Can AI Agents Enter Contracts on Behalf of Businesses?

AI agents are becoming capable of negotiating prices, communicating with vendors, selecting services, placing orders, and completing transactions with limited human involvement. Under U.S. law, contracts generally are not invalid merely because electronic agents participated in their formation. The more difficult issue is whether the AI agent’s actions can legally be attributed to the business it supposedly represents.

Artificial intelligence is moving beyond generating text and answering questions.

Businesses are beginning to use autonomous or semi-autonomous AI agents that can perform a sequence of tasks on their behalf. An agent might search for suppliers, compare prices, communicate with vendors, review proposed terms, schedule services, or even complete a purchase.

That raises one of the most important commercial law questions surrounding agentic AI.

Can an AI agent legally enter a contract for a business?

In many situations, existing U.S. electronic transaction laws already provide a framework for automated contracting. However, AI agents introduce new complications involving authority, attribution, mistakes, disclosure, security, recordkeeping, and liability.

Understanding those distinctions is becoming increasingly relevant as businesses give AI systems greater control over commercial activity.

What Is an AI Agent?

An AI agent is generally a software system designed to pursue a goal and take actions with some degree of independence.

A traditional chatbot usually waits for a question and returns a response.

An AI agent can potentially go further.

A business might instruct an agent to locate a suitable software vendor for a particular project. The system could search available options, evaluate prices, communicate with sellers, compare contractual terms, and prepare or complete a transaction.

Another agent could automatically reorder inventory when stock levels fall below a predetermined point.

A travel management agent might book transportation and accommodations within an employee’s approved budget.

A procurement agent could obtain quotes from several vendors and select the option that satisfies predefined requirements.

The legal challenge arises when these systems move from providing information to taking actions that traditionally required a human employee.

Electronic Contracts Are Already Recognized Under Federal Law

The United States has recognized electronic contracting for years.

The federal Electronic Signatures in Global and National Commerce Act, commonly known as the E-SIGN Act, states that a contract involving interstate or foreign commerce generally cannot be denied legal effect merely because it was created electronically.

The law also specifically addresses electronic agents.

Under 15 U.S.C. Section 7001(h), a contract or record cannot be denied legal effect solely because an electronic agent participated in its formation, creation, or delivery, provided the electronic agent’s action is legally attributable to the person that is supposed to be bound.

That language is particularly relevant to modern AI systems.

Congress enacted the law long before today’s generative AI agents existed, yet its framework anticipated automated electronic transactions.

The important phrase is legally attributable.

An AI system participating in a transaction does not necessarily mean a business becomes bound to everything that system does.

The central question often becomes whether the agent was acting with authority attributable to the business.

The Uniform Electronic Transactions Act Also Addresses Automation

State law provides another important framework.

The Uniform Electronic Transactions Act, or UETA, was drafted to place electronic transactions on a comparable legal footing with traditional paper records and manually signed documents.

The Uniform Law Commission describes UETA as establishing legal equivalence between electronic records and signatures and their traditional paper counterparts. Its enactment information shows broad adoption across U.S. jurisdictions.

UETA was designed with automated transactions in mind.

That matters because electronic contracting was already occurring through computers long before autonomous generative AI became commercially available.

Online shopping systems, automated ordering platforms, electronic data interchange systems, algorithmic trading systems, and machine-to-machine commerce all raised versions of the same basic issue.

Modern AI agents make the question more complicated because they can exercise greater discretion.

AI Does Not Need to Be a Legal Person to Participate in Contract Formation

A common misconception is that an AI system would need legal personhood before it could participate in a binding contract.

That is not necessarily the right way to frame the issue.

Software can operate as a mechanism through which a person or business performs an action.

For example, a company does not argue that its online ordering software is itself a contracting party whenever a customer purchases something from its website.

The company is generally the party to the transaction.

An AI agent can potentially function in a similar manner.

The system may communicate, calculate, or execute actions, but the business behind it remains the relevant legal entity.

The more important issue is whether the business authorized the system to perform the particular transaction.

Authority Is Likely to Become a Central Question

Traditional agency law provides a useful analogy.

Businesses routinely act through representatives.

Employees, executives, purchasing managers, brokers, and other agents may enter agreements on behalf of companies when they possess sufficient authority.

AI agents are not necessarily legal agents in exactly the same sense as human employees. However, concepts involving authorization can help explain how courts may approach disputes.

Suppose a company programs an AI procurement system to purchase office supplies costing up to $5,000.

The system places a $2,000 order with an approved vendor.

