Webinar Description
Key Takeaways
- Explores the security challenges of deploying AI features and models on AWS
- Highlights the limitations of traditional WAFs in detecting AI-generated threats
- Introduces behavioral detection and machine learning-driven security models
- Provides frameworks for evaluating and adapting runtime security tools for AI environments
- Focuses on practical steps to enhance protection for AI-powered systems
As organizations accelerate the deployment of AI models and features in production, the security landscape is shifting rapidly. The webinar “Runtime AI Governance on AWS: Close the Gap Between Deployment and Control” addresses the operational and strategic challenges that arise when traditional security tools struggle to keep pace with AI-driven traffic and threats.
Why AI Governance Matters Now
AI adoption is transforming how businesses operate, but it also introduces new risks. Security teams are finding that legacy Web Application Firewalls, built to recognize known attack signatures, are increasingly ineffective against the unpredictable behaviors of AI-generated traffic. This gap in protection leaves organizations exposed at a time when AI-powered applications are becoming mission-critical.
Rethinking Runtime Security for AI Environments
The session delves into the shortcomings of signature-based security and why these approaches fall short in AI-first environments. Instead, the discussion pivots to behavioral detection and positive security models—methods that leverage machine learning to identify anomalies and threats that evade traditional defenses. These models offer a more adaptive and resilient approach to runtime security, especially for organizations operating on AWS.
Practical Frameworks and Actionable Guidance
Attendees are provided with practical frameworks for evaluating their current runtime security tools. The session outlines concrete steps for adapting existing security postures to better protect AI-powered systems, emphasizing the need for visibility and control over AI-driven API traffic. The content is tailored for security architects, engineers, DevOps teams, and technical leaders responsible for safeguarding AI deployments in the cloud.
Industry Context and Emerging Trends
With the rapid integration of AI into enterprise workflows, the market is witnessing a shift toward more dynamic and intelligent security solutions. The event situates itself at the intersection of application security, AI governance, and cloud infrastructure, offering insights that are both timely and relevant for organizations navigating these changes. The focus on AWS reflects the platform’s central role in modern AI deployments, while the emphasis on behavioral and ML-driven security models signals a broader industry movement beyond rules-based protection.
Who Should Attend
This webinar is designed for security professionals, DevOps and cloud infrastructure teams, product managers, and senior IT decision-makers. It is particularly relevant for organizations deploying AI on AWS and seeking to bridge the gap between rapid innovation and robust security governance.
Event Format and Experience
The event is delivered as a virtual webinar, combining educational content with technical and executive-level insights. All registrants receive access to a recording, ensuring the material remains accessible for ongoing reference and team enablement.
Positioning and Industry Leadership
Hosted by Wallarm, with a focus on AWS environments, the session positions itself as a thought leadership platform for AI security. The messaging centers on closing the gap between deployment and control, moving beyond rules-based protection, and providing actionable next steps for organizations facing the realities of AI-driven threats.