The AI Advertising Podcast: S2
Episode 6
How AI Will Orchestrate Advertising in 2026
About This Episode
According to StackAdapt’s new report, The State of Programmatic Advertising 2026, the next phase of programmatic won’t be about incremental optimization. It will be about orchestration: unifying data, creative, channels, measurement, and AI into a single, intelligent system.
In this episode, we sit down with two industry leaders to unpack what that shift really means in practice.
Paul Verna | VP of Content, EMARKETER
Yang Han | CTO, StackAdapt
Transcript
Diego Pineda (00:00:00)
For years, programmatic advertising has evolved one optimization at a time: better bids, smarter targeting, more channels, a few more dashboards… and of course, a lot more complexity.
But in StackAdapt’s new report, The State of Programmatic Advertising 2026, a different story emerges. The next phase of programmatic won’t be about squeezing a little more performance out of each lever. It will be about orchestration—unifying data, creative, measurement, channels, and AI into something that acts more like an operating system than a collection of tools.
So today, we’re looking ahead to 2026 to unpack what’s changing, what AI is really enabling, and what the smartest marketers will do differently.
And we’ve got two incredible guests to guide us:
Paul Verna, VP of Content at eMarketer, who has one of the clearest views of how programmatic is shifting at the industry level and Yang Han, CTO and Co-founder of StackAdapt, who brings the technical lens — what has to change inside platforms for all of this to actually work.
Together, they help us unpack how AI is moving from optimization to full-funnel orchestration—and what the smartest marketers will do differently as programmatic becomes a unified, intelligent system.
Let’s dive in.
Podcast Intro (00:01:16)
Welcome to the AI Advertising Podcast, brought to you by StackAdapt. I’m your host, Diego Pineda. Get ready to dive into AI, Ads, and Aha moments.
Diego Pineda (00:01:31)
If there’s one headline entering 2026, it’s this: fragmentation is expensive. Two-thirds of marketers say up to 30% of programmatic budgets are lost because of siloed execution. And according to StackAdapt’s report, the next unlock won’t come from a single channel—but from tying them together. So, where is unification actually happening today? Here’s Paul Verna.
Paul Verna (00:01:57)
We’re seeing unified planning between commerce or retail media signals and CTV impressions. So you have the likes of Amazon, Walmart, Kroger starting to integrate off-site programmatic with on-site shopper data. And that’s important because it helps create this single optimization loop that goes from exposure to conversion. And you know, CTV and retail media happen to be the fastest growing format. So we’re seeing that convergence.
So unification is emerging in planning and reach management even if attribution is still very fragmented. Potentially we could see retail media networks announcing off-site CTV partnerships with measurable closed loop reporting. So essentially like a TV to cart kind of scenario. Another signal could be like marketers shifting budgets into what they would actually categorize as an omni channel line item instead of allocating those budgets separately to say display, social or CTV.
Diego Pineda (00:03:00)
But unification isn’t just happening in media planning. There’s a deeper shift in how programmatic platforms themselves are evolving. Here’s Yang Han with that perspective.
Yang Han (00:03:10)
I think in programmatic in the past decade, there was a lot of evolution in programmatic, right? New channels being added, you know, lot of new sources of data, a lot of new players coming into the industry. I think we’ve gotten to the point in which um a lot of the best practices and programmatic are becoming known. And it’s as we see it now in terms of where customers and platforms are gravitating towards. They now want bespoke solutions that are tailored to their vertical because when the one size fits all model is not as effective for, you know, compared to something that’s a lot more bespoke, right? That’s just the nature of things. But the downside of platforms that are only focused on one area, they don’t have the reach, they don’t have the foundation and the capabilities to be as holistic as possible. And so you kind of need to do both, essentially. So a platform like us, we started out, you know, general purpose, executing across every channel, all these different data solutions. Now what we’re building towards is now tailoring it to specific verticals. We’re putting out our e-commerce capabilities, our B2B capabilities, healthcare capabilities. travel, automotive, retail, and so forth, a lot of the fundamentals are the same. But there are differences to the end consumers that matter. And that there are differences into the measurements, into the audience strategies, into that flywheel to make it work. And so it’s very important for a system and platform to be able to differentiate that. And so I think that’s where the evolution is heading towards now, you know, you need to become regardless of your system or a person. It’s all about developing expertise now going to go deep to drive better outcomes and solutions.
