ServiceNow Coming in to Land
Why the Control Tower Matters to the Future of Enterprise AI
When software companies take off, the headlines are usually all about altitude. It’s revenue growth, new product lines, and the size of the sky they’re claiming. But real maturity in enterprise technology isn’t about getting airborne. Execution is all about the landing. That means how well a company aligns its trajectory, coordinates the approach, and manages the turbulence of scale.
In that sense, ServiceNow is coming in to land. The numbers are strong, the engines are humming, and the company’s AI-driven transformation is sounding less like marketing and more like mastery.
Their third-quarter 2025 results confirm that the flight path is now controlled, not coasting. Subscription revenue rose 20.5 percent year-on-year to about $3.3 billion; current RPO climbed to over $11 billion, total RPO reached $24+ billion, and the non-GAAP operating margin expanded to 33.5 percent. The renewal rate held steady at 97 percent (incredible), and full-year guidance lifted about 20 percent to over $12.8 billion in subs.
These are the numbers of a company executing with precision. Yet the real story lies beyond the balance sheet. When execution is this consistent, the more interesting question isn’t what they achieved, but why it’s working.
Think of every organisation as operating its own controlled airspace. A kind of living operational environment where departments, systems, and AI agents all fly at different speeds and altitudes. Some are climbing, some circling, some descending. They cross data corridors, pass through shared zones, and rely on coordination to avoid collision.
ServiceNow understood early that in any enterprise airspace, control is everything. And just like in real aviation, two kinds of air-traffic controllers are needed to keep things safe and efficient.
En-route controllers are needed to manage specific stretches of airspace, maintaining order and separation as aircraft travel through their assigned sectors, much like finance, HR, IT, or customer service teams manage their own domains.
Then there are tower controllers who, by contrast, manage the intersections. Things like the take-offs, landings, and hand-offs between sectors where flights converge, timing is critical, and coordination keeps everything moving safely.
The challenge for most enterprises is that when it comes to AI, while they have plenty of aircraft (applications, automations, and models), they lack unified control. There’s no tower. No controllers. Each software vendor just adds another flight to the sky, and another signal to track. But without a coordinated system, the airspace becomes noisy, siloed, and unpredictable. Unsafe. Not trusted.
That’s the problem ServiceNow’s AI Control Tower was built to solve. It acts as the enterprise’s tower and radar combined, giving organisations visibility, coordination, and, most importanlty, trust across every flight in motion, from departmental automations to cross-enterprise AI operations.
Just like in aviation, the Control Tower is not designed or meant to replace the en-route controllers. It depends on them. Both are essential to the overall system. For air traffic control to work you need aircraft in flight, en-route coordination to manage their movement across sectors, and tower control to handle the apron and runways where timing matters most.
In the enterprise sky, the en-route controllers include the system-of-record vendors like the ERPs, CRMs, HR and asset platforms that manage traffic within their own domains. Each governs its stretch of airspace, maintaining order, process, and compliance within its boundaries. But none of them can see the whole sky. That’s where ServiceNow’s Control Tower comes in.
Like aviation, it combines tower control and flight freedom, enabling domain systems to scale safely under shared governance. ServiceNow doesn’t seek to fly other company’s planes. Rather it coordinates them, providing the radar, sequencing, and cross-sector communication needed to keep every system of record moving in harmony across the enterprise.
What sets ServiceNow apart is that it didn’t just build another aircraft. It built the system that coordinates the entire sky. Its architecture is engineered for orchestration, not participation, designed to manage movement, timing, and safety across every flight path. It does this through four interlocking pillars that mirror the structure of real-world aviation management:
The first, AI Strategy, is equivalent to the flight planning function. It defines the routes, priorities, and airspace design so every AI initiative departs with purpose and stays on course with business objectives.
Secondly, AI Governance is the regulatory and safety function setting the rules of the air through compliance, auditability, and frameworks such as NIST AI RMF and the EU AI Act, ensuring trust and accountability across every flight.
Thirdly, AI Execution is the air-traffic management layer providing operational control that automates hand-offs, monitors flow, and keeps all AI systems moving safely across departments and sectors.
