Prediction Over Reaction: Why Omni’s CEO Thinks Marketers Must Decide Before They Spend
Marketing AI promises the ability to know whether a campaign will work before a single dollar leaves the budget. That shift, from reactive measurement to predictive decision-making, is reshaping how brands approach an increasingly fragmented media landscape.
The challenge is that fragmentation keeps compounding. Social platforms, retail media, AI-powered search, and now agentic AI assistants have all created new surfaces where consumers can be reached – but each one adds complexity to understanding whether the right message is landing with the right person at the right time.
“We are in a fragmented ecosystem, which we kind of always have been, but we’re continuously adding channels and areas to reach consumers,” said Christine Gambino, CEO of Omni, Omnicom Media’s AI-driven marketing intelligence platform, in this video interview with Beet.TV. “We’re adding in AI agents now, we’re adding in social more than we have in the past. These different channels is a different way to reach consumers than we have.”
Identity as the connective tissue
The proliferation of channels has made identity resolution more critical than ever. Without a persistent way to recognize consumers across touchpoints, marketers risk duplicating reach, misattributing outcomes, and losing sight of the full customer journey.
Omnicom Media’s answer is to anchor its platform on Acxiom’s Real ID, which the company says spans 2.6 billion verified global identities. That identity spine connects upstream planning to downstream activation, creative, commerce, and measurement. In January, Omnicom Media unveiled the next generation of Omni, describing it as an AI-driven operating system that integrates those capabilities with trillions of signals and $73.5 billion in annual buying power.
“One of the things on its importance is that we have the ability with Omni to take our Acxiom data, which is our real ID and our connected data structure, and be able to tie that all the way through to our connected capabilities,” Gambino said. “That allows us to really kind of hone in and bring the consumer further up funnel. Our brands want to understand that consumer mind more than ever.”
From attention to prediction
Industry observers have begun describing a shift from an attention economy to a prediction economy. The underlying idea is that marketers are moving beyond simply capturing consumer attention toward anticipating behavior and outcomes before campaigns launch.
Gartner forecasts that worldwide spending on AI platforms and models will reach $64.3 billion in 2026, up 63% from the prior year, with spending on domain-specific and specialized generative AI models growing 210%. That investment is fueling the integration of predictive, generative, and agentic AI into marketing workflows.
“Predictive AI has been out for a while, so it’s not necessarily a new concept,” Gambino said. “But I think what is new is the ability to bring it all together. So your machine learning models tied to your generative AI, tied to your predictive AI. When you’re able to tie all of these together with a frontier model on top of it, really driving it through natural language, you have the ability to start to really drive to and process data more than we ever have in the past.”
Outcome and equity in balance
The pressure to prove performance has intensified as more media is optimized by platform AI. IAB’s 2026 State of Data report highlights the measurement challenge: privacy regulation, signal loss, walled gardens, and fragmented commerce journeys make it harder to connect exposure to sales or brand impact.
Gambino argued that marketers need to balance short-term performance with long-term brand health. Optimizing purely for conversion can erode brand equity, while ignoring performance makes it difficult to justify spend. The goal, she said, is to connect both.
“We also want to make sure we have the mix of outcome and brand awareness,” she said. “Being able to tie those two together so that you are understanding the performance of your actual dollar spent, but also ensuring that you’re not eroding your brand equity to be able to capitalize on that performance. And being able to tie those things together is what makes Omni so unique.”
Deciding before spending
The practical implication of predictive AI is that marketers can increasingly model outcomes before committing budget. That represents a departure from the traditional cycle of spending, measuring, and optimizing after the fact.
Gartner predicts that by 2028, more than 70% of global ad spend will flow through self-serve advertising platforms where AI materially influences media buying, cost, and outcomes. That trajectory makes independent connected intelligence, identity, and outcome measurement more valuable as marketers navigate environments where platform AI shapes delivery and pricing.
“I think that is really why we’re able to move more from the reactive concepts, your regression models, etcetera, and more into that proactiveness to really make sure that am I going to drive the outcome I expect for my brand and doing so before I spend a single dollar,” Gambino said.
