How Brands Stay Visible When AI Shapes Discovery

A customer weighing financial services options can now begin with a simple prompt: “Which provider is best for someone like me?” An AI assistant can compare features, surface trade-offs and suggest a handful of names. Before the customer speaks to anyone, AI has narrowed the market.

This behavior is moving from early adoption to everyday discovery. Customers once gathered information through search engines, brand websites, apps, social feeds and online reviews. Now, Adobe research finds that one in four customers cite AI-powered platforms as their primary discovery tool, ahead of brand websites and online reviews. 

The implication for marketers goes beyond traffic. AI systems are increasingly shaping the competitive landscape by determining which brands are considered, how they are evaluated and what information customers use to make decisions. 

The shift in numbers and behavior is showing up in traffic patterns. Research from Adobe, which has tools to help brands capitalize on these changes, found that AI-driven visits to financial services sites grew 105% year over year in May 2026, marking 19 consecutive months of growth since October 2024.

The point for marketers is that AI-mediated research can send customers to a brand with more context, stronger intent and a clearer sense of what they want. Brands that show up in AI answers are chosen more often and convert customers at 4.4x the rate of organic search. 

The challenge is getting into those conversations in the first place. This imperative is driving a new class of search optimization practices including generative engine optimization (GEO), answer engine optimization (AEO) and agentic search optimization (ASO), which aim to improve how brands are discovered, understood and recommended by AI systems. 

“The next phase of brand visibility will be shaped by how clearly a company can be understood across AI-assisted journeys,” says Duncan Egan, Vice President of Enterprise Marketing, Asia Pacific & Japan at Adobe. “That requires more than content volume. It requires trusted information, consistent signals and a clear view of how your brand shows up to both humans and AI.”

Brand building now must account for the signals AI systems use to interpret a company. Product information, customer stories, reviews, metadata, thought leadership and third-party references all shape that picture. As AI search keeps changing, CMOs need to know whether those systems can keep finding the brand, understanding and presenting it in the right context.

Most marketing teams have a clear view of what happens on owned channels. They can track traffic, engagement and conversion. What has changed is where the journey begins. By the time a customer arrives on owned channels, the consideration journey may already be complete and the purchase journey well underway. 

This change in behavior makes data readiness a strategic issue. Adobe’s 2026 CMO research found that 78% of CMOs cite data integration as the top barrier to adopting agentic AI, and the same fragmentation means teams cannot connect what customers are asking AI to how their brand is actually showing up in those answers.

AI is introducing signals including prompt performance, citation share and how AI systems characterize a brand relative to competitors. Those signals are reshaping what content needs to do and how teams need to think about it.

“AI is changing the signals marketers need to pay attention to,” says Egan. “The brands that move fastest will be the ones that connect customer insight, content operations and governance, then use that foundation to create better customer journeys.”

Content teams will feel the pressure first. Campaigns still need to persuade, inspire and convert. AI-mediated discovery also rewards content that explains clearly, substantiates claims and stays current across every surface where a brand may be interpreted. That shifts the mandate from producing more assets to maintaining a body of information that humans and AI systems can both use with confidence.

As AI-mediated discovery becomes more influential in the customer journey, marketers need a way to translate visibility into practical action. 

Brands need to know where they appear, where they are missing, how they are described and which sources influence those answers. They also need to act on that insight quickly, from updating owned content to improving the evidence AI systems rely on when representing them across search, AI search and other discovery surfaces.

That is the role Adobe is positioning Adobe Brand Visibility to play. Generally available from August 2026, Adobe Brand Visibility brings together recent acquiree Semrush’s AI visibility intelligence with Adobe’s agentic content optimization capabilities to help businesses understand and improve how they appear across AI search. Adobe says the solution draws on nearly 300 million real-world AI search prompts, audience reach data, competitive share of voice and owned-channel insights across platforms including ChatGPT, Google AI Mode, Microsoft Copilot and Perplexity AI.

Adobe Brand Visibility is designed to show which prompts a brand is winning or losing, identify the sources shaping AI perception, recommend changes and connect those actions to business impact through Adobe’s analytics tools. 

Built for execution as much as insight, it enables teams to push changes to owned channels without an engineering queue, reach third-party surfaces like forums, review sites and community platforms that AI systems weight most heavily and connects optimization directly to revenue outcomes through Adobe Analytics.

In practical terms, that gives marketers a way to manage AI visibility as a repeatable workflow rather than a periodic audit.

“AI search is quickly becoming part of how customers form consideration,” says Egan. “The question for marketing leaders is no longer how their owned channels are performing. It’s how much of the market they’re missing before customers ever arrive.”