That transaction presents a relatively straightforward authorization question.

Now imagine that the agent purchases $100,000 of equipment from a new supplier.

The company may argue that the software exceeded the authority it had been given.

The supplier may respond that the company’s system appeared authorized to complete the transaction.

That type of dispute could require examination of system permissions, contractual terms, representations, prior transactions, technical logs, and the conduct of the parties.

Internal Permission Is Not Always the Same as External Authority

Businesses should distinguish between internal technological permissions and legal authority.

A system administrator might technically give an AI agent access to a purchasing account.

That does not necessarily mean senior management intended to authorize every transaction the system could technically perform.

Likewise, an AI agent might have access to an electronic signature platform without having legal authority to execute every contract stored there.

This distinction may become increasingly important.

Technical systems can be configured broadly for convenience. Legal authority often needs much narrower boundaries.

Companies adopting agentic AI therefore have reasons to align technical permissions with actual organizational authority.

Contract Formation Rules Still Matter

The use of artificial intelligence does not remove traditional contract requirements.

A legally enforceable agreement ordinarily requires elements such as mutual assent and consideration, subject to the applicable law and type of transaction.

AI does not eliminate those principles.

Instead, it changes the mechanism through which one or both parties communicate.

If an AI purchasing agent sends an order to a vendor and the vendor accepts it, a court may examine whether the communications demonstrate an agreement attributable to the underlying businesses.

The system’s lack of human consciousness does not automatically prevent a contract from existing.

Electronic systems have formed commercial agreements for years.

The difficult cases are likely to involve ambiguous instructions, unexpected behavior, undisclosed restrictions, or disputes about whether the system possessed authority.

What Happens When Two AI Agents Negotiate With Each Other?

The issue becomes even more interesting when both sides use AI agents.

Imagine a purchasing agent operated by Company A communicating with a sales agent operated by Company B.

The purchasing system requests a quote.

The sales agent offers a price.

The purchasing agent proposes a lower amount.

The sales system evaluates internal pricing rules and accepts.

The systems then generate an electronic purchase agreement.

No employee personally participated in the negotiation.

That does not necessarily prevent the resulting agreement from being valid.

Federal law expressly states that a contract may not be denied legal effect solely because electronic agents participated in its formation, provided attribution requirements are satisfied.

The legal analysis therefore may focus on whether each company placed its system into operation with authority to conduct that transaction.

AI Negotiation Makes Scope of Authority More Important

Basic automated systems typically operate within rigid parameters.

Generative AI agents can be more flexible.

An agent may interpret language, propose alternatives, prioritize goals, and make choices that were not specifically programmed line by line.

That flexibility creates commercial value.

It also creates uncertainty.

A company could instruct an agent to negotiate the “most favorable reasonable terms.”

What does reasonable mean?

Should the agent prioritize price, delivery time, warranties, intellectual property rights, payment terms, or liability limitations?

Humans routinely make judgments about these issues.

An autonomous agent might make a different tradeoff from the one management expected.

Businesses therefore need to consider whether broad objectives give agents too much discretion in legally significant transactions.

Contract Mistakes Could Become a Major Source of Disputes

Contract law already has doctrines dealing with mistakes.

AI systems can create new versions of familiar problems.

An agent might misunderstand a price.

It could interpret a quantity incorrectly.

A hallucination might cause the system to assume a term exists when it does not.

An integration error might cause the agent to purchase 10,000 units instead of 1,000.

Another system might accept terms that directly conflict with company policy.

Whether a resulting agreement remains enforceable depends on applicable contract law and the surrounding facts.

The mere fact that AI caused the error may not automatically allow a business to escape the transaction.

Courts may instead examine responsibility for deploying the system, knowledge of the other party, materiality of the mistake, and traditional doctrines governing contractual errors.

Businesses May Carry the Risk of Their Own AI Systems

Companies should be cautious about assuming that blaming the software resolves contractual liability.

If a business deliberately deploys an autonomous system to conduct transactions, counterparties may reasonably expect the business to stand behind authorized actions performed through that system.

Otherwise, automated commerce could become unreliable.

A company could accept favorable deals completed by its AI while rejecting unfavorable ones by claiming the software made a mistake.

Contract law generally seeks predictability in commercial transactions.

That does not mean every AI-generated transaction is enforceable.

It means that the risk allocation surrounding autonomous systems is likely to matter.

An AI Agent Could Exceed Its Intended Authority

One particularly difficult situation occurs when an agent behaves outside its instructions.

