As autonomous agents begin making decisions and moving data independently, Cisco, Google, Microsoft and IBM are reengineering enterprise security with AI.
Agentic AI is no longer confined to pioneering companies. These systems now operate across enterprise environments, accessing resources, making decisions and taking action with minimal human oversight. But with this autonomy comes a new class of risk. Security frameworks built for predictable, human-centric workflows are ill-equipped to handle agents that operate at machine speed, modify APIs and move sensitive data independently.“Every new AI agent is both an asset and a new risk.
Likewise, cloud networking and security company Cisco is embedding security deeper into the network, down to the silicon layer. The company recently introduced its AgenticOps strategy, which combines real-time observability, zero-trust frameworks and AI-native operations into a single enterprise architecture.
The company has also introduced a Universal Zero Trust Network Access framework that extends identity-based controls to include delegated authorization, which lets users securely grant access to trusted service providers without sharing their credentials; proximity-based phishing resistance, which verifies that a request is coming from a nearby, trusted device; and support for the emerging Model Context Protocol , a new standard that allows AI systems to securely share context across different...
Building on this vision, Cisco is deepening its integrations following the acquisition of Splunk. Telemetry from Cisco firewalls now feeds directly into Splunk’s security platform, enabling automated response playbooks and correlating threat signals across the agentic application stack.The organizations that will thrive in this new era are those that embrace a simple truth: if AI is the engine of enterprise innovation, AI-powered security must be its steering system.
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