If an AI agent places a $15,000 order on behalf of a legitimate enterprise with valid credentials, how can the supplier confirm the agent has permission to make that purchase?

When AI agents execute transactions and access sensitive business systems, verifying their identity alone is insufficient. Know Your Agent (KYA) helps establish who authorized these agents and what actions they are permitted to perform.

The same concern extends to the businesses these agents represent. Agentic Know Your Business (KYB) can help connect AI-driven interactions to verified business identities and organizational authority, adding another layer of trust to autonomous transactions.

How Does KYA Connect to Agentic KYB?

Know Your Agent (KYA) verifies an AI agent's identity, figures out who authorized it, and determines what actions it can perform. It links an agent's credentials to a verified individual or business and establishes the authority granted to the agent.

Traditional KYB checks establish whether a company is legitimate, who owns or controls it, and its associated risks. 

The connection between KYA and agentic KYB becomes clearer across three areas:

• KYA establishes agent-level trust: Verifies the agent's identity, credentials, responsible principal, and scope of permission.

• Agentic KYB strengthens business verification: Uses AI agents to research business identities, ownership structures, and risk indicators, with evidence-backed findings supporting human review.

Together, they support trustworthy agent-driven workflows, where verified business information establishes the legitimacy of the organization, while KYA controls determine whether an agent is authorized to act on its behalf.

Related Read: Agentic KYB: How AI Agents Are Changing Business Verification

Core Capabilities of Know Your Agent

KYA requires controls that identify who is responsible for an agent, define what it can do, and monitor whether its actions remain authorized. Its six core capabilities include:

1. Agent identity verification: Assigns and authenticates a unique digital identity to distinguish an agent from other users and systems.

2. Principal identification: Links the agent to the human or business responsible for its actions.

3. Delegated authority validation: Confirms that the agent has received authorization from the appropriate principal.

4. Permission and scope enforcement: Restricts the systems, data, and transactions the agent is allowed to access or modify.

5. Execution-time validation: Checks whether individual actions fall within approved permissions before they are executed.

6. Accountability and auditability: Records agent activity, authorization decisions, and responsible parties to support investigations and compliance reviews.

According to McKinsey's 2026 State of AI report, 40% of respondents from organizations with more than $1 billion in annual revenue reported scaling AI agents. This growing adoption makes verifying agent identities, enforcing permissions, and maintaining accountability increasingly important.

How Does Know Your Agent Work?

The KYA process involves verifying the person or business behind an AI agent, authenticating its credentials, and checking its permissions before approving specific actions. Ongoing monitoring helps detect misuse and maintain accountability.

Here is how the five-step process works.

1. Verify the Human or Business Behind the Agent

The first step is identifying the agent's principal, whether an individual, employee, or registered business.

For individual users, Know Your Customer (KYC) and Identity Verification (IDV) establish the person's identity. Business-operated agents require additional business verification checks to confirm the company's registration, ownership, and relevant authorized representatives.

For example, when an AI procurement agent claims to represent an enterprise, the receiving platform verifies the organization and identifies the representative responsible for delegating authority. An employee's association with the company alone does not prove that they are authorized to approve purchases or appoint purchasing agents.

2. Establish and Authenticate the Agent's Identity

Once the principal is verified, the agent needs a unique identifier and valid credentials to authenticate its requests. These may include cryptographic keys, digital certificates, or signed tokens. OAuth 2.0 supports delegated access, while JSON Web Tokens (JWTs) can carry identity and authorization claims.

When an agent connects to external systems through the Model Context Protocol (MCP), the receiving service validates the applicable credentials, including their expiration and intended audience.

However, successful authentication does not automatically grant permission to perform every action.

3. Validate Delegated Authority and Permissions

The next step is checking whether the verified principal has explicitly authorized the agent to perform its assigned tasks.

Organizations establish the scope of permission through defined authorization policies, including:

• Approved systems: Applications, Application Programming Interfaces (APIs), or databases the agent can access.

• Permitted actions: Tasks such as retrieving invoices, approving purchases, or updating records.

• Transaction limits: Maximum spending amounts or permitted transaction categories.

• Access duration: When the authorization begins, expires, or requires renewal.

• Restricted operations: Actions requiring separate approval, such as changing bank details or initiating fund transfers.

Consider a purchasing agent authorized to approve software subscriptions up to $500. Its delegation does not cover a $5,000 transfer or changes to the company's bank account information, even when the request originates from the same authenticated agent.

4. Verify Authorization at the Point of Action

An agent's permissions must also be checked when it attempts to execute a transaction. This is known as execution-time validation.

