AI is the Next Generation Ad Channel. Here’s How Brands Must Get Ahead

When OpenAI brought in advertising leadership in late March, it signaled that monetization was imminent. Days later, ChatGPT confirmed the rollout of ads, marking a rapid shift from experimentation to execution.

At the same time, artificial intelligence platforms are moving earlier in the customer journey. Consumers now use large language models (LLMs) to research products and shape preferences before they ever reach search engines or retailer sites. By the time they enter traditional channels, much of their intent is already formed.

This creates a new tension for brands. Retail media still drives measurable performance and cannot be deprioritized. However, AI is influencing decisions in environments where brands have little visibility into what's driving those choices.

Brands are now caught between where performance happens and where influence is growing.

As AI platforms evolve into advertising channels, brands must balance both without overcorrecting. That means sustaining retail media performance while investing in conversational AI. Otherwise, they risk losing visibility into how demand is created and decisions are shaped. The winners will be those who can do both without sacrificing performance or insight.

AI is an Ad Channel Without the Signals Brands Rely On

AI platforms are taking on a more active role in discovery, and they’re doing so without the foundational signals brands rely on to guide investment decisions. In traditional retail media environments, performance is built on clear inputs. Marketers can evaluate search behavior, track engagement, and use that data to forecast spend with confidence.

The most significant gap is the absence of prompt-level data. Brands cannot see what consumers are asking, how those interactions evolve, or what ultimately leads to a recommendation. Forecasting becomes directional at best, making it harder to determine how much to invest or when to scale.

That lack of signal carries through to attribution. Brands may see referral traffic, but they cannot connect it to the interactions or decision points that drove it. The link between discovery and conversion is not measurable in the way marketers expect.

Control is also limited. While paid placements will introduce more levers over time, the organic experience within AI is governed by the platform. The primary input brands can influence is their own data, including product descriptions, pricing, availability, and reviews, but how that information is interpreted and surfaced remains outside their control.

AI is becoming more influential in shaping demand, but the tools to manage, measure and optimize that influence are still maturing. Brands feel pressure to engage early, yet they're being asked to invest in a channel without the signals required to do so confidently.

Until those signals become more accessible, brands will need to operate with a level of uncertainty that directly impacts how they plan, invest and scale.

How Brands Should Prepare for AI as the Emerging Ad Channel

To navigate that uncertainty, you need to rethink how you approach channel strategy, data, and performance.

The goal is not to replace what works, but to expand your approach in a way that keeps you grounded while preparing for what's next.

1. Do not abandon what already works.

Your first priority should be maintaining confidence in the channels that are already delivering results.

Retail media environments still provide the structure, data, and predictability needed to drive performance, and they remain critical because AI platforms do not have full access to major retail ecosystems like Amazon.com and Walmart. Shifting investment too quickly toward AI introduces risk without offering the same level of visibility or control.

You should treat AI as an extension of your existing strategy rather than a replacement. While it's gaining attention as a new channel, it's not yet mature enough to stand on its own. Moving too aggressively can mean sacrificing stable performance for an unproven opportunity.

This is not the time to walk away from a successful channel in favor of a shiny new one. Stay grounded in what's working, and use that as your foundation while you begin to explore how AI fits into your broader mix.

2. Focus on what you can control.

As you navigate with limited visibility, product data becomes one of the most important levers you can control. While AI platforms do not yet provide insight into prompts or decision pathways, they rely heavily on the inputs they receive.

That makes data quality a direct factor in how your brand is represented within AI-generated responses.

This includes the fundamentals you're already managing across retail media and e-commerce environments. Product titles, descriptions, pricing, availability, reviews, and third-party validations all serve as signals that help AI platforms determine what to surface and how to position it. When this information is incomplete or inconsistent, it limits how effectively your brand can show up in both paid and organic AI experiences.

Maintaining strong data hygiene becomes a strategic requirement. You should ensure that your product data is clean, organized, and updated frequently, with a consistent process for refreshing content over time.

3. Test, learn, and prepare without full visibility.

With limited access to prompt data and attribution signals, you need to adjust how you approach this channel. Rather than waiting for perfect information, focus on controlled testing and directional learning.

Start by building a clearer understanding of how traffic behaves and where AI fits within the broader journey. At the same time, monitor how your products are being surfaced, as inaccurate or misaligned recommendations are more likely to be associated with your brand than the platform.

This is a period for building readiness. That means aligning teams, refining data strategies, and establishing processes that can support AI-driven insights as they become available. Taking this approach allows you to build familiarity now while staying flexible so you can move quickly as the ecosystem evolves.

The Future of Retail Media and AI Will Be Interdependent

As AI continues to shape how consumers discover and evaluate products, brands will need to think beyond a single optimization strategy. What performs well in an AI-driven environment may not translate directly to traditional retail or search experiences, and both will continue to matter.

Maintaining visibility across these environments will require balancing how you optimize for AI systems and how you show up for the everyday shopper. That balance is what will determine how effectively you capture both influence and conversion as the path to purchase continues to evolve.

Rather than overcorrecting toward any one channel, the focus should be on managing both in parallel. Brands that stay grounded in what works while building for what's next will be better positioned to maintain performance, adapt to new signals, and remain visible across the full journey.

Meghan Barden is the director of global retail media at Rithum, the connected commerce operations platform helping brands and retailers list, fulfill, and optimize products across every channel.