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Introducing AI Assistant for Akamai Web Security Analytics

September 10, 2026 by Ofir Moskovich

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Key takeaways

AI Assistant for Akamai Web Security Analytics is the first step toward a broader platform AI assistant experience, where security teams already investigate application security events and attack activity.

Investigate faster using natural language to navigate views, apply filters, understand data, and access relevant documentation using everyday prompts.

Gather proactive insights that surface prioritized remediation opportunities and guided workflows that can recommend next steps, including WAF rule tuning and custom rule creation.

Support authorized users with guided investigation and response, while ensuring that human analyst judgment, review, and activation remain essential.

Security teams do not need more noise. They need faster ways to understand what is happening, determine what matters, and take the right next step.

During an active investigation, analysts often move across dashboards, filters, event details, documentation, and remediation workflows. They need to understand what changed, which traffic patterns matter, which vulnerabilities may be involved, and what response options are available.

Although that work is important, it can also be manual and time-consuming.

That’s why we are introducing AI Assistant for Web Security Analytics, a new agent-powered experience designed to help SOC and AppSec teams investigate security events faster, understand activity in context, and move from analysis to guided response with greater confidence (Figure 1).

This first glance of AI Assistant shows everything you need to get started
Fig. 1: This first glance of AI Assistant shows everything you need to get started — by using either suggested prompts or natural language requests.

This release is also an important first step toward a broader platform AI assistant experience across the Akamai application protection platform. We are starting with Web Security Analytics because it is a natural place for investigation and response. Over time, this foundation is designed to support more of the security lifecycle, including posture management, threat discovery, investigation, and faster remediation workflows.

Moving from reactive event review to proactive investigation

Web Security Analytics gives you deep visibility into application security events, attack activity, traffic patterns, and mitigation outcomes. AI Assistant builds on that foundation by making investigation more conversational, contextual, and action-oriented.

Instead of having to manually navigate to every view, filter, and dataset, analysts can use natural language prompts to help explore what is happening in Web Security Analytics.

AI Assistant can help you:

  • Navigate views and filters using natural language prompts

  • Build or adjust Web Security Analytics views faster

  • Access context-aware, relevant product documentation

  • Understand activity trends in your current view

  • Identify notable anomalies and related Common Vulnerabilities and Exposures (CVEs)

  • Receive Akamai-recommended next steps for actionable items

The goal is not to replace human analyst judgment; it’s to reduce the manual work required to achieve the right context, focus on what matters, and move toward the right action.

Ask questions in plain language

Security investigations often start with a simple question:

What changed?

AI Assistant helps you explore that question using everyday prompts. With View Manager, you can build, edit, apply filters, and switch views without manually clicking through each control (Figure 2).

For example, an analyst can ask for help building or editing a view, then use AI Assistant to focus the investigation on the relevant traffic, time window, or attack activity.

AI Assistant provides contextual links to official technical documentation directly
Fig 2: AI Assistant provides contextual links to official technical documentation directly within the chat or by clicking the predefined prompts, helping you understand product features and behaviors without leaving your workflow.

AI Assistant also includes a documentation assistant that delivers relevant Akamai TechDocs guidance directly into your workflow. If you encounter a feature, configuration option, or unfamiliar behavior, you can get concise explanations and links to supporting documentation without leaving the investigation.

Understand security activity faster

Finding the right view is only part of the challenge. Analysts also need to understand what the data means.

Security view analyzer helps evaluate the active Web Security Analytics view, including selected filters and timeframes, and summarizes what is happening in the dataset (Figure 3).

It can help highlight:

  • Overall activity trends

  • Notable anomalies

  • Emerging threat patterns

  • CVEs associated with observed attack vectors

  • Suggested areas for deeper investigation

Security view analyzer provides you a contextual explanation
Fig. 3: Security view analyzer provides you a contextual explanation of your displayed dataset with summary, detected patterns, and further investigation directions.

This gives analysts a faster starting point for understanding contextual activity. Rather than manually reviewing every chart, filter, and data point, analysts can use AI Assistant to uncover patterns that may deserve attention.

Surface what matters and act faster

Investigation is only valuable if you can act on what you find.

AI Assistant introduces guided remediation workflows that help authorized users move from insight to action. When Akamai identifies a potential issue, AI Assistant can provide prioritized remediation opportunities — such as workflows for WAF rule tuning or custom rule creation —  and guide you through responses.

Depending on the scenario, AI Assistant can help identify the relevant security configuration, prepare the appropriate next step, or route you through the right rule-building experience for review and activation.

This helps reduce the gap between identifying suspicious activity and taking the next step to reduce risk. Security teams can spend less time sorting through noise and more time focusing on high-priority risks.

Built for enterprise security operations

AI-assisted security workflows need strong governance.

AI Assistant is designed with enterprise controls in mind, including role-based access controls, model isolation, and privacy safeguards to support responsible use in security operations. These controls help ensure that AI-assisted investigation and response workflows align with how enterprise teams manage access, review, and operational responsibility.

AI Assistant can help security teams reduce manual effort while keeping users in control of investigation and response decisions.

A foundation for broader platform AI assistance

Web Security Analytics is where many users already go to understand application security events, investigate attack activity, and validate actions across their environment. Starting here enables AI Assistant to deliver immediate value in a core, everyday workflow.

Over time, this foundation will become more agentic, moving customers from AI-assisted investigation toward proactive, guided workflows that can surface prioritized issues, recommend quick fixes, and support approved response paths across the platform.

This represents the beginning of a broader direction for the Akamai application protection platform. As the platform unifies asset visibility, posture management, protection, investigation, and optimization, customers can in turn benefit from easier ways to understand threats, prioritize critical issues, and take decisive action.

From insight to action

Security teams do not need more tools, alerts, or manual steps. They need more proactive guidance on what truly matters.

AI Assistant for Web Security Analytics helps SOC and AppSec teams move faster from event review to investigation and response. It combines natural language guidance, contextual analysis, prioritized insights, and guided remediation workflows to help you understand activity faster, reduce manual effort, and take action more confidently.

As application environments become more dynamic and attacks become more complex, AI-assisted workflows can help security teams operate with greater speed, clarity, and control.

Find out more

Learn more about AI Assistant for Web Security Analytics and in Akamai TechDocs.

About the Author(s)

Ofir Moskovich

Ofir Moskovich

Ofir Moskovich is a Senior Product Manager at Akamai who is driving innovation to make application security simpler and more accessible. He creates unified, AI-powered solutions that turn complex security data into actionable insights, helping teams prioritize threats, respond faster, and strengthen defenses. His work empowers organizations to shift from reactive incident handling to proactive protection, inspiring operations with confidence, and enabling resilience against evolving threats.

See Author bio

Tags

AI
Artificial Intelligence
Cyber Security
Security

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