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AI in Ad Tech: Cutting Through Hype & Harnessing Potential

AI

“AI Mania” is in full swing across every possible industry – and adtech is no exception. There’s a strong appetite for AI to enhance campaigns, optimize creatives, and improve audience targeting. This frenzied moment is also fueled by growing fears about job displacement, privacy issues, and potential misuses. But let's cut through the hype and see what's really going on with AI.

AI Breakdown: What's What

First off, let's clarify what AI is. Artificial intelligence is used by many technologies with the hopes of helping machines learn, adapt, and mimic human-like smarts. Here are the leading AI types:

  • Narrow AI: Also called weak AI, it’s about doing specific tasks like speech or image recognition. It doesn't have general human-like intelligence. It’s the most common AI type currently in use and there are a few subtypes that are most common in ad tech:
     
    • Natural Language Processing (NLP): A branch of AI that focuses on the interaction between computers and humans using natural language. Examples of NLP applications include chatbots, virtual assistants, and language translation software. ChatGPT is NLP as it’s based entirely on text and language inputs/outputs.
     
    • Recommendation Systems: These provide personalized recommendations to users based on interests and behaviors. Examples include product recommendation engines used by e-commerce websites and streaming platforms. A famous model is Google's search algorithm, which uses machine learning to continually improve its search results and recommend specific links based on previous search history or user profiles.
  • General AI: Now, this type of AI is more like what you see in sci-fi movies. It's all about a machine's ability to understand, learn, and perform any intellectual task a human can do. It's primarily theoretical, but would be a game-changer if it becomes a reality. We don't have any actual general AI yet, though. Repeat: General AI does not exist today in any form.

Proceeding with Caution in AI-Driven Adtech

AI's potential to transform the ad industry is amazing, but let's not get carried away. Current AI tools can't quite grasp context, nuance, and creativity – crucial aspects in crafting compelling ads. For instance, AI can spot trends and analyze data, but it might struggle with understanding human emotions or cultural subtleties, leading to ads that are nonsensical or inappropriate.

My advice? Be a little skeptical of anything claiming to be entirely AI-driven. In reality, most tools today mix rules-based decision-making, data mining, and benchmarks. Don't let the AI hype and headlines trick you into thinking you're behind. The truth is: while AI is exciting and carries great potential, it’s not quite ready for action in the way that eager platforms and sales teams might try to convince you it is. Before diving into AI-driven solutions, carefully evaluate the tech's maturity and capabilities to make sure it lines up with your campaign goals and gets the results you want without compromising quality.

The Promising Future of AI in DCO & Ad Serving

Innovid's latest real-time offering, Instant Optimization, is a first step towards this AI-enabled future in TV advertising. Using KPIs from InnovidXP — such as website visits, app downloads, or on-site purchases — advertisers can effortlessly shift their focus to high-performing ads, enabling the platform make real-time adjustments that significantly improve digital performance. Instant Optimization uses machine learning to ensure that the most effective ads gain the largest share of voice, optimizing your ad serving strategy without requiring human intervention — all without interfering with your existing media optimization tools.

That's just the beginning. The future of AI applications in dynamic creative optimization (DCO) and ad serving is genuinely exciting. As AI technology advances, it's poised to reshape the ad industry in several ways:

  • DCO: Imagine AI automatically tweaking creative elements to boost performance, selecting KPIs, or even switching between KPIs mid-campaign based on your broader business objectives. Sounds cool, right?

  • Rapid Creative Iteration: One day, AI-driven tools might be able to iterate on existing creative concepts, letting advertisers experiment and adapt campaigns to keep up with audiences’ ever-changing tastes. More safety mechanisms are needed to make this a reality, but the promise of near-instant creative iteration is easily one of the most exciting AI applications for our industry.

  • Predictive Modeling: AI could use predictive modeling to anticipate consumer behaviors and trends, allowing advertisers to stay one step ahead of the competition. Imagine not only considering users’ previous browsing activity, but every touchpoint they have had with your brand, whether through a website, linear spot, email, app, or social post. Perhaps the boldest way AI could revolutionize traditional ad serving is by taking the user’s full experience into account for every impression delivered. This could have massive implications for frequency management and sequential storytelling across devices, platforms, and channels. It could even rewrite marketers’ long-held assumptions about engaging with audiences in the “right place” at the “right time.” Think of audience and media curation targeted toward cohorts of behaviors (e.g. a group with a propensity to investigate online vs in-person, another that prefers to interact with ads vs. watch passively, or one that is more likely to search after ad exposure).

In Summary

The world of ad tech is on the cusp of a revolution driven by advancements in AI. As we navigate this exciting new frontier, it's essential to approach AI with a balance of enthusiasm and caution. By understanding its current capabilities and limitations, and thoughtfully evaluating the potential applications, advertisers can leverage AI to create more effective, engaging, and personalized campaigns. As AI technology continues to evolve, its role in informing creative messages, moment-of delivery, and holistic user modeling will undoubtedly reshape the advertising landscape, opening new possibilities for innovation and success. In the meantime, keep your eyes on the AI-sky and your feet on the adtech ground.