Diego Pineda (00:05:06)
So while Paul sees channels converging, Yang shows us how platforms are becoming more unified and more specialized—broad enough to cover every channel, but tailored enough to deliver vertical-specific intelligence.
Diego Pineda (00:05:24)
For the past decade, AI in programmatic has mostly lived in optimization: bid shading, lookalikes, pacing, small adjustments that make campaigns smoother. But that’s not where the biggest gains will happen. In StackAdapt’s 2026 report, marketers say that AI’s largest impact areas are creative production, data management, and personalization. I asked Paul where AI will create the most visible lift this year.
Paul Verna (00:05:49)
In creative production I’m looking for the most impact to come from things like short form and CTV ready variants. So AI can handle versioning and formats and maybe some light narrative edits that lets the brand run more creative assets that are tied to audience signals without necessarily adding headcount to get that done. As far as audience and data management, I think AI can enable automated segmentation and maybe lookalike expansion. When it comes to personalization and orchestration, I think AI can start moving the needle. So dynamic creative and dynamic copy can potentially merge into a single AI decision layer. And while there isn’t really full autonomy in orchestration yet, there have been steps in that direction with things like AI generated bid strategies or recommended budget allocations or performance simulations.
Diego Pineda (00:06:51)
Paul also predicts we’ll see AI-native campaign types—not just AI “features” bolted onto legacy workflows. But here’s where Yang adds a crucial layer: AI can only orchestrate when multiple systems—or even multiple AIs—work together.
Yang Han (00:07:07)
There are a lot of opportunities for humans to really shape and make good use of AI. Because if you think about even the landscape of AI today, it’s really open-ended. There aren’t too many best practices of how to leverage AI. People are still figuring out the best ways to use AI. There’s been a lot of value people have been able to discover, but people are always discovering new use cases, new methods. The technology is evolving as well. And that requires humans to piece it together.
AI is most effective in relation to other AIs working together so that they can compound and learn from each other rather than in isolation. But it requires the human to really strategize in a creative way to piece it together and in which it actually solves the end outcome. So the role of the human shifts a bit because now it’s the same pattern whenever a new technology is introduced. Humans have to figure out, well, how do I best leverage and incorporate this technology?
Diego Pineda (00:08:07)
This is an important nuance: AI does not replace strategy, it extends strategy. The marketer’s job shifts from pushing buttons to designing the system that pushes the buttons. If 2024–2025 were the years of AI copilots, 2026 may be the year of AI conductors.
Diego Pineda (00:08:27)
StackAdapt’s report found that top performers are 4 times more likely to overhaul half their stack, not to cut tools, but to build more connected workflows. I asked Paul what consolidation signals he expects in 2026.
Paul Verna (00:08:44)
One thing we might see is a rise in Snowflake or data bricks native media products, you know like announced by DSPs DCO platforms or RMN’s. So that would kind of be a sign that warehouse is becoming more like an operating system. I also might look for language and earnings calls that shift maybe from tool rationalization to something like composable workflow adoption. So that would tell me that vendors are selling tighter integrated stacks instead of just cutting tools. And yeah, I think PG programmatic guarantee deals we might see more of those kind of bundled with first-party data guarantees, especially around that convergence between CTV and retail media.
Diego Pineda (00:09:34)
But Yang goes even deeper on why consolidation is now mandatory.
Yang Han (00:09:38)
When an industry matures, you start to see the downsides of things being disconnected, right? Once you know how to get results and perform, you are able to, and you start to realize the gaps between different systems then cause a strain and the disconnect into how intelligent a system can be. For example, the reality is an AI doesn’t have access to it as much data as possible. It only has access to a summary of data from another platform.
That AI’s intelligence is dramatically limited. So if we think about it from the viewpoint of AI, if we believe AI has the power to leverage data and control of systems to be as intelligent as possible, well, you have to give them that direct control. And when everything is holistic, in one platform in which the AI has as much control and as much access to information as possible, that’s when it can become the most intelligent. That’s why I think as things get streamlined, as solutions get figured out end to end, you want things housed into one and so there’s no friction. Systems and AI can execute and learn seamlessly as quickly as possible, as efficiently as possible.
Diego Pineda (00:10:50)
In other words: Fragmentation was useful for innovation. Consolidation will be essential for intelligence. And both guests agree on one surprising exception: Creative strategy should not be consolidated. It needs independence to counter platform incentives and to stay genuinely creative.
