Why AI integration is the key to amplifying its value

Illustration of a robotic hand giving a thumbs up with the word “GOOD!” on its display, symbolizing the positive impact of AI integration in ad tech.

Karim Rayes, Chief Product Officer, Nexxen

Artificial intelligence has quickly become the ad tech industry’s favorite talking point, and understandably so. Nearly every company is racing to launch AI-powered products, from generative creative tools to predictive models and automated campaign recommendations. But amid the buzzwords and marketing decks, a more important question is overlooked: Is the industry building AI as a transformational amplifier, or is it just adding another shiny feature?

Recently, it has largely seemed to be the latter. Many AI rollouts in the space operate in isolation — an algorithm that suggests optimizations, a chatbot for support, a dashboard that generates summaries. These may sound helpful — and often they are — but their impact is limited unless they’re connected to the systems and workflows that allow AI to learn and improve over time.

That’s where end-to-end platforms have a distinct advantage — not just in how they deploy AI, but in how they create the conditions for it to work effectively. These platforms are more than a suite of branded tools; they are integrated systems where each component communicates with the others, and that interconnectedness is critical. For AI to deliver meaningful impact in ad tech, it has to connect — and enhance — each core aspect of an offering, thus enabling continuous feedback and adaptation.

System-wide AI is unlocking insights and value for various stakeholders

Within an end-to-end environment, AI can ingest real-time data across planning, activation, optimization and measurement. It can analyze which audiences are responding, which creatives are converting and how supply dynamics are shifting — not in isolation, but in context. These insights are not only observed; they’re fed back into the system to improve the next decision, the next activation, the next bid. That’s where the magic happens: A closed-loop cycle where performance drives learning, and learning drives better performance.

For example, marketers can use AI to dynamically adjust audience targeting based on in-flight campaign performance, reallocating spend toward segments with the highest engagement or conversion rates. Creative optimization engines can automatically test and rotate ad variations, identifying which messages resonate most with different audience cohorts in real time. On the supply side, publishers can use AI to predict inventory value, bundle premium audiences and fine-tune yield strategies, improving both fill rates and CPMs. Even measurement benefits: AI can connect cross-channel attribution data to inform future media buys and creative strategies, reducing waste and improving ROI.

This kind of system-wide intelligence doesn’t just create efficiencies — it drives competitive advantage. Marketers gain speed and precision, publishers unlock new revenue opportunities and the entire ecosystem moves closer to true performance-driven advertising.

Treating AI as essential infrastructure will set organizations apart

Of course, building this type of AI infrastructure isn’t easy. It requires ownership — or at the very least, deep integration — across the media supply chain. It demands a unified data strategy, interoperable systems and a mindset shift from feature deployment to capability development.

Organizations that want to integrate AI effectively need to start by breaking down data silos, enabling first-, second- and third-party data to flow seamlessly across their systems and through their pipes. They need to align teams across product, data and operations, ensuring that AI initiatives focus on solving core business problems, not just creating flashy moments. Perhaps most critically, they need to embrace an iterative mindset. AI integration is not a one-time project, but an ongoing journey of testing, learning and refining. Those who build this continuous improvement loop into their infrastructure will be the ones who not only keep pace with change, but help define where the market goes next.

This is an inflection point in ad tech. AI isn’t just another wave of innovation; it’s a foundational shift, akin to the arrival of mobile or identity graphs. The companies that treat AI as core infrastructure, rather than another add-on, will be best positioned to lead. And the platforms that are built to work together will have a massive head start, not because they have AI, but because they have the architecture to make AI matter.

The future of advertising isn’t just AI-enabled; it’s AI-connected. And it’s already underway. 

Sponsored by Nexxen

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