If you think your organization doesn't have any AI agents running yet, there's a good chance you're wrong. Somewhere in your business, an employee has probably already built one, inside Microsoft Copilot Studio, Zapier, Salesforce Agentforce, Cursor, Retool, or one of dozens of other platforms that now let anyone spin up an autonomous AI workflow in a matter of minutes.
No approval request. No ticket to IT. No security review. Just a helpful little automation that quietly got connected to a CRM, a shared drive, or a code repository, and then kept running long after anyone remembered it existed.
This is shadow AI agent sprawl, and for small and midsize businesses across the South Bay and East Bay, it's becoming one of the fastest-growing blind spots in the cybersecurity landscape.
Why AI Agents Are a Bigger Risk Than AI Chatbots
Most businesses have already come to terms with the risk of employees pasting sensitive data into ChatGPT or a similar chatbot. That's a real concern, but it's a contained one. A chatbot answers a question and stops. It doesn't have standing access to anything, and it doesn't act on its own.
An AI agent is a different animal entirely. Agents are built to hold persistent permissions, connect directly to business applications, and take action without a human clicking "send" each time. When something goes wrong with an unmanaged AI agent, the damage isn't a bad answer in a chat window. It's a system that got touched, data that got moved, or an account that got accessed, all without anyone watching it happen.
The scale of this shift is already showing up in industry research:
- Nearly half of cybersecurity professionals now consider agentic AI the most dangerous attack vector of 2026.
- The large majority of organizations report they've already run into some form of agentic AI risk firsthand.
- Only around one in five IT leaders say their organization has a mature governance program in place to manage AI agents.
That gap between how fast agents are spreading and how prepared businesses are to manage them is exactly where risk builds up unnoticed.
How Shadow AI Agents Slip Past IT
Traditional shadow IT was relatively easy to spot. A new app meant a new login, a new invoice, or a new browser bookmark that eventually surfaced. AI agents don't follow that pattern.
Many of the platforms where employees are building agents, low-code automation tools, browser-based AI builders, and workflow platforms, don't expose that activity through any centralized system IT can monitor. An employee can build an agent, connect it to sensitive company data, and have it running in production before lunch, without ever generating the kind of paper trail that would normally tip off a security team.
The agents built this way are often the riskiest ones. They tend to be created quickly, by well-meaning employees trying to save time, and they frequently end up with far more access than the task actually required, standing connections to a CRM, a code repository, or a shared drive that nobody outside the original builder even knows exists.
What "Securing" a Shadow AI Agent Actually Means
Bringing shadow AI agents under control isn't about banning the tools your team has already found useful. It's about building visibility and accountability around them before a small automation turns into an incident. That generally comes down to three steps.
Find them. You can't manage what you can't see. That means building an accurate, ongoing inventory of every AI agent running across your organization's platforms, not a one-time survey, but a live picture that updates as new agents get created.
Assess them. Once an agent is identified, the next question is what it can actually do. That includes checking for publicly accessible agents anyone in the company could use, agents with excessive or destructive permissions, credentials or sensitive data embedded in agent instructions, and agents whose original creator has since left the organization.
Govern them. Discovery and assessment only matter if they lead to action. Every agent needs an approval status, an accountable owner, and a clear path for flagging and fixing risky configurations, without grinding the rest of the business to a halt in the process.
Getting Ahead of Shadow AI Before It Becomes a Bigger Problem
The reality every IT and security leader needs to accept is that the decision to use AI agents has already been made, one shadow agent at a time, by the people doing the work. Trying to stop that entirely isn't realistic, and it isn't really the goal.
The goal is knowing what's out there, understanding what each agent can touch, and having a plan to act quickly when something doesn't look right.
At INFORTECH, we help South Bay and East Bay businesses get a clear, honest picture of the risks hiding in their technology environment, including the AI tools and automations your team may already be relying on without realizing the exposure they've created. If you're not sure what's running in your business right now, that's exactly the kind of question we help answer.
Ready to find out what's really running in your environment? Schedule a consultation with INFORTECH and let's talk about closing the gap before it becomes a problem.