If you want to understand the future of the global economy, stop looking at Silicon Valley for a moment and look at the nearest international airport.
At first glance, airports seem like an odd model for the future enterprise.
In many ways they are legacy constructs – noisy, complex, highly physical environments shaped by logistics, regulations, customer expectations, and constant time pressure. But look closer and you'll see that they are also deeply interdependent. Airlines, duty-free shops, security contractors, baggage handlers, caterers, maintenance crews, border agencies, and ground transportation services all operate within the same ecosystem.
An airport is a masterclass in modern business architecture. It is an orchestration engine powering a complex system of outsourced execution. Each entity plays a role in the passenger experience, with its own responsibilities, goals, and constraints.
But the airport doesn't fly the planes, cook the food, or move your baggage. Yet it captures disproportionate value because it owns the infrastructure, the customer experience framework, the regulatory surface, and the coordination logic. That is what makes the model so relevant right now.
As organizations grapple with artificial intelligece (AI), automation, and agent-based execution, the core challenge is no longer just how to do work more efficiently. It's how to design, govern, and orchestrate systems where much of the work is done by others, whether human partners, external providers, or AI agents.
This "Airport Model" isn't just an analogy. It's the survival manual for the modern enterprise.
The enterprise is being redefined
Historically, organizations defined themselves by what they do. Their identity has been tied to execution: a bank does lending, a manufacturer does assembly. That model made sense when scale often depended on owning more of the process.
But now, AI is accelerating the separation between coordination and execution. More work can be automated, delegated, and distributed as AI agents become capable of performing specialist operations and scaling capacity at a fraction of the cost. As that happens, the defining question shifts from "What do we do?" to "What must remain at the center?"
That is where the airport analogy becomes powerful. Among the various stakeholders, an airport determines who does what, where, and when. It creates the conditions for the system to work. It sets service expectations through contracts, SLAs, and KPIs that shape the customer journey and measure whether third parties are delivering as expected.
At the same time, it must operate within external governance and compliance demands from civil aviation authorities, federal regulators, political stakeholders, and other oversight bodies. The challenge is finding coherence between both worlds: external regulations and compliance standards on one side, and internal policies, controls, and experience guidelines on the other. Internal and external audit functions are a strong example of how this balance must be maintained.
This is not a minor operational adjustment. It's a different theory of the enterprise. Value comes from enabling, coordinating, and guaranteeing outcomes rather than executing every task directly.
Orchestrators vs. operators
In an agentic world, many layers of a traditional business - expertise, capabilities, and decision-making - can increasingly be distributed to AI-driven systems.
What remains essential are the "rails" that those agents run on. For example:
- Regulatory & governance layer: Tasks can be outsourced; accountability cannot.
- Information layer: The data that powers decisions remains a core asset.
- Value stream design: The blueprint for how value is created and delivered.
These elements define the enterprise. Without them, organizations lose identity, resilience, and trust.
Execution, by contrast, becomes more fluid. Some tasks will remain in-house, some will move to partners, and some will exist in shared ecosystems that resemble networks more than traditional organizations. Success won't come from automating the most tasks. It will come from knowing what to centralize, what to distribute, and how to make the entire experience feel unified.
The best airports demonstrate this. Despite dozens of independent operators, passengers experience a single journey from curb to gate. The complexity is hidden behind an intentional, coherent design.
This is the central challenge of the agentic enterprise. As organizations deploy fleets of AI agents to handle customer service, logistics, procurement, and other core functions, there is a high risk of fragmentation. Poorly orchestrated systems expose the "seams" between processes, creating inconsistent and often frustrating experiences.
Avoiding this requires a strong coordinating layer. The enterprise must ensure that while execution is distributed, the experience remains unified, accountable, and aligned with the brand. Customers, regulators, and partners judge organizations based on whether their experience is consistent and trustworthy.
Why governance is foundational
There is a tendency to frame governance as a brake on innovation. But in complex environments, governance is what makes scaled innovation possible. Without it, coordination breaks down, visibility disappears, accountability blurs, and risk compounds quietly until it becomes impossible to ignore.
In the airport model, when something goes wrong, like a security breach or a power failure, the airport absorbs the responsibility, regardless of which third party caused it. Governance is embedded into the system, not layered on after the fact, because the consequences of failure are immediate and significant.
The same applies to AI-enabled enterprises. As tasks are distributed across agents, systems, and third parties, organizations need the ability to define rules, monitor outcomes, resolve conflicts, and intervene when necessary. If they cannot evaluate and audit how agents are executing, they lose control of the system itself.
Just as importantly, leaders need to manage the tension between efficacy and efficiency. Third parties, agents, and suppliers must be effective enough to deliver quality services that meet customer needs. But they must also be efficient enough to increase capacity, reduce friction, and drive revenue.
Airport security is a clear example. Passengers want to know security is keeping them safe and minimizing personal risk. But they do not want to spend hours in line or experience screening that feels overly invasive or disruptive. The system has to balance quality and quantity, protection and throughput, trust and speed.
The same tension exists in every agentic enterprise. Process intelligence provides the levers to see, manage, and optimize that relationship. Someone will still be required to own the whole. And when something fails, responsibility cannot be outsourced.
The new economic imperative
Productivity in the agentic era isn't about how many tasks your employees complete but rather about how effectively an organization orchestrates a complex web of automated execution. Airports didn't adopt their model by choice. They evolved out of necessity.
The scale, complexity, and interdependence of their operations made vertical integration impractical. The system needed a clear separation between coordination and execution. As AI agents become more capable, the design of the system they operate within becomes the primary source of value. Organizations that excel will not be those that try to do everything themselves, but those that position themselves as the central node through which value flows. Airports show how this works. They create value not by performing every task, but by orchestrating the environment in which those tasks happen.
The question for leaders today is simple: Are you trying to fly the planes, or are you building the airport?