Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI agents aren’t just talking, they’re taking actions. They’re booking transactions, pulling sensitive data, and chaining tools together to get work done. As enterprises embrace these agents, protocols like the Model Context Protocol (MCP) and Agent-to-Agent (A2A) are enabling powerful new capabilities, but also creating invisible ecosystems of API-driven agent activity that traditional security tools can’t see or control.

For most leadership teams, the question is no longer if they’ll use AI, but how to turn it into measurable business value. Success hinges on the APIs that feed, govern, and scale AI initiatives — and whether your strategy is built for speed, security, and cost efficiency. From accelerating product development to delivering real-time customer experiences, the business case for AI is clear. But without the right API strategy, AI initiatives risk falling short — driving up costs, creating compliance gaps, and limiting ROI.

APIs, AI, and the Amplification of Security Risk A10 Networks experts Jamison Utter and Carlo Alpuerto discuss how the rise of Agentic AI is dramatically scaling up existing API security problems, creating an "amplification effect" rather than introducing fundamentally new security challenges.

Prioritizing Risk: Why Context is King in API Security A10 Networks security experts Jamison Utter and Carlo Alpuerto discuss a fundamental shift in how security teams should view vulnerabilities and risks, especially in the context of API security.

When data flows between two critical SaaS tools (like Salesforce and a CRM chatbot), you have zero visibility into that traffic. This leaves a gaping hole for attackers to exploit Business Logic Abuse. Since you can't see the traffic, you cannot monitor the attack. The Solution? Rigorous Vendor Management. Control Your Own Keys! The responsibility to protect your sensitive data is always yours, even in the cloud.