Your Company Has More AI Agents Than You Think. Now There's a Tool to Track Them.
A client told me last month that his team had "about twelve" AI agents running across the company. When I asked him to list them, he got to seven and stopped.
That gap between "about twelve" and "I can name seven" is the problem Dataiku just decided to solve.
The company launched Agent Management this week. It's a standalone product that inventories every AI agent in an organization, tracks business and technical performance for each one, and sorts them by risk level.
It targets a specific problem I keep seeing in consulting calls: agent sprawl.
What agent sprawl actually looks like
Here's the pattern. A marketing team spins up a content agent. Sales gets a lead qualification bot. Customer support deploys a ticket triage system. The CFO's office builds a forecasting assistant. Each one works fine on its own.
Six months later, nobody knows which agents access which data, whether any of them overlap, or what happens when two agents give contradictory answers to the same customer.
I had one client discover that their support agent and their sales agent were both responding to the same inbound emails. With different answers. For three weeks.
Why this matters more than you think
Most businesses treat AI agents like software subscriptions. Deploy it, forget it, check on it when something breaks. But agents aren't static tools. They learn, adapt, and access data in real time.
An agent you deployed in March might be accessing data sources that didn't exist when you set it up. It might be making decisions based on patterns you never validated. And if you're in a regulated industry, you might be liable for what it did last Tuesday and have no record of why.
That's what Dataiku is targeting. Their platform gives operations leaders a single dashboard showing which agents meet their SLAs, which ones are falling short, and which ones pose compliance or security risks.
The practical question for your business
You don't need Dataiku's product to start fixing this. The exercise is simpler than you think.
Take thirty minutes this week and answer three questions:
- How many AI agents are currently active in your organization?
- What data does each one access?
- Who is responsible for monitoring each agent's output?
If you can't answer all three confidently, you've already outgrown your governance setup.
I run through this exact exercise with consulting clients before we add any new automation. The answers are always revealing. One real estate firm found they were paying for two agents that did the same thing, just built by different teams. Another discovered an agent producing weekly reports nobody had read for four months.
What to actually do about it
You don't need to buy enterprise governance software tomorrow. Start with a spreadsheet. List every agent, what it does, what data it touches, and who owns it. Update it monthly.
If you're an AI agency building agents for clients, this is an even bigger deal. Your clients will start asking for agent inventories and performance reports. The agencies that build governance into their delivery from day one will win the deals. The ones scrambling to add it later won't.
Dataiku priced this as a standalone product for a reason. They're betting that agent governance becomes its own category, separate from the platforms that build and deploy agents. Looking at how fast businesses are adding agents without tracking them, I think they're right.
The deployment race already happened. The next race is figuring out who's actually managing all of it.
