Artificial Intelligence (AI) is transforming various industries and businesses, and ad tech, a specialist sector where we do a lot of work driving digital advertising across digital media on mobile and connected platforms, is no exception. AI is emerging as a game-changer for ad tech, with a variety of uses that are solving problems and driving efficiencies. AI can help ad tech companies with tasks such as:
- Contextual/non-intrusive ad placement decision making
- Conversational chatbots
- Creative assembly decision making
- Measurement
- Predictive audiences
- Process discovery
- Traffic shaping
- Video Ad management & automation
According to Chinmay Abhay Nerurkar, a thought leader and Principal Software Engineer at Microsoft, “AI is revolutionizing the way ad tech operates. By leveraging ML algorithms, we can analyze vast amounts of data to identify patterns and insights about user behavior, preferences, and demographics enabling more precise audience targeting, leading to more relevant ad placements and higher conversion rates”
Chinmay has made notable contributions to the Ad Tech industry by architecting low latency ad serving systems leveraging Artificial Intelligence and has established himself as a thought leader in this domain.
AI can also enable ad tech companies to create ads using generative AI, which can produce realistic and immersive content that can be customized for different markets, channels, and users. For example, WPP, the world’s largest advertising agency, has teamed up with chipmaker Nvidia to create ads using generative AI.
However, to leverage the full potential of AI in ad tech, low latency development is critical. Latency—the time delay between an ad requests triggered by a user accessing a webpage or an app and the delivery of the advertisement—remains the enemy of ad tech, and by extension, the enemy of publishers and agencies relying on increasingly sophisticated tools to drive revenue and engage audiences.
According to Chinmay, “Low latency development is crucial in the ad tech industry. In programmatic advertising, real-time bidding and ad auctions take no longer than 100-200 milliseconds for hundreds of billions of daily ads served. We need to ensure that data travels quickly through the ad serving system for the efficient execution of these auctions, ensuring that bids are processed quickly, and the winning ad is delivered to the user within this critical time frame.”
Low latency development means reducing the time it takes for data to travel from one point to another on the internet. This can have a significant impact on the performance and user experience of ad tech platforms and applications.
Some of the benefits of low latency development are:
- Faster real-time bidding (RTB) and ad targeting: RTB and ad targeting require sub-100-millisecond response times, which means advertisers need to avoid any process that could hinder their ability to win placements. According to Chinmay, “By implementing low latency development practices, we can dedicate more milliseconds to apply predictive targeting and advanced AI algorithms to deliver superior return on advertising spend while guaranteeing a seamless ad experience for the user.”
- Better internet route optimization: Internet route optimization technologies can help ad tech companies find the fastest and most reliable path for their internet traffic, much like a real-time traffic app. This can significantly reduce latency, which can be directly correlated to upticks in revenue in the programmatic and digital ad space.
- Enhanced user experience: Low latency development can help ad tech companies deliver smoother and more engaging user experiences by reducing website page load speeds, bounce rates, buffering, and lagging. According to Chinmay “Studies have shown, as many as 40% of the users will abandon your site after page load times cross 3 seconds. User engagement metrics such as ad view ability, ad interaction rates, and click-through rates tend to decrease as ad loading times increase, impacting revenue for both advertisers and publishers. By minimizing latency, we can ensure that users have a seamless browsing experience and increase user satisfaction and retention.“
While low latency development presents technical challenges, it also raises ethical considerations. As AI evolves, Big Tech companies are being highly watched by regulators and critics to ensure that they are respecting consumer privacy and complying with laws. Chinmay emphasizes the importance of ethical AI development, stating, “AI is powerful tools that can help ad tech companies achieve new levels of innovation. As we build the next generation of ad tech solutions powered by Generative AI-powered and Large Language Models, companies must be mindful of the ethical implications and adopt best practices such as transparency, accountability, fairness, and security to build trust with users.”
