AWS and Cisco tackle three security problems that hit AI agents at scale

AWS and Cisco have announced a strategic partnership to secure AI agents as they are rolled out en masse in corporate environments. The joint solution aims to overcome three critical problems that slow scaling: a lack of visibility into agent actions, security bottlenecks and growing regulatory compliance requirements. The initiative shows how the tech giants approach risk management when adopting AI at enterprise level, and what tools they are preparing for mass agent adoption.

Three problems when scaling AI agents

When companies move from one or two experimental AI agents to dozens or hundreds running at once, complexity jumps sharply. The architecture has to change radically, but many enterprises run into hidden obstacles that freeze deployment.

The first problem is the lack of full visibility. Engineers and risk managers do not know in real time what each agent is doing, which systems it accesses, what data it processes or what decisions it makes. If an agent makes a mistake or heads in a dangerous direction, the system may not notice. This is especially critical in regulated industries, where every action must be documented and explained.

The second problem is security bottlenecks. Manually reviewing every new agent, every update and every call to external systems and APIs simply does not scale. A company can have people check 10 agents, but what about 100 or 1000? Manual work becomes a barrier to growth.

The third problem is compliance. Regulators demand ever more documentation, regular audits and proof that a system operates within established rules. This is especially acute in finance, healthcare and the public sector, where a compliance error can cost millions.

• Visibility: complete loss of control over agent actions in real time
• Security: manual review becomes a serious bottleneck at scale
• Compliance: growing requirements for auditing, documentation and proof of compliance

How AWS and Cisco address the problem

AWS and Cisco have proposed a two-tier approach that combines automation with governance.

First, automated scanning of every agent before deployment. The system checks source code, required permissions, access to external APIs and potential vulnerabilities, all without human involvement. It resembles automated security testing, but works in real time.

Second, a unified management system that gives engineers a single window for monitoring all agents at once. What permissions does each agent have? Which systems does it access? What errors occur? Which unauthorized access attempts were intercepted? All of this information is available from one control panel, with no need to switch between different tools.

The solution integrates AWS tools (Lambda, IAM, CloudWatch) with the Cisco AI Defense platform, which specializes in security validation of AI systems. Cisco brought deep experience in network security: automated threat detection, fast incident response and minimizing false positives. The result: a company can deploy hundreds of agents without increasing the number of security engineers.

What changes in scaling practice

Companies actively adopting AI agents now face a painful choice: slow deployment and check everything manually for the sake of security, or speed up and risk breaching security and compliance. The AWS and Cisco partnership offers a third path: scaling without compromising security.

This shows where the industry as a whole is heading. Security can no longer be bolted on after the fact; it has to be built into the process from the very start of development and testing. AWS and Cisco show that scaling AI agents requires not just powerful cloud infrastructure, but also reliable tools for automated control, monitoring and fast response to potential threats and incidents.