reliance damages, though outcomes will vary based on jurisdiction and factual nuance.
At a deeper level, the agentic trap invites a philosophical shift in how organizations conceptualize AI. Rather than viewing it as a tool akin to a spreadsheet or word processor, companies must recognize that autonomous systems operating in external channels function more like employees. They require onboarding processes, defined scopes of authority, supervision, and performance monitoring. They may not draw salaries, but they can incur liabilities.
The broader legal landscape is still evolving. Legislatures and courts are grappling with questions of AI accountability across domains ranging from tort to intellectual property. Yet contract law, with its centuries-old emphasis on objective manifestations and reasonable reliance, is unlikely to undergo radical transformation. Its doctrines are sufficiently flexible to encompass electronic agents without doctrinal upheaval.
For business leaders, the lesson is sobering but clear. The efficiency gains of agentic AI are real. So are the legal consequences. Deploying such systems without a careful mapping of authority, language constraints, and approval workflows is akin to hiring a junior employee and giving them unfettered power to sign contracts on the company’s behalf.
The law will not “blame the robot.” It will look to the principal—the organization that designed, deployed, and empowered the system. If your AI can negotiate and accept, the law may treat its actions as your own. The relevant statutes were written to ensure that electronic processes remain enforceable. Agency doctrines were crafted to protect third parties who rely on apparent authority. Together, they form a sturdy framework that leaves little room for technological surprise as a defense.
The agentic trap, then, is not a failure of artificial intelligence. It is a failure of governance. When autonomy outpaces oversight, when branding outpaces authority controls, and when speed outpaces review, legal risk accumulates quietly until a single message crystallizes it.
In a world where AI can speak fluently, act decisively, and transact instantaneously, prudence demands intentional design. The question is not whether AI systems can form contracts. They can. The question is whether you have structured your systems so they cannot do so accidentally, unlawfully, or beyond the bounds of your organization’s authority.
If you have not yet asked that question, it may be worth doing so—before your most efficient assistant becomes your most expensive mistake.
Contact Tishkoff
Tishkoff PLC specializes in business law and litigation. For inquiries, contact us at www.tish.law/contact/. & check out Tishkoff PLC’s Website (www.Tish.Law/), eBooks (www.Tish.Law/e-books), Blogs (www.Tish.Law/blog) and References (www.Tish.Law/resources).
References
- Electronic Signatures in Global and National Commerce Act (E-SIGN), 15 U.S.C. § 7001 et seq., available at: https://www.congress.gov/106/plaws/publ229/PLAW-106publ229.pdf
- Uniform Electronic Transactions Act (UETA) (1999), National Conference of Commissioners on Uniform State Laws, overview available at: https://www.uniformlaws.org/committees/community-home?CommunityKey=2c04b76c-2b7d-4399-977e-d5876ba7e034 ↩
- Cornell Law School, Legal Information Institute, “Apparent Authority,” available at: https://www.law.cornell.edu/wex/apparent_authority
- Discussion of actual vs. apparent authority in federal procurement context, Tillit Law Firm, available at: https://tillitlawfirm.com/featured-insights/federal-procurement/actual-and-apparent-authority-in-federal-contracting
- GovInfo link for 15 U.S.C. § 7001: https://www.govinfo.gov/link/uscode/15/7001