Artificial intelligence has the potential to be more than just another tool brands and agencies use in programmatic advertising. As the technology becomes more sophisticated, AI could become more like a trusted coworker with deep expertise in finding the right audiences, optimizing campaigns and buying and selling space.
The ad industry has been using AI in certain forms for years. Machine learning, for instance, can analyze campaign data and provide insights about performance. Deep learning allows you to go even further to understand differences in demographic interests and purchase intent. Generative AI continues to make headlines based on its ability to summarize, organize and even produce content.
As marketers look to grow their impact over the next year, it’s time to look beyond the hype. We can all talk about AI until we’re blue in the face, but it won’t matter if we’re not generating results. The ideal measurement remains: are you able to use AI to drive performance and scale?
Your best bet is to start by learning more about the use cases for AI in programmatic advertising, as well as the challenges to overcome.
Generative AI and Its Practical Impact
Whether you’re shooting pictures, video or even writing campaign copy, developing campaign creative has traditionally been time-consuming and expensive. So has running A/B tests. This in turn has made it difficult to personalize advertising at scale.
Generative AI is changing that, making it fast and easy to spin out large volumes of creative assets – for example, hundreds of images instead of two or three – at nearly zero cost. That opens up a lot more room for iterating and fine-tuning campaigns to resonate more deeply.
Tools like ChatGPT and Midjourney can also improve our ability to target the right audience. You can use prompts to define groups based on specific criteria, identify pain points, provide the most relevant keywords and more.
The better AI helps you know who you’re targeting and what they want, the more likely you’ll produce higher-quality content that converts. Audiences will reward you with greater engagement and taking the desired actions, boosting return on ad spend (ROAS) in the process.
Navigating Privacy and Regulation in AI
AI has become part of programmatic advertising at a time when governments and regulators are putting a bigger emphasis on protecting consumer privacy. This includes the introduction of the EU’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), which have limited how brands and agencies can access or manage information.
For example, a device ID was traditionally a hugely important signal to track a consumer’s behaviors and predict their future actions. We can’t see those device IDs the majority of the time today on platforms like iOS, and it’s in direct response to those regulations.
Generative AI complements programmatic advertising within privacy limitations by allowing marketers to infer audience insights without direct tracking. As authorities learn more about the risks associated with training AI on large language models (LLMs) that scrape data from the open web, however, we’ll all have to monitor how the regulatory landscape evolves and stay focused on maintaining compliance.
Upskilling and Talent Development
Generative AI is powerful, but we’re still nowhere near the moment where machines handle everything. That’s why designers should study generative tools and techniques and leverage them to maximize their creative output. It’s also why you started to see a lot of people on LinkedIn calling themselves “prompt engineers,” to show they are proficient in having a conversation with these systems.
The greater priority from a talent perspective will be finding people who can combine generative AI outputs with programmatic strategies that maximize performance. Knowing how to derive insights and act on them with speed will help people with those skill sets adapt campaigns so they deliver on expectations and reduce wasted effort and expense.
Focusing on ROAS Fundamentals
Generative AI will allow us to go much deeper in terms of analytics and reporting, which is great news for anyone working in the programmatic space. I’m excited for people to have better tools to really understand incrementality and the true impact of spend.
The industry still has a lot of incentivization problems, where marketers are assessed and compensated based on how they can prove to their bosses they made the best of their spend, versus developing a strategy that drives consistent ROAS. Generative AI should be used to not only help run campaigns but evaluate real-world outcomes that lead to ongoing improvements in performance and scale.
You’re going to continue seeing a lot of bold claims and predictions about AI and programmatic advertising in 2025. Don’t get swept up in that. Instead, stay heads-down on the fundamentals of ROAS and how the technology can help refine the work you do, stay competitive in the programmatic space and contribute to greater marketing success.
Ready to stay ahead this year? Get started with LifeStreet today to leverage AI and programmatic advertising for smarter, more successful campaigns.