• by Laurie Sullivan , Staff Writer @lauriesullivan, March 3, 2025

There are concerns that brands could become completely disconnected from consumers who use AI agents to shop across retail media networks and the web. Paid media and search, along with search engine optimization, are likely to experience the biggest shift.

Data & Programmatic Insider (DPI) caught up with Jim Yu, BrightEdge founder and CEO, one of the most knowledgable experts in SEO. What follows are excepts of what he shared. 

Data & Programmatic Insider:  What happens when AI agents start selling to AI agents for consumers?  

As AI agents evolve to take on roles such as comparing options and finalizing transactions, we will see more streamlined transactions in terms of efficiency and speed of purchase.

I also think other benefits for the consumer lie around better and more personalized recommendations. I think this will also help consumers get more precise answers and product matches based on specific intent-based interactions, especially as AI agents become exponentially better over time. And let's not forget that an AI agent is a 24/7 service, so the concept of traditional business hours kind of flies out of the window. 

In terms of business implications, brands could worry that they will become increasingly disconnected from direct consumer interactions and customer relationship models. On the other hand, some may offset that with the fact that AI agents significantly reduce costs. Balancing that with the human touch and interaction is definitely a conundrum many will have to solve for.

Also, take into consideration the emergence of new AI marketplaces where businesses could hire out their agents for consumers. This could be a whole new ecosystem that builds out over the next few years, so it's one to watch!

The curve ball here lies in privacy and data transparency. Like any technology -- success lies with the consumer and their trust and confidence (ie, accuracy), and human oversight must be part of that equation.

DPI: How does advertising and marketing work at this point?

Yu: In terms of the overall impact on advertising and marketing, I think it's going to be quite profound. Personalization, as I mentioned before, is a big part of that.

An agent is only going to be as good as the data that feeds it, so the ones that will win need to have that -- think audience demographics, behavior, preferences, demographics, and so forth. If they do that well, then I could see them automating and building out custom landing pages for different types of users and so forth, which is automation based on automation. 

You then need to look at things like efficiency from that automation and one step further -- emails, social posts, and performance measurement. Agents will get more predictive -- i.e., Salesforce Einstein can identify key trends and predict which deals are likely to close, optimizing customer interactions.

A future consideration point of debate here could be around the overall democratization of advertising techniques. That means smaller players will be able to compete with the large powerhouse brands, which is a new competitive dynamic we will see evolve.

DPI:  How will brands distinguish AI agents from spam bot on their websites?

Yu:  A great question -- a catch-22, as brands want to make sure they are found, cited, and are part of any AI agent conversation (especially as the number of them grows). But at the same time, security is such an important, topical, and sensitive subject.

The key here lies in detection techniques, which are also advancing all the time. This can be based on behavioral analysis to identify agents and spot if answers are actually too quick for a human reader or repetitive and don't align with typical user behaviors.

Going more technical, there are things like network and device fingerprinting -analysis of TLS or JA3 fingerprints to identify unusual configurations often used by bots.

There are also ways to look at and examine IP ranges and user-agent to track the agent's data origins.

And good AI itself helps detect bots -- especially advanced machine-learning models that are specifically built on large databases or genuine browser data so they can spot anomalies – which could mean a bot. There is a whole range of methods here, including authentication certificates, traffic and API monitoring, and log file analysis.

Overall, the best way to detect is to deploy a multi-layer of methods, as I mentioned above.

The challenge is for brands to stay on top of this and adapt, adapt, and adapt more as AI agents will.