Lastly, AI Value is the performance and telemetry system tracking fuel, altitude, and efficiency and translating every flight’s data into measurable business outcomes in real time.
Together, these pillars make ServiceNow the airspace orchestrator, not just another aircraft. It is the platform capable of connecting, governing, and optimising every other flight in the enterprise sky, keeping traffic visible and synchronised through the Workflow Data Fabric.
After all, imagine a real airport control tower that couldn’t communicate with different airlines. The result would be chaos. The same principle applies here. Complex ecosystems thrive only when coordination and autonomy coexist under intelligent regulation.
So that means the quiet brilliance of ServiceNow’s approach lies in its focus on stability under speed. That is, governance as growth.
Its innovation isn’t a single model or algorithm. It is the governance architecture that allows many to coexist. The solution turns scattered initiatives into measurable business assets, making risks visible, aligning AI development with enterprise strategy, and letting organisations prove, not just promise, value. In aviation terms, it provides the landing path for every new flight of automation. That is critical.
Because aviation teaches us that the measure of a system’s sophistication isn’t how many planes it launches, but how safely and efficiently they land. ServiceNow’s architecture reflects that truth. Its success feels less like another climb into new airspace and more like a controlled arrival. That’s the real payoff we all experience when we travel. And that is the mark of a company that’s learned how to coordinate complexity rather than just accelerate it.
Yet even the best-equipped tower faces trade-offs. Too much control creates bottlenecks and too little invites trouble. So ServiceNow’s future depends on managing that balance by allowing partners and customers to fly their own aircraft while maintaining oversight of the whole airspace.
If the customer’s (AI CoE), and by extension the tower, insists that every signal pass through it, the system slows. But if it permits too many private channels, coherence is lost. The art lies in orchestrating both. Maintain centralised visibility without stifling decentralised freedom.
Customers and their teams will continue to choose bespoke AI tools tied to their ERP and vertical systems of record, but the Control Tower’s role is to ensure that this freedom doesn’t fracture the operational airspace and that innovation still resolves the larger challenges of trust, safety, and efficiency rather than creating new turbulence.
That symmetry between the enterprise and the tower defines the current competitive frontier in AI. The race is no longer just about building the fastest or most capable model, but about governing coexistence through the choreography of thousands of machine and human actors operating safely in the same airspace.
ServiceNow’s other advantage is its understanding that control and freedom are actually not opposites, but coordinates. Its success now depends on how well it can manage both. The partner side will be interesting.
For direct customers, the implications are immediate. Most already have dozens of AI projects flying in loose formation. They need orchestration, visibility, and safety. The Control Tower model provides that discipline, letting IT and business leaders coordinate across the enterprise to know which models are active, where data is flowing, and what outcomes are being achieved.
But just as in aviation, control brings responsibility. Stronger towers demand stronger governance. Fairness, transparency, and trust must be built into the infrastructure itself, not added after the fact.
For partners, this marks a shift. Many are used to flying solo, managing their own airspace with little interference. That model won’t hold in the 21st century. The new environment rewards those who can operate within a regulated, coordinated sky, where visibility, safety, and shared standards take precedence over individual autonomy. Some will thrive and accelerate through alignment with ServiceNow’s platform and alliances. Others may need to adjust to remain visible and viable within the broader system.
For ServiceNow, landing this strategy requires precision, and the financials suggest it’s achieving it. The company is expanding margins while accelerating adoption, embedding AI governance exactly when enterprises most need it, and doing so on a platform now central to how organisations coordinate intelligence.
In this sense, ServiceNow’s leadership is less about dominance and more about discipline. The stronger its tower becomes, the more it must enable, not control, the flights around it. True ongoing maturity lies in building a system where thousands of independent journeys can still move in harmony, each confident that the sky above them is both open and safe.
I hope ServiceNow continues to go deeper with the Control Tower concept. It’s a rich idea. Strategically brilliant. One that captures exactly what the AI era demands. But it remains under-explained. Not yet fully articulated. The potential is far greater than the current narrative suggests.
For me, what it says most profoundly, is that ServiceNow isn’t trying to teach the world how to fly. It is actually showing it how to land.