Diego Pineda (00:11:13)
One of the major findings in The State of Programmatic Advertising 2026 is that the strongest performers are moving aggressively into channels that used to be considered experimental: digital out-of-home, audio, in-game, and even programmatic direct mail. I asked Paul which channels will truly “graduate” into full-funnel work.
Paul Verna (00:11:33)
I think of in-game and audio is already being, you know, mainstream formats and and they have kind of bridged that continuum between upper funnel and and more conversion type outcomes. But the ones, you know, I find um programmatic direct mail particularly interesting and programmatic digital out of home. So direct mail is rising fast because it plugs directly into that first party data and the churn models and things like card abandon workflows. But it’s just really interesting when you look at those digital signals and you put them into a situation where like you’re actually getting something in your mailbox like a physical object. I think that’s kind of interesting, programmatic digital out of home. I think it’s gaining real distribution and there’s more automated buying um even some closed loop attribution via mobile and retailer data. So that’s kind of like moving it from upper funnel to full funnel activation.
Diego Pineda (00:12:33)
StackAdapt’s platform data shows that first-party audiences deliver more than twice the ROAS than third-party data.
So, how should advertisers rethink data quality and data design, especially as AI becomes more embedded into programmatic advertising?
Paul Verna (00:12:49)
The performance gap tells us that AI doesn’t magically fix weak inputs. it just amplifies them. First party data works better not just because it’s proprietary, but because it’s more accurate, it’s better labeled. It’s more closely tied to real business outcomes. So, as AI becomes more embedded in that buying process, the competitive edge shifts from who has the most data to who has the cleanest, most connected data. So advertisers should rethink data design as an operating system not as a media tactic. So that means investing in ID resolution in consistent taxonomies in feedback loops that connect exposure to LTV. AI models work best when they can learn continuously from outcomes. So that the brands that win are actually the ones that are designing data for learning, not just for targeting.
Diego Pineda (00:13:50)
I asked Paul where he sees AI impacting advertising the most in 2026. This is what he said.
Paul Verna (00:13:56)
I would have to say AI becomes more pervasive in every aspect of the digital advertising value chain from creative ideation to targeting to optimization to measurement. And even if there’s an AI bubble, that won’t stop this technology from continuing to work its way into the day-to-day work of ad buyers, ad sellers, and intermediaries. So, I think that is definitely a, you know, what I would call that out as like a winner. And as far as like the signs that we might see, basically just every company that is using AI to, you know, create or serve or measure ads, like we’re going to just start to see them dig a little deeper into um trusting AI to make the right decisions in an automated way.
Diego Pineda (00:14:50)
Now, what do leaders need to do to prepare? Yang’s answer was pragmatic.
Yang Han (00:14:55)
The worst thing you can do is think of AI as just a general black box that will solve all your problems automatically. That’s not how it works. You really have to understand what it’s good at, where to best place it, and why exactly it can solve these problems and how we’ll essentially piece together and work because as I mentioned earlier it’s really about how you put together these solutions to send an outcome and to do that very well you really have to dig deep into the details of how information flows in and out how one AI agent is going to be able to take one set of information leverage that generate a very positive outcome and output for the next system and whatnot so it’s fundamentally it’s true with a lot of other different systems. It’s being able to truly understand the details and the value that gets delivered and why.
Diego Pineda (00:15:47)
Yang also stressed something that often goes unsaid: AI cannot be rushed. Platforms need years of data foundations, pipelines, and flywheels to support real orchestration.
So, Paul gives us the market signals. Yang gives us the architectural requirements. Together, they outline the roadmap for marketers who want to win in 2026.
Diego Pineda (00:16:15)
If we zoom out, the story of programmatic from 2015 to 2025 was about expansion — new channels, new data, new tools, new vendors.
But the story of 2026 and beyond will be about convergence.
A world where AI operates across the entire funnel…
Where unified planning replaces siloed buying…
Where vertical-specific intelligence becomes a competitive edge…
And where the programmatic stack behaves less like a collection of tools and more like a Programmatic Operating System.
If you want to go deeper, download StackAdapt’s full report, The State of Programmatic Advertising 2026 at stackadapt.com. It’s packed with insights, benchmarks, and predictions that can help you build your strategy for the year ahead.
Podcast Outro (00:16:59)
Thanks for listening to this episode of The AI Advertising Podcast. This podcast is produced by StackAdapt. Visit us at stackadpat.com for more information about using AI in your advertising campaigns. If you liked what you heard, remember to subscribe, and we’ll see you next time.
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