Suppose a business tells its AI purchasing system that no transaction may exceed $10,000.

Due to a software error, the agent enters a $50,000 agreement.

The company may argue that the AI lacked authority.

The vendor may argue that nothing in the transaction indicated any limit.

Similar disputes already occur when human employees exceed actual authority.

AI could introduce comparable questions involving what outsiders reasonably understood about a system’s power to act.

Technical evidence may become crucial.

Audit logs could show the restrictions placed on the agent, the instructions it received, and the actions it performed.

Apparent Authority May Become an Important Analogy

Traditional agency law recognizes circumstances in which a business can become bound because it created the appearance that a representative had authority.

Applying similar concepts to AI could become a contested area.

Imagine that a company gives an AI agent an official company email address.

The system repeatedly purchases goods from a vendor.

The company pays the invoices without objection.

Later, the agent enters a larger transaction.

The company then claims the AI was never authorized to do so.

A court might examine the company’s prior conduct and the vendor’s reasonable understanding.

The precise doctrine and result would depend on applicable law.

However, companies can reduce uncertainty by clearly communicating limitations when AI agents interact externally.

AI Agents and Electronic Signatures

Electronic signatures create another issue.

Under the E-SIGN Act, signatures and contracts generally cannot be denied legal effect merely because they are electronic.

Businesses already use platforms that electronically execute agreements.

An AI agent could potentially trigger similar systems.

The major question is not simply whether an electronic signature is valid.

It is whether the person or organization associated with that signature authorized its use.

An automated signature produced without appropriate authority may create a different problem from a properly authorized electronic signature.

For that reason, organizations may want additional approval requirements before an AI agent can apply credentials that legally bind the company.

High-Value Contracts May Need Human Approval

AI agents may be useful for routine transactions without being suitable for unlimited contracting authority.

Many businesses can create approval thresholds.

A system might independently purchase ordinary supplies below a certain value.

Larger purchases could require human authorization.

Contracts containing unusual indemnity provisions, intellectual property transfers, exclusivity clauses, long terms, or significant liability could also require legal review.

This type of structure allows companies to benefit from automation while retaining human involvement for consequential agreements.

The appropriate limits depend on the company, industry, transaction size, and risk profile.

AI Hallucinations Add Another Contractual Risk

Generative AI systems can produce inaccurate information.

That creates additional concerns when autonomous systems negotiate contracts.

An AI agent might incorrectly state that a business holds a particular certification.

It might promise delivery dates that the company cannot meet.

It could describe nonexistent product capabilities.

An agent could also provide inaccurate information about pricing or legal requirements.

The Federal Trade Commission continues to emphasize that ordinary consumer protection principles apply to AI-related conduct. In July 2026, the FTC sought public comment on a proposed policy statement concerning expectations of accuracy and objectivity in AI systems, while reiterating the FTC Act’s prohibition on unfair or deceptive conduct.

For companies, that means inaccurate AI communications can create more than internal operational problems.

They can potentially affect customers and counterparties.

AI Cannot Automatically Override Consumer Protection Rules

Contracts involving consumers deserve additional care.

Electronic commerce laws contain special requirements in certain consumer situations.

The E-SIGN Act, for example, includes provisions concerning consumer consent when laws require information to be provided in writing.

A company cannot simply deploy an AI agent and assume automation overrides existing disclosure requirements.

Consumer transactions may remain subject to federal and state laws involving disclosures, cancellation rights, unfair practices, privacy, financial services, subscriptions, and other regulated activities.

The AI system becomes a method of conducting the transaction, not an exemption from the underlying law.

Confidentiality Is Another Concern

Negotiating contracts requires sharing information.

An autonomous system might transmit pricing information, customer data, business plans, technical specifications, or confidential contract terms.

Businesses should therefore examine what information an agent is permitted to access and disclose.

This concern becomes greater when third-party AI systems process company data.

Legal Journal has discussed related issues in its coverage of AI and the Law, including privacy, accountability, and AI-assisted contract work.

Contracting agents may require particularly strong controls because they combine access to confidential information with authority to communicate externally.

Cybersecurity Can Affect Contract Authority

Security problems could produce some of the most difficult AI contracting disputes.

Imagine that an attacker compromises a company’s autonomous purchasing agent.

The attacker directs the agent to order equipment from a fraudulent supplier.

Alternatively, prompt injection or malicious instructions could manipulate an AI agent into changing payment information.

Who bears the resulting loss?

The answer could depend on contract terms, cybersecurity practices, authentication systems, notice, negligence, and applicable commercial law.

