With the popularity of AI tools soaring, like ChatGPT, many wonder—what will the future of AI in adtech, and the advertising industry overall, look like? Taylor Pate, CTO of KERV Interactive, shares his thoughts on the matter in his KERV Blog debut.
There’s been a rapid rise in AI within the last decade. In fact, in the last five years alone, the ad industry has seen huge improvements in the way AI optimizes media buying, targeting, etc. We see this at every major ad exchange, even in walled-gardens like Facebook. Even though AI has been in use for several years, the last year in particular has seen a massive jump in interest. A lot of that is because AI is getting better thanks to the rise in strong neural networks.
For those not in the know, neural networks are a subset of machine learning, and key to deep learning algorithms. Humans pour in data and the neural network’s accuracy improves over time—eventually able to categorize large quantities of data at high speeds. Example: image recognition.
We’re reaching a point with AI where use cases will begin to grow and expand. From my perspective, we’ll see industry advancements through AI in adtech in three major areas:
- Ad relevance
- Ad personalization
- Automated production
Prediction 1: Stronger contextual relevance will fuel brand-consumer connections
Relevance has always been important to advertising. Even going back to the heyday of Madison Avenue with print and television ads, the more relevant the ad is to the content, the more attention it gets.
For digital, creating contextual relevance started out based on keywords, categories and tagging. Now, with today’s AI, we can go beyond just words on a page. For images and video, AI can identify objects, people, logos, then analyze those elements against the content on the screen for better ad placement. It’s the same way advertisers might choose to place a perfume ad in a fashion magazine because of the contextual relevance—but AI takes the manual work out for digital advertisers.
This level of identification and automation means more granular, accurate and consistent contextual targeting, ultimately driving better consumer experiences.
Prediction 2: More dynamic personalization will drive better consumer experiences
Generative AI systems—GPT-4 and DALL-E2, for example—are poised to achieve hyper-personalized advertising strategies.
We’re already seeing this with content creation. Tools like Jasper and ChatGPT leverage data analysis, natural language processing and machine learning algorithms to generate personalized content based on user-input prompts.
As these AI systems continue to develop, we’ll see this applied in even smarter ways. If the “old-fashioned” approach to AI in advertising focused on optimizing which creative is served to each user segment, then the new approach would focus on dynamically changing the content of the creative based on each individual user.
Prediction 3: Automated production will streamline digital ad strategies
Ad production has always been a huge lift. Going from concept to production involves large teams and significant approval processes. After all that work, you want to get as much mileage as you can from each asset produced.
With the power of modern AI, we have some options at our disposal to improve this process:
- Generate variations of existing ads
- Create audience-specific messaging/visuals
- Create context-specific messaging/visuals
- Automate multi-platform formatting (ex: 15 second vertical TikTok ad vs. 30 second CTV ad)
- Generate new ads from existing content
By leveraging AI, brands not only power faster production and approvals, they also enable management of larger sets of variations, more granular targeting strategies, and faster launches.
The adoption of AI is set to explode across industries, and AI in adtech will undoubtedly be a major trend throughout 2023 and into 2024. Stronger contextual targeting, smarter personalization and greater automation ad production will save businesses time and money all while creating better experiences for consumers.