Authentication identifies the agent making a request, while authorization determines whether that agent is permitted to perform the requested action.

For a payment request, the system checks the agent's active credentials, the validity of its delegation, the transaction amount, and any applicable restrictions before deciding whether to proceed.

The outcome depends on the authorization policy:

• Approve: The request meets all applicable permissions and transaction limits.

• Reject: The request violates a restriction or the agent lacks valid authorization.

• Escalate: The transaction exceeds an approval threshold and requires confirmation from an authorized human.

This prevents an agent from relying on previously granted access to perform actions outside its current authority.

5. Monitor Agent Activity and Maintain Audit Trails

Agent activity needs ongoing monitoring, even after successful authentication and authorization. Organizations track transaction histories, permission violations, and unusual behavior to identify potential misuse.

For instance, if an agent authorized to retrieve invoices suddenly attempts multiple fund transfers, monitoring can flag the activity for investigation. Historical behavior may also inform an agent's reputation and future risk assessments.

Depending on the findings, organizations can suspend the agent or revoke its credentials and permissions. Meanwhile, audit trails preserve records of its actions, authorization decisions, and responsible principal, supporting investigations and compliance reviews.

How Does KYA Relate to KYC and IDV?

KYA builds on traditional identity verification by establishing trust before allowing someone or something to act. However, AI agents introduce an additional layer of verification because they operate on behalf of individuals or businesses rather than acting as customers themselves.

While KYC focuses on customer identity and risk, and IDV confirms whether identity claims are genuine, KYA extends identity assurance to autonomous agents and their delegated authority.

Here's how the three differ:

How they work together: Consider a banking customer who authorizes an AI assistant to manage account-related tasks. IDV helps confirm the customer's identity, KYC establishes the customer's identity and risk profile, and KYA connects the agent to that verified customer and their approved permissions.

The same principle applies to enterprise agents, where business verification establishes the organization's legitimacy before agent-level authorization controls come into play.

Related Read: How to Verify Digital Identities Without Slowing Onboarding

Where Know Your Agent Is Used: Use Cases and Examples

Know Your Agent applies wherever AI agents interact with financial systems, enterprise applications, third-party platforms, or sensitive information. The checks required depend on what the agent does, which systems it accesses, and the risks involved.

Here are some common use cases where KYA helps organizations verify and control AI agent activities:

• Agentic Commerce and Autonomous Payments: AI agents can place orders, manage vendor payments, and execute purchases on behalf of individuals or businesses. KYA enables merchants and payment platforms to check whether these transactions fall within the agent's delegated authority. For enterprise transactions, agentic KYB provides additional context about the business behind the interaction.

Example: A purchasing agent books business travel through an external platform. The platform checks whether the agent is authorized to use the company's payment method and whether the booking falls within its approved spending policy.

• Enterprise AI Agents and Internal Workflows: Businesses increasingly use AI agents to automate operational tasks across finance, procurement, and customer service. KYA connects these agents to accountable employees or departments and governs their access to internal systems.

Example: An HR agent can retrieve employee leave balances and process routine leave requests. However, changes to payroll information or employment records require separate authorization from the relevant HR personnel.

• Third-Party Agents and API Access: External AI agents often interact with enterprise applications through APIs or protocols such as MCP. Organizations need to determine which external agents can access their services and whether their requests fall within approved access permissions.

Example: A third-party logistics agent connects to a retailer's order management system to retrieve shipment statuses and update delivery estimates. However, it cannot cancel orders, issue refunds, or modify customer payment information without additional authorization.

• AI Agents Accessing Sensitive Customer Information: Agents handling banking records, healthcare information, or other regulated data require stricter access controls. KYA supports restrictions based on the responsible principal, the agent's assigned purpose, and the sensitivity of the requested information.

Example: A healthcare scheduling agent can check appointment availability and confirm bookings using permitted patient information. But accessing medical histories or sharing clinical records remains restricted unless the appropriate permissions and authorizations are in place.

Juniper Research projects that global agentic commerce spending will reach $1.5 trillion by 2030, while also identifying trust as the leading barrier to adoption. This makes reliable agent verification and transaction authorization important for merchants and payment platforms.

What Are the Main Challenges of Implementing KYA?

Implementing KYA becomes more complicated when AI agents operate across multiple systems, interact with external platforms, or act on behalf of different users. Organizations face several practical challenges in establishing and maintaining trust across these interactions, such as:

• Fragmented identity and business data: Agent credentials, human identities, and business verification records often reside in separate systems, making it difficult to connect an agent to its legitimate principal.

