Boomi has unveiled new tools aimed at helping enterprises keep artificial intelligence agents under control as businesses move rapidly from AI experiments to real-world deployment.

At the center of the update is the Boomi Agent Control Plane, an AI-native infrastructure layer designed to connect AI agents to business systems while governing their actions, monitoring costs and limiting security risks.

The platform can operate across public cloud, private cloud and on-premises environments, giving organizations greater control over where data and AI workloads reside.

The launch comes as companies grapple with the risks of deploying autonomous AI agents without sufficient oversight.

Gartner predicts that by 2027, 40 percent of enterprises will demote or decommission autonomous AI agents because of governance gaps discovered only after production incidents.

Cost is another growing concern. A 2026 FinOps Foundation survey found that 98 percent of respondents now manage AI spending, up from 31 percent two years earlier.

Boomi said its control plane is designed to address both problems by giving companies a central view of AI agents and tools, enforcing access and rate limits, tracking token usage and requiring human approval for high-risk actions.

The company said the system is vendor- and model-neutral, allowing enterprises to govern agents built using different platforms and models without being locked into a single AI ecosystem.

Boomi is also expanding governed access to enterprise systems through more than 1,000 pre-built tools and Model Context Protocol servers, allowing AI applications to connect to platforms such as Salesforce, SAP, Oracle and Workday.

Other capabilities include running agents behind corporate firewalls, grounding AI outputs in verified business data, turning natural-language instructions into multi-system workflows and expanding APIs for developers.

“The governance conversation has shifted from model risk to execution risk,” Omdia Chief Analyst Michael Barnes said.

Boomi chairman and CEO Steve Lucas said tighter control should not be viewed as a barrier to AI adoption.

“Control is not the brake on enterprise AI. It is what makes scale possible,” Lucas said.