If you're deploying AI agents that can make decisions, move data, and trigger actions across your business, you need a way of watching what they're doing. That's why enterprises are building control towers - centralised systems to govern and monitor their agent fleets.
But most of the thinking stops there, which is a missed opportunity. In the workshops and strategy sessions we've been running at Valliance, we’re coming to the realisation that the control tower isn't only an oversight tool for your agents. It's going to give your organisation a real view of how work actually gets done, across every team, every department, every workflow. Human and machine.
What control towers actually do today
Before we get into where this is heading, the systems on the marketplace right now already do more than most people realise.
ServiceNow's AI Control Tower governs fleets of agents across platforms, monitoring them for bias and compliance drift. Palantir's AIP governs agents through the same access controls and change management as human users. UiPath's Maestro orchestrates agents it didn't build, with human checkpoints baked in.
These are more than dashboards, they’re serious infrastructure. But they’re all built around the single assumption that AI agents are a separate category of worker that need to be supervised. The control tower watches the machines and the humans watch the control tower. That hierarchy feels intuitive. It's also limiting.
The scaling problem most enterprises aren't ready for
Those platforms are built for scale, but most enterprises aren't there yet. They're running agent proof of concepts: one or two agents, handling a specific task within a single team, managed by the developers who built them.The 'control tower' in most of these setups is a terminal window or a Slack channel.
That works at small scale, but it doesn't work when you're running agents across an entire enterprise.
Gartner predicts that 40% of enterprise applications will feature task-specific AI agents by the end of 2026, up from less than 5% in 2025. That means managing dozens, possibly hundreds of agents, working across departments, interacting with different systems, making decisions at varying levels of autonomy.. The developer-managed, backend-invisible approach breaks down entirely.
And the people who need visibility aren't all the same. We have to start thinking in terms of the different relationships people will have with these agent networks.
Some people will be orchestrators, overseeing large networks of specialised agents, deciding which workflows to automate and how the pieces fit together - they’ll need deep operational control. Others will be supervisors, your compliance officers and risk specialists, who need audit trails and escalation paths. Then you have collaborators, project managers and team leads working alongside agents day to day, who need intuitive interfaces that don't require a technical background. And beyond all of them, there are passive recipients across the business who benefit from what agents produce without ever interacting with them directly. They might never open the control tower, but the control tower still needs to account for how agent outputs reach them.
A single dashboard view doesn't serve any of these groups well. What's needed is an operational layer that adapts to each of these roles, with different levels of access, different information, and different capabilities. That's a fundamentally different design problem from 'build a monitoring screen'.
Where the real opportunity sits
Think about what we're building to manage AI agents now - governance frameworks, approval workflows, performance tracking, escalation protocols, end-to-end visibility. It makes sense, but why have we never done that for how humans work together? We have ITSM tools, access controls, compliance processes. But they're scattered across different systems and teams. Nobody has stitched them into a single view of how work actually flows through a business.
We build all of this for agents because we're terrified of what happens when one goes rogue. But how terrified are we of what happens when a human goes rogue? When a senior manager leaves and takes undocumented processes with them? When a compliance check gets done by one team but never communicated to another? When ways of working exist as policies buried in a SharePoint folder that nobody opens? The more you think about it, the more alarming it gets. We treat agents without governance as a liability. We should be holding our human operations to the same standard.
Can your organisation see, right now, how work flows between teams? Can you spot where handoffs break down, where decisions stall, where a process that should take two days takes ten? Most enterprises can't. They have ERP systems, project management tools, HR platforms. Process mining tools like Celonis have offered glimpses of workflow visibility, but no one has built a single operational layer that shows how work actually moves through the organisation end to end.
Now, because we have to build it for agents, we're creating something with much wider potential. The control tower, built out of necessity to govern machines, is going to give leaders visibility into their entire operation for the first time.
None of this is an argument that humans and agents are interchangeable. They're not, and both are valuable in ways the other can't replicate. The point is that the orchestration layer, the thing that tracks workflows, enforces governance, manages approvals and monitors performance, doesn't need to care which parts of a process are handled by people and which by machines. It just needs to see the whole picture.
The view from the top
Picture this from a CEO's perspective. You open your control tower on a Monday morning and you can see, in one view, that a claims processing workflow in your insurance division has a bottleneck. Three human reviewers are overloaded, while two AI agents handling the same type of review are sitting at 30% capacity. The control tower doesn't just show you the problem. It shows you where the handoff between the agents and the human team is breaking down, and suggests a rebalancing.
You can drill into your supply chain and see that an agent responsible for inventory forecasting has started drifting from its baseline and its predictions are getting less accurate week on week. The control tower has already flagged it, escalated it to your agent operations team, and paused its autonomous decision-making until the issue is resolved. No one had to notice. The system caught it.
You ask a question in natural language: 'Where are we losing time in the onboarding process?' The control tower pulls from across the workflow, human steps and automated ones, and tells you that the delay isn't in the agent-handled document verification. It's in the three days it takes a manager to schedule an induction call.
That's the difference between a dashboard that monitors your agents and an operational layer that shows you your business. One tells you what your machines are doing. The other tells you where your organisation is working and where it isn't, regardless of who or what is doing the work.
Why this matters now
My colleague Dom Selvon has written about the five layers of enterprise intelligence: ontology, knowledge graph, semantic layer, context graph, and trust layer. Once those foundations are in place, the control tower is the operational layer that sits above all of them.
The enterprises that treat their control tower as an agent-babysitting dashboard will get exactly what they've designed: a monitoring tool. Useful, but limited.
The enterprises that see it as an operational layer for the entire organisation, one that orchestrates work regardless of who or what is doing it, will have something their competitors don't: a real understanding of how their business actually works.
That changes how you allocate resources, how you design teams, how you find bottlenecks, and how you decide what to automate next. It turns the control tower from a cost of doing AI into genuine strategic advantage. It also raises real questions about organisational design, management structures, and what 'running a team' means when half your team isn't human. Most enterprises aren't ready to answer those questions yet. But the ones who start asking now, while they're still building the infrastructure, will be far ahead of those who wait.
The control tower is coming whether you plan for it or not. The question is whether you build one that watches your agents, or one that really shows you your business.
