For the Dirty Projectors, the stillness might be the move. But for ad ops, progress only comes from moving with intention.
Maybe AI isn’t taking over ad ops. Maybe it’s elevating it. From prompt engineering to creative alignment and data stewardship, ops teams are moving from the weeds to the frontlines of strategy. Here’s what it takes to keep up.
Everyone keeps saying AI won’t replace humans. Sometimes, I’m not so sure.
Two recent moments in my personal life prompted me to pause and reflect on what “human in the loop” actually means—and whether that loop is getting smaller.
First, it was during a therapy session when my therapist casually mentioned that our platform was recording everything we said. It was no surprise that AI was helping her take notes, but it also created a podcast based on our discussion.
Was it an episode of Black Mirror?
Similar issues. Similar language. Similar therapeutic advice. But delivered by two AI characters.
Then, there was a recent call with my AI health coach. It was a real-time voice interaction driven entirely by data from my Oura Ring, Apple Watch, and Whoop. No waiting. No human. Just my AI coach, Andrew, sharing insights about my metabolic health delivered in a calm, slightly robotic tone.
It’s even scarier to me now that I thought it was normal.
If AI can personalize emotional support and wellness advice, how long before it handles the pacing alerts, floor pricing logic, or yield recommendations in ad ops? (Spoiler alert: it already is.)
Agents on the Rise
I remember someone at a big ad tech company telling me that soon, the sell-side agent will connect with the buy-side agent, and voilà—it’s a done deal.
Maybe it’s true.
“We are nearing the time when every brand will have an agent,” Kaitlin Leary McCrann, GM, Global Buyside Partnerships at Scope3, said on a session at DMS by Luma.
According to her, several of the large consultancies estimate that over 75% of brands will have deployed agents by the end of 2026. Agents can deeply align brand values, outcomes, and consumer experiences—if deployed correctly.
But we can’t just let the agents run wild. “You have to prompt it, check it, prompt it again, and repeat that until the model deeply understands your values, principles, regulatory guidelines, data goals, and outcomes,” she wrote on LinkedIn after the session.
And for media companies? A similar shift is underway. Major publishers are already exploring ways of using autonomous campaign management and dynamic floor logic to enhance monetization while maintaining control. These are no longer experiments.
So no, the job of ad ops isn’t going away. But the role is changing—fast. And the future belongs to those who can evolve alongside it.
Ad Ops Evolution
“Ad operations, once focused on managing inventory and delivering ads, is now evolving into a strategic powerhouse. This shift is driven by advancements in technology, changing consumer behaviors, and the increasing complexity of the advertising ecosystem,” Dharmesh Ramesh, Senior Manager at Operative, wrote on LinkedIn in January.
What does this mean for ad ops?
AI and machine learning are transforming the ad ops landscape. These technologies are becoming central to campaign management, optimization, and measurement.
To stay ahead, ad ops pros need to enhance their skills in data fluency, analytical expertise, proficiency in AI tools, automation, and workflow optimization, as well as strategic and creative collaboration, excellence in data governance, and continuous learning and adaptability.
Moving Beyond the Dashboard
Where operations once focused on pulling and reconciling reports, there has been a shift to interpreting models, questioning inputs, and translating signals into stories.
AI-powered forecasting and campaign optimization now demand clean, connected data. It also requires someone who can add meaning to machine outputs.
“Data is only valuable if someone’s interpreting it in context. We’ve had automation in place, but the ops team still needs to translate what’s actually happening,” one publisher told me during a recent working group.
That’s why ops pros need deeper fluency in data modeling and diagnostic thinking. “We approach AI as authentic intelligence—enhancing, not replacing, the human element,” Jesse Waldele, SVP of Digital Operations and Client Success at Dow Jones, recently said.
Ad ops must go beyond dashboards to understand how decision systems behave across campaigns. When teams are empowered to act on what the data shows, they can proactively optimize pacing before the end-of-month panic.
