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In the ever-evolving world of digital advertising, programmatic has proven to be a reliable mainstay—and a dynamic space for innovation.
Despite overall ad spending forecasts suggesting slower growth ahead, programmatic advertising remains a bright spot, with global spend reaching $595 billion in 2024 and projected to approach $779 billion in 2028. In the US, it has accounted for more than 90% of digital display ad dollars since 2023 and is forecast to see double-digit growth through 2026.
Expanding opportunities in retail media, contextual targeting, AI, social search, and beyond are creating new programmatic possibilities, offering the potential for more precise targeting, greater efficiency, and deeper connections with consumers. Yet, challenges persist. Signal loss continues to be a pressing concern, despite Google reversing its plans to deprecate third-party cookies in Chrome and instead allowing users to “make an informed choice” when browsing. And low quality AI-generated and made-for-advertising (MFA) content has further complicated advertisers’ efforts to ensure effective and meaningful ad placements in suitable environments.
As the industry navigates both the challenges and opportunities at hand, staying informed on the latest programmatic trends will be critical for maximizing the potential of these advancements. The ability to integrate new innovations into existing strategies, while also balancing this innovation with practicality, will define success in 2025.
What a difference a year makes. Headed into 2024, advertisers were bracing themselves for an imminent spike in signal loss, with Google planning to deprecate third-party cookies in Chrome by year’s end. Coupled with the previous loss of Firefox and Safari data and increasing privacy-minded regulations, most teams were preparing for the shift by exploring alternative targeting and measurement solutions.
Then, of course, Google walked back its formal cookie deprecation plans, pivoting instead to a user “opt-in” approach that’s set to take place sometime in 2025. And while it’s no longer the “D-Day” many in the marketing world had feared, signal loss will only continue to increase in the months and years ahead.
To continue to adapt to a (mostly) cookieless world in 2025, advertisers must focus on strengthening their first-party data strategies, ensuring data is collected and organized in a clean and accurate way. This is an especially pressing need, given that marketers cited data quality and accuracy as the leading challenge to meaningfully leveraging data in the years ahead. Maintaining large, clean pools of first-party data will allow teams to personalize and target ads based on individual users, use look-a-like modeling to tap into new audiences, effectively retarget ads, and leverage data clean rooms to enrich and extend their data, thus optimizing their programmatic campaigns and driving performance in a privacy-first environment.
Beyond prioritizing first-party data strategies, teams can implement other privacy-friendly targeting and attribution tactics within their programmatic campaigns, including contextual targeting and geotargeting, alternative identifiers like RampID and UID 2.0, additional use of premium and curated inventory, and media mix modeling for measurement. Given that less than 20% of consumers say they always accept when given the opportunity to opt into cookies, adapting to signal loss now—rather than clinging to cookies until the bitter end—will position advertisers for success in the year ahead.
Contextual targeting is experiencing a renaissance and renewed interest, propelled by both signal loss and new AI-driven opportunities.
As signals from third-party cookies continue to decline, using context to connect with consumers in relevant ways will grow increasingly important. Research shows that 72% of consumers feel the content surrounding an ad can influence their perception of it, and 60% report they are likely to remember a contextually relevant ad. As the programmatic space evolves, leveraging the power of contextual is becoming increasingly essential for effective audience engagement.
Additionally, advancements in AI are taking contextual targeting to new heights. Large language models (LLMs) enable advertisers to parse vast amounts of data and make placements with even greater precision than they could have in the past. For instance, in the digital audio space, these models can now be used analyze large datasets (such as podcast transcripts) to deliver highly relevant ads. This ability to drill down to such a precise level of content opens up new opportunities for more personalized, impactful ads.
