In Depth
Cisco, a networking and security company, treats AI risk mainly as a security problem. Its work in the area (including capabilities it markets as AI Defense, built partly on its acquisition of Robust Intelligence) centers on protecting AI applications in production: validating models against a library of known failure modes and attacks, applying guardrails to inputs and outputs, and monitoring agents at runtime for prompt injection, jailbreaks, and data leakage.
That framing complements governance-first frameworks rather than competing with them. Where the NIST AI RMF organizes how you manage risk and the OWASP Top 10 for LLM Applications lists what to defend against, a security-vendor approach like Cisco's focuses on the operational defenses: testing models before deployment and enforcing controls while they run. It sits closer to AI runtime governance than to policy.
For AI vendors, enterprise security teams, often the same teams that run Cisco gear, increasingly expect AI applications to carry real security controls rather than documentation alone. Knowing the categories these frameworks test, adversarial robustness, injection resistance, data-leak prevention, tells a vendor what its own agent will be measured against.
What It Looks Like
A vendor's agent is being deployed inside an enterprise whose security team runs AI applications through an automated validation and runtime-protection layer of the kind Cisco offers. The layer probes the agent with adversarial inputs, checks how it handles injection and jailbreak attempts, and enforces guardrails on its traffic in production. An agent that was red-teamed against these same attacks before shipping passes cleanly. One that was only reviewed on paper gets flagged.
Why It Matters For AI Vendors
Security-led buyers judge an agent by how it holds up under attack. Documentation counts for less. A framework like Cisco's will test for adversarial robustness, injection, and leakage, so a vendor does well to build and red-team against those threats early. The failures such tools catch, an agent that can be jailbroken or made to leak data, are also the ones most likely to become claims, so hardening against them supports the sale and reduces the risk.