Akamai launches Agentic Security Framework to secure AI agents in real-time commerce

Akamai Addresses Security Challenges Posed by AI Agents with New Framework

As AI agents increasingly handle tasks and transactions on behalf of users, businesses face mounting questions around identity, intent, and trustworthiness. Akamai (NASDAQ: AKAM) has responded by unveiling its unified agentic security framework for its Bot & Agent Control solutions, which connects identity verification, observability, trust assessment, and edge security into a single, real-time decisioning layer designed to power scalable AI-driven interactions at the edge 1

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"AI agents are replacing clicks, acting and handling commerce for us. For that to work, businesses need to recognize not just the agent, but who is behind it and what it's trying to do," said Patrick Sullivan, VP, CTO of Security Strategy at Akamai 1

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. The framework aims to give businesses confidence to open their doors to AI agents without compromising security, creating an environment where identity informs visibility, visibility drives trust, and trust powers critical business decisions.

Six Integrated Pillars Enable Trusted AI-Driven Interactions and Commerce

The Agentic Security Framework comprises six tightly integrated pillars delivered through a coordinated ecosystem of partners. At its foundation lies verified identity and human attribution, achieved through Akamai's collaboration with Visa to authenticate AI agents for secure, permissioned transactions 2

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. Integrations with frameworks like Visa's Trusted Agent Protocol help define how agents operate in payment environments, establishing clearer standards for authorization, permissions, and transaction-level trust.

Akamai is also working with Skyfire and Experian to strengthen trusted AI agent identity through the "Know Your Agent" (KYA) framework, which provides a standardized method for agents to declare identity, origin, and intent, linking them to the platforms they operate on and the users they represent 2

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. This ensures that an AI agent is not only legitimate but also verified as acting on behalf of a specific, authorized individual, providing the accountability merchants require to process automated transactions safely.

User-Centric Authentication and Adaptive Trust Analysis Secure AI Agent Interactions

To maintain security during the handoff between a human and an AI agent, Akamai integrates with identity providers such as Auth0 and Ping Identity 2

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. These integrations allow businesses to apply existing security policies, including behavioral analysis and multi-factor authentication, to the AI agents their customers use, ensuring that agent actions remain consistent with the user's established identity, behavior, and intent.

The framework enables organizations to dynamically determine the trustworthiness and intent behind every interaction across browsers, bots, and agents through adaptive trust analysis 2

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. This approach shifts beyond binary decision-making toward a spectrum of trust that puts the user at the center, allowing customers to identify which interactions support business outcomes and which introduce abuse, fraud, or operational risk.

Edge-Based Enforcement and Content Monetization Create New Business Models

Security and performance requirements for secure AI agent interactions are being met through Akamai's distributed edge network, which utilizes high-performance compute to evaluate the risk and intent of an agentic request instantly 2

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. By processing these decisions at the edge, Akamai helps businesses maintain security and control without compromising the speed of the user experience.

As AI models and agents consume more web content, the framework provides a path for fair compensation through content monetization. Through partnerships with TollBit and Skyfire, Akamai enables publishers and content owners to negotiate access and facilitate tokenized, pay-per-request models 2

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. This allows businesses to monetize their data while providing AI agents with the licensed access they need to function, addressing a critical gap as autonomous agents increasingly scrape and utilize web content.

Operational Visibility Provides Critical Intelligence for AI Agent Management

Through TrafficPeak and industry-leading web security analytics, Akamai provides organizations with a unified view of their web traffic, distinguishing between human users, beneficial AI agents, and malicious bots 2

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. These high-scale log analyses allow security and business teams to observe how agents interact with their sites over time, providing the data necessary to refine access controls and commercial strategies. The result is a scalable model where every interaction is verified, understood, and acted on in real time, helping businesses move toward a unified approach to managing bots, agents, and users 1

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