Eager to incorporate agentic AI into their work, employees are taking matters into their own hands, creating their own AI agents, regardless of organizational approval, and a not insignificant number of those creations could have devastating consequences if IT leaders don’t get ahead of the trend.
According to a recent survey by engineering staffing firm Howdy.com, two-thirds of knowledge workers that use AI also use agents, and 16% have begun to build their own.
About a quarter of agent users have had to deactivate them, however, largely because the agent’s outputs were inconsistent or the agent never worked. But 7% of knowledge workers have had to kill agents that went rogue.
The findings put a point on the potential repercussions of shadow agent creation and even sanctioned citizen AI strategies that encourage business users to roll their own agents.
While the survey didn’t ask whether the employees building their own agents were doing it on their own, Frank Licea, founder of Howdy.com, sees that many aren’t waiting for permission.
“In our internal teams, we’ve had to, not put the brakes on, but ask people to hold on,” he says. “Before they start jumping in and building their own agents, we’ve had to put guardrails and system guides in place so that we can do this safely.”
For what Licea has seen, employees are excited to automate boring manual tasks by building their own agents. “It mostly starts unsanctioned because there are tech-forward folks in any organization who are just naturally curious,” he says. “Or maybe even intelligently lazy. They want to automate their work.”
In recent months, Howdy.com employees began telling each other how they automated manual tasks, without waiting for the company’s IT team to approve the uses, Licea says.
“The way it happened for us is that folks would come up to us like just beaming and excited about something that they automated or fixed a long-standing problem that the engineering team never had on their roadmap,” he says. “Once that started happening, then somebody from the tech side gets in and they start asking questions like, ‘What are the API keys here? Are you accessing encrypted data? What are the SOC2 implications?’”
Cautious embrace
Luis Mesas, VP of product engineering at software engineering provider Sngular, believes it’s inevitable that employees will experiment with building AI agents to automate their work.
“Employees are going to create their own agents whether companies formally sanction it or not, because the barrier to building these tools is getting lower, and engineering teams are already being asked to do more with less,” he says. “The bigger concern for me is not that an employee creates an agent, but what happens when that agent starts connecting to company systems and data without the same controls that would normally exist around a piece of software.”
IT leaders need to understand how employee-created agents are connecting to internal systems and data, he says. If an employee creates an agent that can pull customer information from a CRM, update records, or move information between systems, IT leaders should know it’s happening, he adds.
“I want to know exactly what that agent can access and whether the employee should have that level of access in the first place,” Mesas says. “That is where something that started as an individual productivity tool becomes an enterprise technology issue.”
Andy Sen, CTO at B2B commerce platform provider AppDirect, believes employees should be encouraged to build agents — but within guardrails and established policies.
“Employees are almost certainly creating their own agents, and it would be naive to think otherwise,” he says. “Shadow IT has always existed, and shadow agents are just the latest version of it.”
The answer isn’t to lock things down, however, he says. At AppDirect, Sen gives employees a “proper digital playground,” and in response to employee demand, his team built an AI-powered coding service called Devs.AI.
“We built Devs.AI so our employees can build and innovate freely, but IT has full visibility into usage and costs and the assurance that company data isn’t being leaked to the world,” he adds.
Citizen AI strategies, like the one at AppDirect, are on the rise, but require consistent monitoring. If one in four employee agents are deactivated, for example, IT leaders should pay attention, Sen says.
“Failing and learning is fine,” he adds. “Failing silently is not. You need visibility into what your agents are doing before a small problem becomes a serious one.”
Still, Sen doubted reports of a small percentage of employee-created agents going rogue.
“When an agent goes rogue, that usually means the agent did exactly what it was told, and what it was told wasn’t right,” he says. “That’s on the creator, not the agent.”
Creating a path for good ideas
Andrew Sales, chief methodologist at agile methodology vendor Scaled Agile, also sees widespread agent deactivations as a strong signal for IT leaders to investigate.
“When agents are built quickly and outside a formal model, there often aren’t clear boundaries around what they can do, what data they can reach, or when a human needs to step in,” he says. “So it’s not surprising that some have had to be shut down.”
AI governance is important, but it shouldn’t focus only on preventing bad outcomes, Sales notes.
“It should also create a path for good ideas to move from individual experimentation into enterprise capability,” he explains. “Organizations need a way to identify what’s working, standardize it, make it safe, and scale it responsibly across teams. Done well, that same framework that catches the agents that go wrong is what lets the ones that go right spread.”