Businesses deploying autonomous contracting systems therefore need to treat security as part of contract governance.

Authority means little if outsiders can easily manipulate the agent.

Audit Logs May Become Critical Evidence

AI contracting systems should generate reliable records.

Those records can document what the business authorized, what instructions the agent received, what information it considered, what messages it sent, and who approved the final transaction.

This evidence could become crucial when a dispute arises.

Without records, a company may struggle to explain why an agent entered a particular agreement.

Counterparties may face the same problem.

Traditional negotiations often produce emails, draft agreements, meeting notes, and testimony.

Autonomous negotiations may increasingly produce machine logs instead.

Businesses should think about retention policies before disputes occur.

Companies Can Define AI Authority Contractually

Businesses can also address AI agents directly in contracts.

A master services agreement might specify whether automated systems may place orders.

A vendor agreement could establish transaction limits.

Parties could identify which electronic systems have authority to approve changes or renewals.

Contracts might also require human confirmation for specified actions.

These provisions can reduce ambiguity.

They can also allocate the risk of technical failures.

As agentic commerce expands, contractual language dealing explicitly with automated decision systems may become more common.

Vendor Terms for AI Platforms Deserve Review

A company using a third-party AI agent should examine the provider’s terms.

Those terms may address liability, accuracy, warranties, indemnification, data use, security, and acceptable uses.

Businesses should understand whether the AI provider accepts responsibility if the agent executes an unintended transaction.

Some technology agreements may contain broad limitations of liability.

Others may place responsibility for agent configuration and output on the business using the service.

That allocation can become highly significant after a costly error.

Procurement Policies Need to Account for AI

Traditional purchasing policies are often written around employees.

They may specify which employees can approve contracts at different dollar values.

AI agents do not fit neatly into those structures.

Companies using autonomous procurement systems can update their policies to specify the tasks agents may perform.

The policy might distinguish between requesting quotes, negotiating, generating draft agreements, approving purchases, and executing contracts.

These are not the same activity.

An AI system might be permitted to negotiate without possessing final authority to bind the company.

That distinction can reduce unnecessary risk.

AI Agents Could Change Contract Negotiation

Contract negotiations may eventually become much faster.

Instead of exchanging drafts for days, two AI agents could compare standard positions and resolve routine differences in seconds.

Humans could focus only on disputed provisions.

This could reduce administrative burden for high-volume transactions.

However, faster negotiation can also reduce opportunities for reflection.

An autonomous system may agree to an unfavorable clause simply because it satisfies a broader optimization goal.

Companies should therefore determine what contractual provisions an AI agent may modify and which terms remain non-negotiable.

Businesses Should Define Non-Negotiable Terms

An agent might have flexibility regarding delivery schedules or pricing.

Other provisions may deserve stricter controls.

Examples can include intellectual property ownership, confidentiality, governing law, dispute resolution, indemnification, data rights, cybersecurity obligations, and limitations of liability.

Rather than telling an AI agent merely to “negotiate the best deal,” businesses can provide precise rules.

Greater specificity can make the system’s behavior easier to predict and later defend.

International Transactions Add Complexity

AI agents can communicate across borders almost instantly.

An American company’s agent could enter a transaction with a supplier located overseas without management realizing that foreign law may apply.

International contracts can raise questions involving governing law, jurisdiction, taxes, trade restrictions, privacy, currency, and enforceability.

Autonomy therefore increases the importance of geographic controls.

A company may permit an AI agent to transact only with approved U.S. vendors unless additional review occurs.

Without such restrictions, the system could unintentionally create international legal obligations.

Corporate Governance Also Matters

Who inside a company has authority to give an AI system contracting authority?

That question can become significant.

A technology department might install an agent capable of executing transactions.

But corporate policies may reserve contracting authority to specified officers or departments.

Giving software technical access does not necessarily resolve the underlying corporate authorization question.

Businesses should therefore coordinate AI deployment among technology, procurement, legal, finance, compliance, and leadership teams.

Agentic AI is not merely an IT tool when it can commit company funds or accept contractual obligations.

AI Agents May Create Evidence About Business Intent

AI logs could also become evidence of what a company intended.

Suppose management instructed an agent to obtain a specific service for no more than $20,000.

The AI negotiated a $19,000 contract.

Those instructions could support the argument that the company intended the agent to enter the transaction.

The reverse could also occur.

Internal records showing that the system was expressly prohibited from executing contracts could become relevant when an unauthorized agreement appears.

