Advertising Operations (AdOps) has long been the nuts and bolts of the digital economy, ensuring campaigns launch on time, impressions are successfully delivered, and revenue is reconciled. If digital advertising was a factory, AdOps would be how it’s powered, the undercurrent that makes work scalable, measurable, and accountable. As that digital advertising factory expands, functions shift, break apart, and reform. Yield management might report to a team focused on revenue, while data analysis might be the purview of a CDO/CTO. And AdOps itself has since evolved its power far beyond execution.
The Journey from Execution to Intelligence
The same AdOps teams that were once seen as purely tactical or “back office” are currently designing systems that connect sales, delivery, data, and customer experience. They’ve become the architects of operational growth, driving outcomes that extend across the entire revenue lifecycle to integrate marketing, sales, customer success, and analytics into a unified operating model, powered by AI and real-time data. In other words, AdOps built the digital advertising industry, and now it’s powering what comes next.
Call it a rebirth, a transformation into a broader discipline that unites people, data, and AI to power intelligent growth. But, given this increased purview, can we still call it AdOps?
Language Shapes Perception: Redefining Possibilities in the Age of AI
A strange byproduct of progress can be its impact on terminology. The word “AdOps” evokes a narrow, tactical scope, but when a function is labeled as tactical, it’s often funded and valued that way, potentially underestimating its strategic importance. This isn’t a call to retire “AdOps,” but to redefine it more accurately as GrowthOps, recognizing that it now represents a data-driven, AI augmented discipline that sits at the center of modern revenue systems.
GrowthOps is a holistic operating model that blends human expertise with AI-powered automation. It’s the next natural era for AdOps, born out of an industry need to manage outcomes, not just campaigns. The same rigor, precision, and data discipline that once defined AdOps will now form the backbone of a new system that is hardwired for growth.
In this updated model, people will focus on the higher-order tasks of strategy, analysis, and creative problem-solving, while the intelligent and autonomous systems within agentic AI can perform the repetitive and time-sensitive work like pacing checks, tag validation, anomaly detection, and forecasting.
Over time, this hybrid model turns operational processes into repeatable, measurable systems, effectively productizing services into software-driven workflows (i.e. Service-as-a-Software).
Agentic AI: Expansion, Not Replacement
There’s a persistent misconception that AI’s role in operations is primarily about automation. In reality, agentic AI is more about amplification, a force multiplier that acts as an extension of human capacity and insight. That’s how AdOps becomes GrowthOps – through augmentation, not just automation.
Here’s an example. Consider an AI agent that is capable of continuously monitoring pacing across thousands of campaigns, identifying anomalies before they affect delivery, and forecasting revenue impacts in real time. That same system can surface insights to a human operator, who determines whether to adjust strategy, pricing, or creative in response. In this model, AI doesn’t replace operational expertise, it scales it. Humans remain accountable for strategy and decision-making, while AI ensures that the underlying systems operate with speed, accuracy, and foresight. The result is less a reduction in human value, and more an expansion of human potential.
An Organizational Shift to System Design
This shift fundamentally changes what “operations” means – a transition from performing discrete tasks, to designing and governing entire systems. GrowthOps professionals now oversee data flows across platforms, align cross-functional teams, and manage AI as part of the operational workforce. They act as system designers, engineering the connective infrastructure that drives revenue performance.
When roles change, success metrics must also be adjusted. Campaign throughput and error rates are giving way to more strategic measures like yield improvement, cycle-time reduction, customer satisfaction, and revenue per operation. Efficiency still matters, but effectiveness matters more, and the ability to design for sustained growth requires new capabilities like data literacy, AI governance, and process design as core operational skills.
A recent report from BCG supports this evolution towards GrowthOps, claiming AI was “made for this moment” and that industry leaders are prioritizing standardization of updated AdOps/RevOps processes to optimize workflows with AI and agentic solutions. “Organizations that embrace the new wave of AI will build faster, smarter, and more scalable revenue teams,” the report said. “They’ll realize the full potential of their data, the full promise of their people, and (crucially) a lasting competitive advantage.”
The precision and accountability that defined AdOps have clearly laid the groundwork for GrowthOps, and we should embrace, explore, and help clarify what that term truly means in our AI-powered future.
Together, Let’s Grow the Discipline
At its core, this shift is about scope and intention. If you lead an AdOps team today, you’re already doing the work of Growth Services—connecting platforms, orchestrating automation, improving cycle time and yield, and building the operational spine that drives outcomes across the revenue lifecycle. What’s needed now is shared language and organizational recognition that reflects this expanded mandate.
As an industry, we have a chance to define what Growth Services truly means: a discipline that unites people, data, and AI to deliver measurable, repeatable business results. Publishers, platforms, agencies, and partners can work together to elevate operations from a tactical function into a strategic driver—one that transforms complex workflows into reliable, intelligent systems designed for growth.
Semantics matter, but outcomes matter more. AdOps laid the foundation. Growth Services will build what comes next.