To make the most of contextual advertising in 2025, advertisers need to focus on deeply understanding their audiences to ensure they are advertising in the most precise and relevant contexts. Though contextual targeting doesn’t rely upon personal data, first-party data can be used to enhance it: Some platforms allow teams to leverage this data to identify patterns in how and where audiences consume content and to then use those insights to inform contextual targeting parameters. Additionally, teams can embrace AI-powered advancements to improve their contextual strategies, utilizing newer tools that allow for more granular and dynamic ad placements.
While forecasts call for robust growth in the programmatic space, much of that growth is being powered by direct and private paths to publishers, rather than spending on the open exchange. In the year ahead, more than 91% of total US programmatic display ad spending will go towards private marketplaces (PMPs) and programmatic direct. And though spending on the open exchange will only increase by approximately 3% in 2025, PMP spending is expected to grow by nearly 13%.
This shift reflects a growing focus on inventory quality and curation, with advertisers turning to PMPs and direct buys to ensure greater transparency and precision over their media buys. These more controlled environments offer access to premium placements and the ability to bolster their own data with publishers’ proprietary data, thus enabling more precise targeting in a privacy-conscious era. They also help mitigate the risks of wasting ad spend on low-quality sites, which has become a growing concern. With MFA impression volume increasing by 19% YoY in 2024, there is a pressing need to ensure ad spend is going to high-quality inventory. By prioritizing PMPs and direct buys, advertisers can safeguard their budgets, reach key audiences, enhance campaign effectiveness, and deliver meaningful engagement in 2025 and beyond.
In 2025, programmatic non-video ad spending is projected to reach $65.21 billion in the US. Programmatic video ad spending, on the other hand, will surpass $110 billion, accounting for nearly 75% of new programmatic ad dollars from 2024 through 2026. Though this surge in video spending is not necessarily a new trend, recent AI-driven tools and enhancements present new opportunities in the space.
Advancements in dynamic content creation and enhanced contextual targeting capabilities, in particular, hold significant potential. Though contextual targeting has long been a key tactic within video advertising (think: running home improvement store ads within HGTV programming), LLMs are making it even more impactful. Since these models can process huge amounts of information and data rapidly, they can be used to analyze and categorize video content more precisely—down to the individual scenes in TV shows. Generative AI is also powering dynamic content creation in the video space, allowing teams to personalize ads to individual viewers without having to create variations manually. For example, a travel commercial could be dynamically adjusted to feature destinations that are family-friendly or adults-only based on a viewer’s preferences and viewing habits, or a car commercial could be altered to match the tone of the content a viewer is watching—lighter for a comedy, or more serious for a drama. By embracing these AI-driven tools, teams can ensure their video ads are personalized, impactful, and effective.
The search landscape is undergoing a profound transformation, driven by the rise of social search and AI-powered chatbots. In fact, by 2026, traditional search engine volume is predicted to drop by 25% as tools like AI chatbots and other virtual assistants become more mainstream. This shift will undoubtedly impact programmatic search and available inventory, and marketers will need to adapt to new, evolving platforms to maximize their search spend.
Social search is rapidly growing, especially among Gen Z and millennials. These younger audiences are increasingly turning to platforms like Instagram, TikTok, and YouTube to explore products, services, brands, and ideas, rather than traditional search engines. This shift marks a significant change from older generations, who still overwhelmingly rely on search engines as their primary discovery tool.
As such, advertisers will need to rethink how they allocate their programmatic budgets and, specifically, how they balance traditional search with social platforms’ native search functionalities. This shift will require advertisers to refine their targeting strategies, tapping into new opportunities for engagement and discovery while ensuring they’re meeting those consumers where they are spending time and seeking out new information.
Meanwhile, AI-powered chatbots and search engines are reshaping how people find information. Google’s AI overviews now often place AI-generated answers first when users search the web, and OpenAI recently rolled out a search feature that is embedded within its existing GPT framework. With 61% of Gen Z and 53% of millennials saying they are using AI tools in place of search engines, marketers face new challenges in reaching audiences.
