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[1]
Akamai Unveils Agentic Security Framework to Power Trusted AI-Driven Interactions and Commerce
As AI agents increasingly act on behalf of users, every request raises critical questions of identity, intent, and trust. To address this, Akamai (NASDAQ: AKAM) today announced its unified agentic framework for its Bot & Agent Control solutions, which connects identity, observability, trust, and edge security into a single, real-time decisioning layer to power scalable AI-driven interactions at the edge. Six tightly integrated pillars form the framework, which are delivered through a coordinated ecosystem of partners: "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, Akamai. "We've built this so that identity informs visibility, visibility drives trust, and trust powers the decisions that let companies safely grow and monetize these new AI interactions. We're giving businesses the confidence to open their doors to AI without compromising security." Across its ecosystem, Akamai is helping businesses move toward a unified approach to managing bots, agents, and users. The result is a scalable model where every interaction is verified, understood, and acted on in real time.
[2]
Akamai Unveils Agentic Security Framework to Power Trusted AI-Driven Interactions and Commerce
Akamai announced its unified agentic framework for its Bot & Agent Control solutions, which connects identity, observability, trust, and edge security into a single, real-time decisioning layer to power scalable AI-driven interactions at the edge. Six tightly integrated pillars form the framework, which are delivered through a coordinated ecosystem of partners. Verified identity and human attribution: Through its collaboration with Visa, Akamai is establishing a trusted foundation by authenticating AI agents for secure, permissioned transactions. Integrations with frameworks like Visa?s Trusted Agent Protocol are helping define how agents operate in payment environments, setting clearer standards for authorization, permissions, and transaction-level trust. Akamai is also collaborating with Skyfire and Experian to strengthen trusted AI agent identity through the ?Know Your Agent? (KYA) framework, which provides a standardized way for agents to declare identity, origin, and intent, linking them to the platforms they operate on and the users they represent. KYA can help ensure that an AI agent is not only legitimate but is also verified as acting on behalf of a specific, authorized individual. This provides the accountability required for merchants to process automated transactions safely. User-centric authentication: To maintain security during the handoff between a human and an AI agent, Akamai integrates with identity providers such as Auth0 and Ping Identity. These integrations allow businesses to apply existing security policies, such as behavioral analysis and multi-factor authentication, to the AI agents their customers use. This ensures that the agent?s actions remain consistent with the user?s established identity, behavior, and intent. Adaptive trust analysis: The framework enables organizations to dynamically determine the trustworthiness and intent behind every interaction across browsers, bots, and agents. This 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: Security and performance requirements for AI interactions are being met through Akamai?s distributed edge network. By utilizing high-performance compute, Akamai can evaluate the risk and intent of an agentic request instantly. Processing these decisions at the edge, Akamai helps businesses maintain security and control without compromising the speed of the user experience. Content monetization and value exchange: As AI models and agents consume more web content, the framework provides a path for fair compensation. Through partnerships with TollBit and Skyfire, Akamai enables publishers and content owners to negotiate access and facilitate tokenized, pay-per-request models. This allows businesses to monetize their data while providing AI agents with the licensed access they need to function. Operational visibility and traffic analysis: Through TrafficPeak and our 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. 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. Across its ecosystem, Akamai is helping businesses move toward a unified approach to managing bots, agents, and users. The result is a scalable model where every interaction is verified, understood, and acted on in real time.
[3]
Akamai Launches Framework to Secure AI Agent Interactions
Akamai Technologies, Inc. is the world's No. 1 supplier of Internet applications and content distribution acceleration services. The activity is organized primarily around 3 areas: - content distribution: transmission, storage, and management of data flows, media content, electronic applications, etc.; - development of applications on Internet sites: applications for recording user visits to sites, research, etc.; - other: data management, distribution control, application performance measurement, secure content transmission, etc. The United States account for 50.2% of net sales.
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Akamai unveiled its unified agentic security framework for Bot & Agent Control solutions, addressing identity, trust, and security challenges as AI agents increasingly handle transactions on behalf of users. The framework integrates six pillars including identity verification through partnerships with Visa, Skyfire, and Experian, enabling businesses to verify, understand, and act on every AI-driven interaction in real time at the edge.
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
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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
. 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.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
. 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
. 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.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
. 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
. 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.Related Stories
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
. 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
. 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.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
. 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 users1
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