Akamai announced a unified agentic security framework on June 15, 2026, designed to enable AI agents to safely participate in digital commerce by connecting identity verification, trust analysis, and edge security into a single real-time decision layer. The framework addresses a fundamental challenge: as AI agents increasingly act on behalf of users in financial and commercial transactions, businesses and consumers need assurance that these agents are legitimate, authorized, and trustworthy.

Why Do AI Agents Need Their Own Security Framework?

Unlike traditional chatbots or customer service tools, AI agents are designed to take autonomous action on a user's behalf, including making purchases, processing payments, and accessing sensitive systems. This autonomy creates new security risks that existing identity and access controls were never designed to handle. The problem is straightforward: how can a merchant know that an AI agent requesting a transaction is genuinely authorized by the person it claims to represent, and not a fraudulent imposter or compromised system ?

Akamai's framework tackles this by introducing what the company calls the "Know Your Agent" (KYA) protocol, developed in collaboration with Skyfire and Experian. This protocol provides a standardized way for AI agents to declare their identity, origin, and intent, linking them directly to the platforms they operate on and the specific users they represent. The goal is to ensure that an AI agent is not only legitimate but also verified as acting on behalf of an authorized individual.

What Are the Six Pillars of Akamai's Agentic Security Framework?

The framework rests on six interconnected security and trust components, each designed to address a different aspect of agentic commerce:

• Verified Identity and Human Attribution: Through partnerships with Visa, Skyfire, and Experian, the framework authenticates AI agents for secure, permissioned transactions and establishes clear standards for authorization, permissions, and transaction-level trust.
• User-Centric Authentication: Integrations with identity providers like Auth0 and Ping Identity allow businesses to apply existing security policies, such as behavioral analysis and multi-factor authentication, to the AI agents their customers use.
• Adaptive Trust Analysis: The framework enables organizations to dynamically determine the trustworthiness and risk profile of each agentic transaction in real time.
• Edge-Based Enforcement: Security decisions are made and enforced at the network edge, protecting performance while validating every automated request.
• Content Monetization and Value Exchange: The framework allows organizations to distinguish, manage, and monetize agentic traffic separately from human traffic.
• Operational Visibility and Traffic Analysis: Enhanced visibility helps organizations understand and track agentic interactions across their systems.

This multi-layered approach reflects a broader industry recognition that AI agents cannot simply be treated as extensions of existing user accounts. They require their own identity layer, their own trust evaluation, and their own governance mechanisms.

How Can Businesses Implement Agentic Security Today?

Akamai's framework is delivered through a coordinated ecosystem of partners, meaning organizations don't need to build these capabilities from scratch. Here are the practical steps businesses can take to secure AI agent interactions:

• Establish Agent Identity Verification: Work with identity partners to implement the Know Your Agent protocol, ensuring every AI agent operating on your platform can prove its legitimacy and authorization status.
• Integrate Existing Identity Controls: Connect your current identity and access management systems (such as Auth0 or Ping Identity) to apply behavioral analysis, multi-factor authentication, and session-based trust to AI agent interactions.
• Deploy Real-Time Trust Decisioning: Implement edge-based enforcement that evaluates the trustworthiness of each agentic transaction as it occurs, rather than relying on static rules or post-transaction audits.
• Monitor and Monetize Agentic Traffic: Use operational visibility tools to distinguish agentic traffic from human traffic, track agent behavior, and potentially create new revenue streams through agent-specific services or premium access.

What Do Industry Leaders Say About Agentic Commerce Trust?

The framework has attracted support from major financial and identity companies, each bringing their own expertise to the problem. Visa, for example, is establishing what it calls the "Trusted Agent Protocol," which defines how agents are authenticated, authorized, and trusted at the transaction level.

"Without trusted identity and explicit permissioning, AI agents cannot participate in commerce at scale," said Rubail Birwadker, Senior Vice President and Head of Growth Products and Partnerships at Visa. "Visa's Trusted Agent Protocol provides the identity layer that defines how agents are authenticated, authorized, and trusted at the transaction level so businesses and consumers can transact with confidence."

Rubail Birwadker, Senior Vice President and Head of Growth Products and Partnerships, Visa

Experian, which specializes in identity verification and risk assessment, is contributing what it calls the "Experian Agent Trust framework," designed to bring transparency and accountability to AI-driven interactions by verifying identities, assessing risk, and strengthening confidence in every transaction.

"AI agents are quickly becoming part of digital commerce, but trust will determine how far and how fast adoption grows," explained Kathleen Peters, Chief Innovation Officer at Experian. "With the Experian Agent Trust framework, we are helping businesses bring more transparency and accountability to AI-driven interactions by verifying identities, assessing risk, and strengthening confidence in every transaction."

Kathleen Peters, Chief Innovation Officer, Experian

Skyfire, a fintech company focused on enabling agents to access global payment rails, emphasized that the trust layer must be built into the infrastructure itself, not bolted on afterward.

"AI agents can't participate in the economy without trusted identity and the ability to transact," stated Amir Sarhangi, Co-Founder and Chief Executive Officer of Skyfire. "Skyfire provides that foundation, enabling agents to authenticate, operate within policy, and access global payment rails. With Akamai, we're bringing that trust layer to the edge, so enterprises can securely enable trusted agents without re-architecting their existing systems."

Amir Sarhangi, Co-Founder and Chief Executive Officer, Skyfire

Why Does This Matter Now?

The timing of Akamai's announcement reflects a critical inflection point in AI adoption. As large language models (LLMs), which are AI systems trained on vast amounts of text data to understand and generate human language, become more capable and more widely deployed, the use cases for autonomous AI agents are expanding rapidly. Agents can now handle complex, multi-step tasks like booking travel, managing expenses, or processing orders without human intervention at each step.

However, this autonomy creates liability and security challenges that have no precedent in digital commerce. If an AI agent makes an unauthorized transaction, who is responsible? If an agent's identity is spoofed or compromised, how quickly can the fraud be detected and reversed? These questions cannot be answered without a standardized framework for agent identity and trust, which is precisely what Akamai and its partners are now providing.

The framework also reflects a broader shift in how companies think about AI security. Rather than treating AI as a tool that humans control, the industry is increasingly recognizing that AI agents will operate with genuine autonomy, making decisions and taking actions in real time. This requires security architectures that can evaluate trust and enforce policies at machine speed, at the edge of the network, rather than relying on human review or centralized approval processes.