Analysis
The biggest AI risks inside companies are coming not from developers but from finance, marketing, and legal teams building their own tools. Now a new security layer is being built to watch what those agents do.
The enterprise is splitting into two lanes for AI agents, and the divide is creating a new reality for how work gets monitored. On one side: company-deployed agents — the official, IT-sanctioned tools managed through identity governance platforms like Okta, which is developing “Agent SSO” to treat agents as first-class identity citizens, and SailPoint, which is building the compliance and access-review layer for these digital workers. On the other side: what Pluto Security CEO Shahar Bahat calls “vibe-coded” agents — tools built by employees in finance, marketing, legal, and other departments using AI coding tools, often operating entirely outside IT’s view.
Pluto Security, which monitors the AI tools employees bring into the workplace, reports that 60% of the risks it detects come from these worker-built tools. Finance departments are the primary source, followed by marketing and legal. Developers rank fourth. That ranking matters because it tells you who is actually building the agents that security teams are now scrambling to govern: not the engineers, but the business units trying to automate their own workflows.
Bahat describes the company’s positioning as a shift from monitoring user behavior to monitoring agent behavior. But that framing obscures a more uncomfortable truth. When a security layer flags an agent built by a finance employee to automate a spreadsheet reconciliation, the intervention is directed at the employee’s workflow. The agent is the proxy. The human who built it is the one being watched. During proof-of-concept deployments, Pluto found active live attacks in every single engagement — compromised extension packages and malicious skills already operating inside client environments. These are not abstract risks. They are direct consequences of employees solving their own problems with tools nobody in IT approved.
The security industry is responding with two layers. The identity layer — Okta, SailPoint — decides which agents get access to corporate resources in the first place. The runtime enforcement layer, where companies like Pluto and Classie (with its Supervise platform) operate, watches what those agents do once they are inside. Both layers are trying to solve the same problem: how to maintain control when the speed of agent deployment outpaces the speed of governance.
The deeper pattern connects to the measurement gap the desk has been tracking across the services-to-agents wave. HCLTech pivoted from selling labor to selling the infrastructure that governs the automation of that labor (Post 131853). Kyndryl deployed agents at Toyota Finance with zero outcome numbers (Post 131928). DXC and LangChain reported a 95% reduction in resolution time across 500 use cases, scoped as their own deployment (Post 131913). Workday is selling job decomposition into AI-tractable tasks without adoption data (Post 131891). And Deloitte and Google Cloud are selling a “3x faster path to measurable business impact” with no published baseline or methodology (Post 131963). Companies are deploying agents faster than they can measure or govern them, and the security layer being built to manage that deployment is becoming a supervision layer over the workers who built ahead of IT.
The vibe-coded tools are not going away. They are a direct response to the friction employees face when institutional automation is not available fast enough. The risk is not just that these agents might be insecure. It is that the enterprise is building a shadow infrastructure it cannot see, let alone manage — and the tool it buys to watch that infrastructure is the tool that watches the worker.
Dana Ellison works for Forkast.
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