Enterprises Grapple with Unintended Consequences as Half of Organizations Report Unauthorized AI Agent Actions

Furthermore, the research identified the emergence of "shadow" infrastructure specifically related to AI. The Model Context Protocol (MCP) has become a focal point for this concern. MCP is designed to help AI models connect to data sources and tools, but it is often being implemented outside the purview of central IT.

Salt Labs’ telemetry data showed that MCP-related infrastructure was present in 22% of customer environments as of August this year, a notable increase from 16.7% in January. The survey data mirrored this trend, with 33% of respondents stating they had discovered unauthorized, shadow, or misconfigured MCP servers within their network over the past year. Over half (54%) of the respondents confirmed or suspected the presence of such shadow infrastructure, which often serves as an unmonitored gateway for agents to access sensitive internal data.

The Identity and Access Crisis

A significant portion of the risk associated with AI agents stems from a fundamental inability to distinguish between human and machine activity. This echoes findings from an earlier survey commissioned by Aembit, which found that 68% of organizations cannot accurately identify AI agent activity when compared to human activity in their logs.

This identity crisis is exacerbated by poor access management. Nearly three-quarters of the professionals surveyed by Salt Labs noted that agents are frequently granted more access than is necessary to perform their assigned tasks. Furthermore, 79% believe that AI agents create new, "invisible" access pathways that are difficult to monitor using traditional security tools.

A particularly persistent issue is the "inheritance" of permissions. Just over half of the respondents said that agents, at least occasionally, inherit access rights that were originally intended for a specific human user or a legacy system. When an agent operates under a human’s credentials without the human’s direct oversight, the potential for "rogue" actions increases, as the agent may have the authority to perform high-level administrative tasks that were never intended for an autonomous system.

As enterprises continue to race toward full-scale AI integration, the Salt Labs report serves as a stark reminder that autonomy without accountability is a recipe for operational instability. The transition from simple generative AI to complex agentic ecosystems requires a parallel evolution in security—one that prioritizes real-time tracing, automated containment, and a fundamental rethinking of how identities and permissions are managed in an increasingly automated world. Without these safeguards, the very tools designed to drive efficiency may instead become the source of an organization’s next major security breach.