“And I think that’s what is going to be the difference now than what we’ve had in the past.”
Marketing AI promises the ability to know whether a campaign will work before a single dollar leaves the budget. That shift, from reactive measurement to predictive decision-making, is reshaping how brands approach an increasingly fragmented media landscape.
The challenge is that fragmentation keeps compounding. Social platforms, retail media, AI-powered search, and now agentic AI assistants have all created new surfaces where consumers can be reached – but each one adds complexity to understanding whether the right message is landing with the right person at the right time.
“We are in a fragmented ecosystem, which we kind of always have been, but we’re continuously adding channels and areas to reach consumers,” said Christine Gambino, CEO of Omni, Omnicom Media’s AI-driven marketing intelligence platform, in this video interview with Beet.TV. “We’re adding in AI agents now, we’re adding in social more than we have in the past. These different channels is a different way to reach consumers than we have.”
Identity as the connective tissue
The proliferation of channels has made identity resolution more critical than ever. Without a persistent way to recognize consumers across touchpoints, marketers risk duplicating reach, misattributing outcomes, and losing sight of the full customer journey.
Omnicom Media’s answer is to anchor its platform on Acxiom’s Real ID, which the company says spans 2.6 billion verified global identities. That identity spine connects upstream planning to downstream activation, creative, commerce, and measurement. In January, Omnicom Media unveiled the next generation of Omni, describing it as an AI-driven operating system that integrates those capabilities with trillions of signals and $73.5 billion in annual buying power.
“One of the things on its importance is that we have the ability with Omni to take our Acxiom data, which is our real ID and our connected data structure, and be able to tie that all the way through to our connected capabilities,” Gambino said. “That allows us to really kind of hone in and bring the consumer further up funnel. Our brands want to understand that consumer mind more than ever.”
From attention to prediction
Industry observers have begun describing a shift from an attention economy to a prediction economy. The underlying idea is that marketers are moving beyond simply capturing consumer attention toward anticipating behavior and outcomes before campaigns launch.
Gartner forecasts that worldwide spending on AI platforms and models will reach $64.3 billion in 2026, up 63% from the prior year, with spending on domain-specific and specialized generative AI models growing 210%. That investment is fueling the integration of predictive, generative, and agentic AI into marketing workflows.
“Predictive AI has been out for a while, so it’s not necessarily a new concept,” Gambino said. “But I think what is new is the ability to bring it all together. So your machine learning models tied to your generative AI, tied to your predictive AI. When you’re able to tie all of these together with a frontier model on top of it, really driving it through natural language, you have the ability to start to really drive to and process data more than we ever have in the past.”
Outcome and equity in balance
The pressure to prove performance has intensified as more media is optimized by platform AI. IAB’s 2026 State of Data report highlights the measurement challenge: privacy regulation, signal loss, walled gardens, and fragmented commerce journeys make it harder to connect exposure to sales or brand impact.
Gambino argued that marketers need to balance short-term performance with long-term brand health. Optimizing purely for conversion can erode brand equity, while ignoring performance makes it difficult to justify spend. The goal, she said, is to connect both.
“We also want to make sure we have the mix of outcome and brand awareness,” she said. “Being able to tie those two together so that you are understanding the performance of your actual dollar spent, but also ensuring that you’re not eroding your brand equity to be able to capitalize on that performance. And being able to tie those things together is what makes Omni so unique.”
Deciding before spending
The practical implication of predictive AI is that marketers can increasingly model outcomes before committing budget. That represents a departure from the traditional cycle of spending, measuring, and optimizing after the fact.
Gartner predicts that by 2028, more than 70% of global ad spend will flow through self-serve advertising platforms where AI materially influences media buying, cost, and outcomes. That trajectory makes independent connected intelligence, identity, and outcome measurement more valuable as marketers navigate environments where platform AI shapes delivery and pricing.
“I think that is really why we’re able to move more from the reactive concepts, your regression models, etcetera, and more into that proactiveness to really make sure that am I going to drive the outcome I expect for my brand and doing so before I spend a single dollar,” Gambino said.
“And I think that’s what is going to be the difference now than what we’ve had in the past.”