That’s how ops shift from post-mortem reporting to proactive strategy—catching delivery issues before they drag down revenue.
Prompting Like a Pro
From predictive bidding to dynamic floor pricing to creative testing, today’s ad ops teams are deploying more AI-powered tools than ever. As we learned in last year’s AdMonster report: Ad Ops Reimagined — A Guide to Reshaping Ad Ops With Generative AI, tech alone isn’t the differentiator.
The next-gen ops leader is fluent in prompt writing, model tuning, and customizing AI tools to reflect publisher logic.
It’s about creating instructions that align with internal taxonomies, campaign pacing goals, and delivery diagnostics.
In practice, generative AI is already assisting ops teams in summarizing pacing trends, explaining under-delivery, and even flagging misaligned creatives. The edge comes from tailoring outputs to match business logic.
Are you ready to speak machine?
Out of the Weeds, Into Strategic Flow
Automation clears the runway, streamlining repetitive processes like segmentation, trafficking, reporting, and bid adjustments.
It gives ops teams space to rethink strategy, tighten feedback loops, and actually fix what’s broken.
“What we’re seeing is a shift towards more strategic roles in ad ops,” Laura Boodram, CRO at FatTail, once told me. “Our clients are telling us that their teams are happier—they’re doing less grunt work and more of the creative and strategic work that drew them to this field in the first place.”
Publishers working with Theorem reaffirm this. Since introducing automation at SiriusXM, John Harris, Senior Director of Ad Technology Operations, recently told me that his team can now focus on driving revenue and improving yield. Now, they focus on optimization rather than execution.
None of these advancements would be possible without an ad ops team that understands how to integrate AI tools into existing workflows and optimize them for maximum efficiency.
Finding Your Creative Edge
AI can optimize delivery and streamline workflows, but it can’t decode the nuance of brand strategy. While AI handles the grunt work, ops teams are reviewing briefs, testing variations, and optimizing for performance in real time.
Getting there means removing the blockers—namely, the outdated asset collection and approval processes that have long plagued campaign launches.
“FatTail’s Portal enabled us to streamline asset collection and management significantly, freeing up our team for more strategic tasks,” Anne Thiel, Senior Director of Advertising & Revenue Operations at Cox Automotive, once told me. “It removed all the email communication and automated all the reminders… we saved $18,000 a month automating just this one process.”
Streamlining asset collection and management freed her team’s time for more strategic tasks. That shift—from chasing files to shaping outcomes—is what makes ops essential in creative conversations.
The Signal Keepers Are Among Us
Machine learning models are only as good as the data they’re trained on. That places ops on the frontline of data quality, governance, and privacy compliance.
And as cookies continue to crumble, publishers are taking matters into their own hands—rebuilding identity maps, defining clean room strategies, and strengthening internal controls.
“We’re doing more internal audits now than we ever have,” one publisher told me during a recent working group. “Everything from how segments are defined to how consent flows through the system—it’s all under review.”
That mindset is reshaping ad ops into the role of data steward—curating first-party assets, partnering with product and legal teams, and ensuring the data flowing into AI models is clean, compliant, and of high value. In a machine-led world, humans still control the fuel.
Learn Fast or Get Left Behind
The age of AI in ad ops isn’t about standing still—it’s about moving forward with purpose. Automation and agentic AI are raising the bar, but they are also freeing up space for ops teams to lead, innovate, and shape outcomes.
Ops pros are stepping into analyst and advisory roles. They spot the gap before the CFO does. They flag why performance dipped, even though the dashboard looks fine. They tell the story that keeps a brand invested or helps a publisher re-price inventory with confidence.
What Sets the Next Generation of Ad Ops Apart?
- The ability to prompt, interpret, and guide AI models with business logic and creative insight.
- A commitment to data quality, privacy, and ethical use—fueling trustworthy automation.
- The drive to learn fast, adapt quickly, and collaborate across teams and disciplines.
AI might be running the play, but humans are still calling the shots. The future belongs to those who step out of the weeds and into the flow of innovation.