By Elizabeth Maxson, CMO, Contentful
AI has fundamentally changed how consumers discover brands. Buyers are turning to answer engines to search and evaluate products, compare alternatives, and make personalised recommendations. What once required multiple searches, review sites, and product pages can now happen in a single conversation.
The result is a fundamental shift in who marketers are marketing to. Alongside consumers, marketers now have a second audience: AI systems that interpret, compare, and recommend brands on behalf of people.
That shift has made Answer Engine Optimization (AEO) a top priority. Companies are restructuring websites, enriching metadata, and publishing content in formats large language models can easily interpret. If AI can’t confidently understand your brand, it is unlikely to recommend it.
These investments are necessary, but not the panacea. We can’t assume that if AI recommends a brand, consumers will naturally choose it. This is where brand building comes into play, which relies on humans to provide context, strategy, and meaning.
This means modern marketers have two jobs. The first is ensuring AI systems can confidently understand and recommend your brand. The second is building the emotional resonance, credibility, and trust that make consumers feel confident choosing it.
A smaller consideration set changes the role of brand
We know that answer engines compress the top of the funnel. Rather than evaluating dozens of brands, consumers receive just a handful of recommendations.
This makes discoverability increasingly important, but it also makes familiarity more valuable.
For example: Someone could ask an AI assistant to recommend a running shoe. Within seconds, it presents several brands, complete with summaries, feature comparisons, customer sentiment, and purchase links. Every company on that list has solved the discoverability problem. The remaining decision belongs to the consumer.
At that moment, people rarely evaluate every recommendation with equal weight. They gravitate toward brands they already recognise, have heard about from trusted sources, or have encountered repeatedly through lived experiences. The AI recommendation creates consideration. Familiarity and trust are what create decision confidence.
Managing AI reputation without neglecting human reputation
This creates a new challenge for marketers. Because now, every brand has an AI reputation: a digital understanding built from the information large language models ingest and synthesise. If that understanding is incomplete, inconsistent, or outdated, AI may recommend a brand without accurately representing what makes it different.
Managing that AI reputation is rapidly becoming an essential marketing capability – and marketing leaders must invest in this – but it can’t become the entire job.
Brands must continuously invest in the emotional, cultural, and experiential signals that shape how people perceive them.
Why brand building becomes more valuable
95% of consumers say trust is critical when making a purchase decision.
When AI filters an overwhelming marketplace into a handful of credible options, consumers rely even more heavily on the associations they have already formed. In effect, AI delegates research while people continue to make judgments.
That judgment is rarely formed in the moment. It is built months or years beforehand through consistent experiences, memorable campaigns, word of mouth, and cultural relevance.
ASICS offers one example of this principle in practice. During the London Marathon, the company avoided centering its campaign exclusively on product performance, but also emphasised the emotional experience shared by runners—the anticipation before the race, the resilience during it, and the satisfaction of crossing the finish line. The campaign succeeded because it reflected something authentic about its audience.
This strategy was designed to improve an AI ranking, but designed to create memories that consumers carry into future purchasing decisions.
Risk in becoming indistinguishable
As more organisations rely on the same AI tools, generic language, predictable structures, and interchangeable messaging are becoming commonplace. Brands that optimise exclusively for discoverability risk becoming perfectly understandable to AI while becoming increasingly forgettable to people.
That’s why AI reputation can’t be managed on instinct alone. Marketing teams need tools that provide continuous visibility into how answer engines describe their brand, where those descriptions diverge from their intended positioning, and what actions will improve discoverability without sacrificing differentiation.
Then, they have to balance that machine-readable clarity with the original thinking, distinctive voice, and the genuine audience understanding that humans require to build trust. This is the unlock; a major differentiator for brands.
Marketing’s next competitive advantage
Doing AEO well will soon become table stakes. But optimising for answer engines solves a different problem than building a brand. AEO helps AI understand who you are. Brand building helps people decide why you matter.
The easiest way to think about this is to treat AI as another persona that values structure and accuracy, not a replacement audience. When balanced against the emotion, relevance, and authenticity that humans need to develop trust, marketers can earn confidence from both.
