Development teams have executive mandates to ship AI features without friction. Security teams lack the organizational support to push back. Leadership understands the security debt is mounting (see: fafoframework.com) but prioritizes competitive pressure over future incidents.

This calculation is rational only if the actual risk is understood. Most organizations are operating with incomplete information.

1. Existing security frameworks don’t apply to AI agents

AppSec and ProdSec frameworks were built for deterministic applications with predictable behavior. AI agents make independent decisions, access data dynamically, and generate outputs based on context.

OWASP released an LLM Top 10, but adoption is minimal. Existing risk frameworks and compliance standards weren’t designed for autonomous entities. Security teams lack the frameworks to evaluate agent behavior at the decision-making level.

2. AI agent incident blast radius is fundamentally different

Traditional applications operate within fixed boundaries. AI agents are given problem-solving directives and autonomous access to tools and resources.

While some security models align, the attack vectors differ fundamentally. The vulnerability is at the reasoning layer where agents interpret instructions, combine context, and make autonomous decisions.

Traditional breaches expose static data. AI agent incidents expose proprietary IP embedded in training data, enable customer-facing system manipulation through prompt injection, and create liability across customer interactions through behavior manipulation.

Compliance frameworks (SOC 2, PCI DSS, HIPAA) have no provisions for autonomous systems, while emerging regulations (GDPR, AI Act) have uncertain enforcement standards.

3. Solving this requires refusing the velocity vs. safety trade-off

Most security approaches force organizations to choose between shipping fast and operating safely. AI security requires both simultaneously: visibility into agent reasoning for security teams, frictionless implementation for development teams, and retroactive solutions that address accumulated debt without requiring rewrites.

The organizations that solve AI security will be the ones that refuse to choose between velocity and safety.