The Brands That Win with AI May Not Be the Fastest Movers

Brands that stand out in the AI era are the ones willing to run the longer race. The real advantage comes from discipline, proprietary knowledge, and creative judgment—not just more content.

By Eric Fulwiler, Co-founder & CEO, Rival

Every company suddenly has the ability to generate content and marketing campaigns using artificial intelligence (AI). These days, the conversation around AI is less about whether to adopt the technology and more about how quickly it can be deployed. While investments in AI continue to surge, there is a growing problem many companies are not confronting directly. What happens when every brand starts producing generic outputs from generic inputs with the same AI tools?

Signs of that shift are everywhere. Scroll through social media posts, company blogs, landing pages, or marketing copy and certain patterns repeat themselves. The phrasing and sentence structure sound familiar. Even the images appear stylistically interchangeable after a while. The issue is not quality. Since content is easier than ever to produce at scale, brands risk falling into a convergence trap where it’s becoming harder to stand out.

Rival, a global marketing consultancy, spent nearly five years studying challenger brands and interviewing more than 500 chief marketing officers (CMOs) to understand how companies can build long-term competitive advantage in the AI era. Rival’s research suggests that many companies are jumping into AI without considering what happens when competitors use similar models and datasets. The lesson from challenger brands is that differentiation takes time to build—a marathon, not a sprint mentality.

The marathon mentality doesn’t mean companies should be moving slowly. They should be measuring progress differently. It’s the preparation that happens before the race. Rival found that the strongest challenger brands differentiate themselves not by producing the most AI content, launching pilots, or chasing short-term wins. They succeed by building a foundation over years rather than chasing a breakthrough moment.

The danger is that AI makes it very easy to start with the tool instead of the customer. AI allows any company to generate a campaign almost instantly. That doesn’t change the basic marketing discipline: understanding what customers need and finding the best ways to serve them. If marketing teams are unclear about the customer need, they may end up creating more content around an unclear idea.

The concept of mainstream culture is also breaking down. Rival’s microcultures research shows that most adults ages 18 to 25 do not believe mainstream popular culture exists. It’s more common today to have smaller communities built around specific interests and identities like Swifties and sneakerheads. AI can help marketers identify these communities faster. Yet, it still takes human judgment and creative instinct to determine whether a brand belongs in the conversation.

The microcultures example gets at the bigger issue. AI, as a standalone tool, can be useful to companies in the early stages of identifying an opportunity. But the quality of the work depends on the brand’s own customer knowledge, the systems connecting that knowledge to AI, and the people making decisions. Rival breaks that down into a three-layer model to help companies understand how the technology can create a real brand advantage.

Layer one is first-party data (the foundation), not just customer relationship management (CRM) records and email lists. Companies already hold a full body of knowledge about their customers, campaigns, creative assets, past performance, operations, and much more. AI is only as useful as the information it is given. If a brand feeds generic input into the same public models as everyone else, the output is likely to feel generic too.

Layer two is AI systems (the engine), where AI becomes part of the actual marketing operation. This includes data infrastructure and retrieval-augmented generation (RAG), AI embedded into core operations, custom or fine-tuned models trained on proprietary data, and agentic workflows that can manage tasks. These systems only become valuable when they are fed by the company’s own data, the foundation.

Layer three is human talent (the ceiling), and arguably the most important component. AI raises the floor by making things easier. Human talent raises the ceiling by deciding what is actually worth making. Human judgement is key when everyone is accessing the same AI tools. Companies need people who can turn their knowledge of the brand and the customer into effective marketing.

As Tim Cawley, Rival’s chief creative officer, put it: “A mindless hack can strum a tuneless guitar chord. Or Eddie Van Halen can use that same guitar to melt your face off with ‘Eruption.’ The best creative people have stories to tell, insights to share, and emotions to elicit. AI is just a tool to deliver those outputs.”

Here’s the takeaway from all this: AI will not create a brand advantage just because a company uses it. The advantage comes from the work behind it. Rival recommends a more disciplined approach that involves understanding the data foundation, defining what makes the brand distinct, using creative judgment, measuring outcomes instead of activity, and treating AI as infrastructure rather than a campaign.

None of that is especially flashy, but that’s the point. Going back to the marathon analogy, brands that stand out in the AI era are the ones willing to run the longer race.

By Eric Fulwiler, Co-founder & CEO, Rival

  Agency, AI, Eric Fulwiler, Opinion Piece, Rival