A new form of tool sprawl is emerging in cybersecurity operations as AI agents proliferate across security teams, creating a looming coordination problem that could turn incident response into chaos, according to Netskope CISO James Robinson in a recent interview with CRN. The challenge centers on what Robinson calls "agent sprawl"—an overabundance of agentic systems authorized to assist security analysts with tasks and investigations. As Security Operations Center (SOC) analysts increasingly run multiple agents simultaneously, the risk grows that numerous AI agents will all attempt to handle the same security incident at once, generating overlapping and competing actions that confuse rather than help.
The collision scenario Robinson describes is straightforward but messy: when an employee reports a potential phishing email, six different agents could reach out to the analyst simultaneously to offer assistance, creating what he characterizes as a "really, really messy and confusing" situation. This concern has already surfaced among security leaders making deployment decisions about agentic AI, with discussions focusing on whether to specifically program AI agents to watch for other agents. Security teams may need to adopt a collision detection approach—similar to protocols used in early Ethernet networking—for agent-generated messages and actions, allowing one agent to recognize that another has already claimed an incident, requested evidence, or begun a response.
Fortunately, many organizations won't need to invent entirely new operating models, according to Harpreet Sidhu, global cybersecurity lead at Accenture. SOC teams already encounter overlap when multiple people start working on a single case, and the existing control plane that oversees human-led processes can govern agent-driven processes as well, he explained. Governance structures already exist to break ties on investigative findings and determine who gets primacy on actions going forward. Meanwhile, Khiro Mishra, founder and CEO of Dallas-based solution provider Shieldient, has prioritized avoiding overlapping agents while building an agentic framework for security services by narrowing each agent's scope—creating smaller agents with tightly defined roles rather than assigning alerting, triage, detection, investigation, and threat hunting to a single broad SOC agent.
The underlying problem is that without coordination mechanisms, automatic processing and responding by multiple agents simultaneously will produce what Robinson warns could be "very ugly" outcomes. Organizations that learn from existing human-driven SOC models stand the best chance of managing the transition smoothly, applying governance frameworks already proven effective at deconflicting human analysts to the new challenge of managing autonomous systems. The granular approach—defining agent functions as narrowly as possible to prevent overlap—offers one immediate path forward for security teams navigating this emerging complexity. For enterprise security leaders, the collision risk underscores a broader strategic tension between automation velocity and operational coherence, forcing choices about whether speed gains justify the coordination overhead of managing multiple intelligent systems. The agent sprawl challenge also raises questions about whether security vendors will consolidate capabilities into unified platforms or whether interoperability standards will emerge to help diverse agents coexist without chaos.