As AI tools become a more widespread (and, perhaps, preferred) search method, it’s likely that monetization opportunities will decrease for traditional search inventory. For programmatic search, this could mean a shift in how and where ads are placed, as new search experiences like conversational search evolve. While these shifts have yet to provide meaningful opportunities for programmatic buys within AI search tools, advertisers will need to stay agile and explore alternative inventory within AI-driven environments as they become available. This could include experimenting with branded content, sponsored responses, and other AI-powered advertising solutions that align with the conversational nature of these platforms.
In 2024, programmatic retail media display ad spending grew by 41.7%, and it’s projected to leap another 29.3% in 2025. By 2026, RMN spending is forecast to exceed $30 billion, representing nearly 16% of all programmatic display. This surge is driven in large part by the wealth of consumer data that retailers hold, as well as new partnerships that make this data more actionable for advertisers. Major retailers are increasingly partnering with adtech platforms, enabling advertisers to leverage robust customer data to create highly personalized and effective programmatic campaigns.
Take, for instance, the partnership between LiveRamp and supermarket chain Albertsons. By leveraging LiveRamp’s robust identity framework, Albertsons can connect and analyze their first-party data to paint a fuller picture of the consumer journey across multiple touchpoints. This data is then connected to other advertising platforms through secure data clean room integrations, allowing for seamless activation and meaningful measurement. This approach allows advertisers to deliver highly targeted, personalized campaigns using rich retailer data—all while maintaining privacy standards.
This type of collaboration signals a growing trend of retailers and adtech companies working together to unlock new, privacy-conscious opportunities in the programmatic space. However, retail media isn’t without its challenges. Before diving into retail media, advertisers must first ensure their own data is clean and organized, and then carefully vet potential partnerships to ensure the media networks with which they’re partnering also have clean, reliable data and that they adhere to privacy-compliant practices. And, given that many of these media networks are walled gardens, advertisers must also navigate the complexities of data integration and ensure they can still measure campaign performance across these closed and deeply fragmented ecosystems. As these media networks expand, advertisers will need to adopt a flexible, data-driven strategy to utilize them while ensuring appropriate transparency and privacy compliance.
Artificial intelligence has always been foundational to programmatic advertising: Machine learning powers real-time bidding (RTB), enabling split-second decisions on ad placements based on available data, and other types of AI are critical to optimizing bids, targeting ads, and measuring performance. However, in 2025, it’s generative AI that’s dominating the conversation.
If 2024 was defined by advertisers’ experimentation with generative AI’s capabilities in programmatic, then 2025 will likely be defined by advertisers meaningfully investing in and implementing the technology. Though 92% of advertising agencies say they currently use the technology in some capacity, only 44% of marketers and advertisers say their employers currently pay for such tools. This disconnect between usage and investment signals an opportunity for marketing teams to close the gap and fully harness generative AI’s potential.
Whether by enhancing contextual targeting, automating manual tasks, generating ad variations for better personalization, analyzing large datasets, or assisting with media buying strategies, generative AI enables teams to unlock new levels of creativity and efficiency in programmatic. And, by freeing up marketers to focus on high-level strategy and problem solving, it can help reduce burnout (a challenge that has long plagued the industry). Of course, simply investing in these tools won’t guarantee success, especially given the risks that come along with gen AI. A strategic approach—prioritizing tools that align with organizational goals and ensuring a clear plan for implementation, training, and managing risk—will be essential for realizing their full potential in 2025 and beyond.
From tackling challenges like signal loss and low-quality inventory to embracing opportunities in video, retail media, and contextual targeting, advertisers are poised for an exciting yet complex year ahead. By embracing key programmatic trends and maintaining adaptability, marketers can optimize their programmatic ad spend and create meaningful, personalized connections with audiences—ultimately driving high engagement and results.
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Searching for deeper insights into the trends set to shape advertising in 2025? Our report, Reality Check: The 2025 Advertising Trends Report, breaks down the key innovations and opportunities to watch in the year ahead.