• Unclear delegated authority: Establishing who has permission to authorize an agent becomes difficult when multiple employees, departments, or third parties are involved.

• Changing permissions and agent behavior: An agent's responsibilities and access privileges can change over time. Outdated permissions may allow actions beyond its current role.

• Limited visibility and accountability: Disconnected authentication and transaction records make it harder to trace suspicious activities, investigate unauthorized actions, and establish responsibility.

• Evolving standards and compliance expectations: KYA lacks a universally adopted implementation standard. Organizations must navigate applicable identity, financial crime, and AI governance requirements while agent-specific frameworks continue to develop.

These governance gaps carry operational consequences. Gartner predicts that by 2027, 40% of enterprises will demote or decommission autonomous AI agents because of governance failures identified after production incidents. This highlights the importance of defining appropriate permissions and oversight before agents are deployed.

Even an authenticated agent can be compromised through stolen credentials, prompt injection, or malicious instructions that influence a jailbroken model. KYA therefore needs complementary security controls to address threats beyond identity and authorization.

How Bureau Builds Trust in Agentic Business Workflows

Bureau helps organizations build a stronger foundation for agent-driven business transactions by bringing business verification, identity intelligence, and risk assessment into connected workflows.

Whether an AI agent is interacting with a financial platform or acting on behalf of an enterprise, these capabilities help organizations assess the business behind the interaction and its associated risks.

Bureau supports this through three key capabilities:

• Establishing business legitimacy: Bureau's KYB Risk Engine helps verify company registration, beneficial ownership, and associated risk indicators. This gives organizations a reliable business identity foundation when dealing with agents representing enterprises.

• Connecting identity and risk signals: Its Unified Risk Decisioning Platform brings together identity, device, behavioral, and transaction intelligence to identify suspicious patterns and support informed risk decisions.

• Adapting verification to different risks: Configurable workflows, no-code rules, and risk thresholds allow organizations to adjust verification requirements based on the nature and risk of each interaction.

Bureau is also extending its business verification approach through agentic KYB, where AI agents research company information, investigate ownership structures, and consolidate evidence-backed findings for human review. This reduces repetitive research, gives verification teams clearer information for assessing business legitimacy, and reduces the time needed for verification.

Together, these capabilities strengthen the business identity and risk assessment foundation needed for agent-driven transactions, while agent-specific authorization and permission enforcement remain separate requirements.

Building Trust in an Agent-Driven Economy

KYA builds trust in AI agents by verifying their identity, responsible principal, and delegated authority, working alongside existing identity verification and KYB processes. Meanwhile, agentic KYB is making business verification more efficient through AI-assisted research and evidence-backed assessments.

Bureau brings together verified business information, identity intelligence, and risk signals to help organizationsassess risks and establish trust in agent-driven business interactions.

To see how Bureau's business verification and unified risk decisioning capabilities can strengthen business verification, improve risk visibility, and build greater confidence in agent-driven transactions, schedule a demo today.

FAQs

1. What is Know Your Agent (KYA) in AI?

Know Your Agent (KYA) is an emerging verification approach that establishes an AI agent's identity, identifies the individual or organization responsible for it, and validates its delegated authority. It helps organizations determine whether autonomous agents are permitted to access systems or execute transactions.

2. How is Know Your Agent different from KYC?

KYC verifies a customer's identity and assesses associated risks, while KYA focuses on AI agents acting on behalf of individuals or businesses. KYA builds on verified identities by checking agent credentials, delegated permissions, and authorization for specific activities.

3. How can businesses verify an AI agent's identity?

Businesses can authenticate AI agents using unique identifiers, cryptographic credentials, digital certificates, or signed tokens. They must also verify the responsible principal and validate delegated permissions before allowing the agent to access sensitive systems or perform transactions.

4. How is Know Your Agent used in agentic banking?

In agentic banking, KYA helps financial institutions identify AI agents acting on behalf of customers or businesses and validate their transaction permissions. It supports controlled access to financial services, authorization checks for payments, and accountability for autonomous banking activities.

5. What is the difference between KYA and agentic KYB?

KYA verifies an AI agent's identity and delegated authority. Agentic KYB uses autonomous AI agents to research and verify businesses, including ownership structures and risk indicators. The two address different trust requirements across AI-driven business interactions.

6. Can a verified AI agent still pose a security risk?

Yes. Even verified AI agents can be compromised through stolen credentials, prompt injection, or excessive permissions. Organizations need continuous activity monitoring, execution-time authorization checks, and appropriate security controls to detect suspicious behavior and prevent unauthorized actions.