Why AI visibility is no longer enough for brand reputation: Red Surtida

Artificial intelligence is rapidly reshaping how people discover, consume, and evaluate information. From search queries to purchase decisions, AI-generated answers are increasingly becoming a first point of reference, influencing perceptions of brands, businesses, and leaders at an unprecedented scale.

As organisations race to optimise their presence within these emerging platforms, a critical question remains: does visibility automatically translate into trust?

New research from the global communications agency, Burson suggests the answer is far from straightforward. Ahead of the release of ‘The Credibility Paradox’, a study analysing more than 55,000 believability scores across 85 companies and seven major AI platforms, the agency highlights a growing gap between being mentioned in AI-generated responses and being believed by the audiences reading them.

In this interview, Red Surtida, APAC Head of Intelligence & Transformation at Burson, unpacks the findings, explores the implications for brands across Asia-Pacific, explains why credibility and not just visibility, is becoming the defining measure of reputation in the generative AI era, and what this means for the future.

Excerpts:

1. Why do you believe credibility, not visibility has become the defining challenge in the AI era? 

AI has made visibility easier and more cost-efficient to achieve. Brands can now appear in summaries, search results, and AI-generated answers with far greater frequency than before. But visibility alone does not necessarily create influence.

AI systems pull from multiple sources. If a brand’s claims are not supported consistently across those sources, visibility may not translate into credibility, preference, or action. The challenge is shifting from simply being present in AI-generated answers to ensuring the information being cited is substantiated and believable.

The organizations best positioned to win GEO are likely those that treat it as a reputation opportunity, not a visibility problem.

2. The report introduces the idea of a Credibility Paradox. What exactly is the paradox, and what core changes will it bring that communicators should pay attention to? 

The Credibility Paradox is the gap between being seen and being believed. A brand, product, or service can appear prominently in an AI-generated answer and still have limited influence over whether audiences believe or act on that information. Visibility has become easier to achieve, but credibility still requires independent validation.

For communicators, this suggests that success can no longer be measured solely by presence or share of voice. It also means making sure brand claims hold up with stakeholders when AI cross-references information from earned media, customer reviews, expert commentary, and other independent sources.

3. One of the findings shows that business decision-makers are significantly more convinced by AI-generated brand information than the general public. What risks and opportunities does this create for organisations?

Business decision-makers often have a stronger understanding of how AI sources information. As a result, they tend to be more comfortable incorporating AI-generated information into their evaluation process. This presents an opportunity for organizations, particularly B2B, where AI answers are increasingly driving not only information, but also consideration.

At the same time, misinformation and disinformation can speed through the same channels. Organizations need to ensure that information is accurate, current, and consistent across websites, media coverage, analyst reports, reviews, and other trusted sources. The more easily information can be verified, the more resilient it tends to be.

4. Were there any findings that challenged conventional communications wisdom or surprised you during the research process?

The workplace finding stood out. It aligns closely with what we observed in our Reputation Economy research - workplace reputation tends to be easier for audiences to believe because there is proof in the form of employee reviews, news coverage, workforce policies, and employee experiences shared publicly.

Leadership credibility was also interesting, but for a different reason. Most people never interact with C-Suite leaders directly, so they're relying entirely on external signals to judge whether someone is a credible leader. The more abstract a claim, the more proof it needs.

5. For years, organisations have invested heavily in executive thought leadership. Does this finding suggest companies need to rethink how they build leadership credibility in the AI era? 

Executive visibility still matters, but visibility without substance is just noise now.

The strongest leadership signals are not built on commentary alone. They are supported by business results, organizational decisions, third-party recognition, and independently verifiable sources. The industries that scored highest on leadership credibility were those where credibility was associated with institutional performance and long-term results rather than individual profile.

For organizations, this points toward executive visibility programs grounded in tangible evidence and measurable outcomes – building a consistent pattern of externally validated leadership signals over time.

6. Many organisations view Generative Engine Optimization as a technical exercise. At what point does GEO become a communications and reputation management discipline? 

GEO becomes a communications discipline when organizations recognize that AI visibility is shaped by many of the same factors that have always shaped reputation.

AI systems increasingly rely on earned media, expert commentary, reviews, research, corporate content, and third-party validation when determining what information to surface.

Our research shows that believability varies significantly across audiences, industries, and topics. That variation makes it a reputation challenge as much as a technical one.

Communications teams are well positioned to address this because the drivers of credibility - narrative consistency, earned authority, independent validation, expert voices - have long been central to the discipline.

7. From an APAC perspective, how mature are organisations in understanding the credibility implications of generative AI? What differences have you observed between APAC markets and Western markets?

Several APAC markets, including China, Singapore, South Korea, India, and Indonesia, have been early adopters of AI. In many cases, AI is already embedded into everyday workflows and digital experiences, creating a high degree of familiarity.

However, APAC is highly diverse. Levels of maturity vary considerably depending on local platform ecosystems, regulatory environments, media landscapes, and adoption patterns.

What appears consistent across regions is that most organizations are still primarily focused on AI adoption, productivity, and operational efficiency. Fewer are actively considering the implications for credibility, reputation, and decision-making.

8. For decades, communicators have focused on shaping narratives for people. What era are we entering now and how does that change the communications industry itself?

AI is making explicit something that has always been true: reputation is built through evidence, not simply through messaging. AI systems look for consistency, corroboration, and validation across multiple sources. In many respects, they apply credibility tests similar to those used by people when evaluating information.

For communications professionals, this means creating a proof ecosystem. Simply articulating a compelling narrative is no longer enough. Communicators need to ensure organizations have credible evidence to back their narrative.

The role of communicators remains largely the same: building reputation, establishing credibility, and shaping perception. What is changing is the environment in which those outcomes are achieved, and the level of substantiation required to support them.