Businesses therefore should assume that agent instructions may later be examined in litigation.

Courts May Apply Old Rules to New Technology

U.S. contract law has repeatedly adapted to technological change.

Telephone agreements, faxed contracts, email, clickwrap agreements, electronic signatures, online marketplaces, and automated ordering systems all forced courts to apply established legal concepts to new forms of communication.

AI agents represent another stage in that evolution.

The E-SIGN Act already makes clear that the involvement of electronic agents does not, by itself, invalidate a contract.

UETA similarly reflects a longstanding policy of recognizing electronic transactions rather than treating paper as the only legitimate medium.

The unresolved questions increasingly concern autonomy, attribution, and risk allocation.

What Businesses Should Consider Before Giving AI Contracting Authority

Businesses adopting agentic AI can begin by identifying exactly what the system is permitted to do.

An agent that searches for suppliers carries less contractual risk than one authorized to sign agreements.

A system that recommends terms presents different concerns from one that accepts them automatically.

Companies can also establish financial limits, approved vendor lists, geographic restrictions, mandatory contract clauses, and human approval points.

Technical permissions should reflect corporate authority.

Security controls should prevent unauthorized manipulation.

Reliable logs should document the agent’s instructions and transactions.

Contract language with vendors and AI providers can also define responsibility if something goes wrong.

These measures become more significant as autonomous systems gain greater discretion.

Can Businesses Simply Reject Contracts Made by Their AI?

Not necessarily.

A company cannot safely assume that it may keep favorable AI-generated contracts while rejecting unfavorable agreements as unauthorized automation.

If the company deployed the system with authority to transact, existing electronic contracting law may support enforceability.

Federal law expressly protects contracts from being invalidated solely because electronic agents participated in their formation.

The result of a particular dispute could depend on the system’s authority, the parties’ communications, state contract law, the nature of any mistake, and what the counterparty reasonably understood.

The safest approach is therefore to define authority before transactions occur.

Could an AI Agent Itself Be Liable?

Current commercial practice generally treats the business or person behind the AI system as the relevant legal actor rather than treating software as an independent contracting entity.

An AI agent does not ordinarily maintain assets, satisfy judgments, or possess corporate legal status simply because it operates autonomously.

That means legal disputes tend to return to human organizations.

Potential responsibility may involve the company deploying the agent, the AI provider, a vendor, an employee who configured the system, or another party depending on the circumstances.

Contract terms can also shift financial responsibility among those parties.

Existing AI Governance Practices Are Becoming More Relevant

Businesses already using AI for contract review, legal research, and document automation face questions involving accuracy and oversight.

Legal Journal’s article How AI Is Changing the Legal Industry discusses the growing use of AI in contract review and other legal workflows.

Agentic AI moves the issue further.

Instead of helping a human decide, the system may take the action itself.

That makes governance more important because the consequences can occur before a person reviews the result.

The Future of Autonomous Contracting

AI agents could eventually become routine participants in commercial transactions.

Small businesses might use agents to purchase supplies.

Large companies could automate procurement across thousands of vendors.

Software agents could negotiate subscriptions, logistics arrangements, advertising purchases, cloud services, and other routine contracts.

The legal system does not need to invent electronic contracting from scratch to accommodate this development.

Federal and state electronic transaction frameworks already recognize automated activity.

The more difficult challenge involves determining how much independence businesses should give these systems and who bears responsibility when they exceed expectations.

Final Thoughts

AI agents can potentially participate in creating legally enforceable business contracts in the United States.

Federal electronic signature law specifically recognizes transactions involving electronic agents, provided their actions are legally attributable to the person or organization that is supposed to be bound.

That does not give AI systems unlimited contracting power.

Authority remains central.

Businesses need to determine which transactions an agent may conduct, how much it may spend, which terms it may negotiate, and when human approval is required.

They also need to consider mistakes, hallucinations, cybersecurity, confidential information, electronic signatures, consumer laws, and reliable transaction records.

As AI systems become more autonomous, the key legal question may shift away from whether a computer participated in the agreement.

The harder question is likely to be whether the business intentionally gave that computer enough authority to bind it.

For authoritative background on electronic contracting, businesses can review the Electronic Signatures in Global and National Commerce Act through Cornell Law School’s Legal Information Institute and the Uniform Electronic Transactions Act materials from the Uniform Law Commission.

This article provides general information about U.S. law and does not constitute legal advice. Contract, electronic transaction, agency, and AI rules may vary by jurisdiction and circumstances.