It's 10 PM. Do You Know What Your AI Agents Are Doing?
If you're old enough, you probably remember the public service announcement that aired every night before the evening news:
"It's 10 PM. Do you know where your children are?"
Today, executives should be asking a different question.
Do you know what your AI agents are doing?
Not just the ones running in Microsoft.
Or Salesforce.
Or ServiceNow.
All of them.
Across every platform.
Across every workflow.
Across your entire business.
For most organizations, the honest answer is no.
And that's becoming one of the biggest operational risks of enterprise AI.
The Challenge Isn't Building AI Agents
Building AI agents is getting easier every month.
Every major software platform now offers tools to create intelligent assistants, automate workflows, and connect AI into everyday business processes.
The result?
Organizations aren't deploying one or two AI agents anymore.
They're deploying dozens.
Soon, many will be managing hundreds.
The challenge isn't creating them.
It's knowing what's happening once they're running.
Every New Agent Creates Another Decision-Maker
AI agents don't simply automate repetitive work.
They make decisions.
They approve requests.
They interpret policies.
They collaborate with other systems.
Sometimes they trigger additional agents.
Sometimes they ask humans for help.
Sometimes they encounter situations no one anticipated.
Individually, each agent may be operating exactly as designed.
Collectively, they create a new operational challenge.
Who's watching how all of those decisions fit together?
Why Existing Tools Don't Answer the Question
Every AI platform gives you visibility into its own agents.
That's useful.
But enterprise AI doesn't live inside one platform.
Your organization might have agents running inside Microsoft, Salesforce, ServiceNow, OpenAI, and custom applications built specifically for your business.
Each platform shows you its own slice of the world.
None shows you the enterprise.
When something unexpected happens across multiple systems, leaders are left stitching together logs, dashboards, emails, and conversations to understand what actually occurred.
By then, the decision has already been made.
The Real Risk Isn't One Rogue Agent
People often imagine the biggest risk is a single AI agent behaving unpredictably.
In reality, that's rarely the problem.
The greater challenge is losing sight of how dozens—or eventually hundreds—of agents interact across the organization.
An approval gets delayed.
A policy conflict appears between systems.
An exception never reaches the right person.
An important decision waits because no one realizes human input is needed.
None of these failures happen because one agent malfunctioned.
They happen because no one is coordinating the system as a whole.
Enterprise AI Needs an Operating Layer
As AI becomes embedded across the business, organizations need more than individual agent dashboards.
They need an operating layer that provides oversight across the entire AI ecosystem.
A place where leaders can understand what's happening, coordinate human decisions, manage exceptions, and ensure AI is executing work the way the business intends.
Because the question executives will increasingly be asked isn't whether they have AI.
It's much simpler than that.
Do you know what your AI agents are doing?
And before long, "I think so" won't be a good enough answer.