Businesses racing to deploy AI agents across their operations are discovering an uncomfortable truth: agents that act autonomously also spend autonomously. Boomi is betting that the governance problem is now big enough to build a product category around.

On September 2, 2026, Boomi announced its Agent Control Plane, a vendor-neutral infrastructure layer designed to sit between any AI agent and the enterprise systems it touches. The pitch is straightforward: as organisations connect AI agents to SAP, Oracle, Salesforce, Workday, and similar platforms, someone needs to be watching what those agents actually do, and what they cost.

What the Agent Control Plane Does

Think of it as a smart intermediary that every AI agent request passes through before it reaches a business system. As a request comes in, the control plane checks identity, applies rate limits, inspects the action being requested, and decides whether to let it through, throttle it, or hold it for human review.

The key capabilities Boomi has built in:

Governance at the point of action. High-risk transactional operations, things like deleting records, submitting payments, or modifying customer data, are flagged and paused for human approval before execution. Agents can work autonomously on routine tasks while humans stay in the loop on the decisions that matter.

Token spend tracking. This is getting more attention than you might expect. The FinOps Foundation’s 2026 State of FinOps survey found that 98% of practitioners now actively manage AI spend, up from just 31% two years ago. The Agent Control Plane tracks model usage in real time and curbs token overruns before they turn into budget surprises.

Deployment flexibility. The control plane runs on public cloud, inside a company’s own virtual private cloud, or on-premises. That matters for organisations in regulated industries that need their data and AI activity to stay within specific boundaries.

Model and vendor neutrality. Whether an agent is built on Boomi’s own platform, an open-source framework, or a third-party provider, the control plane can govern it. That positions Boomi as infrastructure rather than a competing platform, which is a deliberate play.

Why This Is Coming Now

The timing aligns with a broader governance crisis emerging in enterprise AI deployments. Gartner has projected that by 2027, 40% of enterprises will demote or shut down autonomous AI agents specifically because governance gaps only became visible after the agents were already in production.

That’s the fundamental problem: most AI governance thinking happens before deployment, not during it. Policies get written, frameworks get approved, but once an agent is live and making decisions across dozens of connected systems, oversight becomes genuinely difficult.

The Boomi solution centralises what was previously scattered. Instead of trying to instrument governance into every individual agent or every connected system, the control plane creates a single observation and enforcement point.

The Real Cost Problem Nobody’s Talking About

Beyond governance, the cost dimension is catching business leaders off guard. When AI agents can autonomously trigger API calls, model inferences, and automated workflows, token consumption can compound quickly. A single poorly configured agent running unchecked can generate costs that dwarf what was budgeted for an entire project.

The FinOps jump from 31% to 98% of practitioners managing AI spend in two years tells the story. What started as an R&D curiosity is now live in production, connected to real systems, and generating real bills.

Boomi’s control plane addresses this directly by applying rate limits and spend caps at the infrastructure level, before costs accumulate in whatever cloud bill arrives at the end of the month.

What This Means for Business

If you’re deploying AI agents in your business, or planning to, the governance question will hit you before you expect it. The typical progression looks like this:

1. You start with a contained pilot where one agent handles one workflow.
2. The pilot works. You scale. More agents, more systems, more action types.
3. Somewhere in that scaling, you lose visibility into what’s happening.
4. Something goes wrong (or the bill arrives) and you scramble to understand how.

The Boomi approach is to build governance infrastructure before that scramble happens. That means designing a system where agents have defined permissions, their actions are logged, costs are tracked, and humans retain the ability to intervene.

For Enterprise DNA clients working on AI agent deployments through Omni Ops, this is the kind of infrastructure thinking that separates a successful enterprise AI program from an expensive one. Agents are tools. Like any tool, they need a workbench with proper controls, not just an open field.

The control plane category Boomi is building is going to get crowded. This won’t be the last vendor announcing something similar. But the underlying need it addresses, governing agents that operate across multiple systems with real business consequences, is not going away.

---

Ready to think through your AI agent governance model before deployment? The team at Enterprise DNA’s Omni Advisory service helps business leaders build AI strategy that accounts for governance, cost, and risk from day one. Book a discovery call to start that conversation.