Interview with AI Times Korea – The B2B Marketing Landscape is Changing: “We Now Need to Convince AI Before We Convince Customers”

AIM B2B CEO Robert Heldt sat down with AI Times Korea to discuss how the rise of generative AI is transforming not only how B2B companies market themselves, but also how customers research, evaluate and make purchasing decisions.

In the past, prospective customers typically used search engines to find information about companies and products, compared multiple websites themselves and then made a purchase decision. An increasing number of buyers are using AI platforms such as ChatGPT, Gemini and Perplexity to search for information and compare and evaluate companies and products.

“AI can distribute knowledge remarkably quickly, but it cannot replicate experience.”

Robert Heldt, co-founder and CEO of AIM B2B, is a B2B specialist with more than 17 years of experience in digital marketing and strategic communications. He has supported global companies with their market-entry strategies across Japan and the rest of the Asia Pacific region. As CEO of Tokyo-headquartered AIM B2B, Robert helps global companies enter and grow in Asian markets, while also serving as the APAC representative for AMIN Worldwide, a global alliance of more than 50 marketing and advertising agencies.

Robert shared his views on B2B marketing strategies in the age of AI, the evolving meaning of GEO, how AI evaluates and recommends companies, the growing importance of brand trust and expertise and how the B2B buyer journey is likely to change over the next three to five years.

In particular, Robert says, as AI processes vast amounts of online information to summarize companies and recommend specific businesses or products, what a company has accumulated in terms of information and how much trust it has earned in the market are emerging as new sources of competitive advantage. Rather than simply seeking higher visibility in search results, companies now need strategies that enable AI to accurately understand them and recognize them as credible and trustworthy businesses.

Against this backdrop, he explains, interest in Generative Engine Optimization (GEO), beyond traditional Search Engine Optimization (SEO), is growing across the B2B marketing industry. However, GEO should not be viewed simply as a new technique for gaining visibility in AI-generated search results. The key is to continuously build a broad base of digital trust assets, including a company’s expertise and experience, customer case studies, content and brand reputation, that gives AI the information and context it needs to understand the company.

“What generative AI has changed is not simply the way people search for information, but the way they make decisions,” he said.

As generative AI becomes more widespread, the way customers search for information and make purchasing decisions is changing. What changes are you seeing and how are they reshaping the way companies grow?

In the past, users compared search results one by one and drew their own conclusions. Today, however, AI synthesizes information from multiple sources, understands the context behind a user’s question and provides a consolidated answer. In other words, information discovery is shifting from search to conversation.

This shift is becoming increasingly evident in the B2B market as well. Recent global research confirms that this trend is already underway. According to Boston Consulting Group, 96% of CMOs say that AI is already changing how buyers discover and evaluate brands. Meanwhile, G2 found that more than half of B2B software buyers now turn to AI chatbots more often than Google when researching products and vendors.

As a result, buyers are increasingly using AI to understand the market, compare competitors and narrow down their shortlist before engaging directly with companies.

Is GEO simply the new SEO or is it an entirely different game?

To answer that question, it’s important to first understand what GEO actually is.

Many digital marketing professionals describe GEO as the evolution of traditional SEO. While SEO focuses on helping websites become more discoverable and rank higher in search engine results, GEO is designed to increase the likelihood that generative AI systems and AI-powered search services will understand, reference and incorporate a company’s information when generating responses.

I do not see GEO as an entirely different game from SEO. Rather, I believe it represents an expansion of SEO’s objectives and scope in the AI era.

In the past, success largely depended on achieving higher search rankings. Today, what matters more is consistently demonstrating across multiple digital touchpoints what your company specializes in, what problems it solves and why it is a credible and trustworthy organization.

This means that keyword optimization alone is no longer enough. Companies need to continuously develop and maintain a diverse range of content, including customer success stories, technical resources, media coverage and expert thought leadership. Which showcases their expertise and real-world experience while delivering consistent messaging across channels.

Ultimately, GEO is not simply a technical exercise designed for AI. It is a strategic approach to digital communication that enables both people and AI systems to better understand a company’s expertise, credibility and value.

In your view, how do AI systems understand and recommend companies?

The exact algorithms that AI services use to recommend particular companies or products are not publicly disclosed. However, looking at the current direction of generative AI and AI-powered search, several common principles are becoming increasingly clear.

The first is Entity. Traditional search engines primarily focused on matching webpages to keywords. However, AI-powered search increasingly emphasizes the relationships between entities such as companies, products, technologies, industries and people.

As a result, companies need to do more than repeatedly mention product names. They should consistently publish content that clearly communicates what they specialize in, what problems they solve and how they create value within their industry.

The second is Context. AI does not simply recommend a company because its name appears frequently or because certain keywords are repeated. What matters is the broader context: the industries a company operates in, the customer challenges it has solved and the unique expertise and experience it has accumulated over time. Rich contextual information enables AI to better understand a company and connect it with relevant user questions.

The third is Authority. Generative AI and AI-powered search services are evolving toward making use of information that is consistently supported by multiple trustworthy public sources. The more consistently a company’s website, media coverage, customer case studies, technical documentation, research papers and industry reports reinforce the same core messages, the more likely AI is to understand, reference and potentially recommend that company.

The fourth is Freshness. AI services are increasingly incorporating up-to-date information. That means companies should not rely solely on legacy content. They need to continuously publish new customer success stories, technology updates and industry insights so that their digital presence remains current and relevant.

Ultimately, I believe companies should focus less on trying to optimize for specific algorithms and more on building long-term credibility.

In the AI era, marketing is becoming less about competing for search rankings and more about establishing thought leadership. Companies that consistently contribute valuable insights, publish credible customer success stories and support their claims with objective evidence are more likely to be recognized as trusted leaders, not only by customers, but also by AI systems.

In other words, the companies AI is most likely to reference are not necessarily those that have mastered algorithms, but those that have consistently built expertise, credibility and trust across the digital ecosystem.

Does this mean that brand reputation and corporate credibility will become even more important in the era of AI-powered search?

Absolutely. When generative AI produces answers about a company, it relies on a wide range of information and data that has already been accumulated across the public domain. As a result, assets such as a company’s expertise, customer experience, market reputation and media coverage continue to play an important role in the AI era.

In the past, a brand primarily influenced how customers perceived and selected a company. Going forward, however, it will also influence how AI describes, interprets and presents that company. This is why it is becoming increasingly important for information about a business to be consistently developed and communicated across multiple channels within a coherent context.

What should companies start building today to prepare for the AI era?

Many companies begin by asking how they can create content that is optimized for AI. In my view, however, the priority should be building a strong foundation of digital assets that demonstrate their expertise and credibility.

AI services are increasingly generating responses by drawing on a wide range of publicly available information,not only corporate websites, but also media coverage, customer success stories, technical documentation, research publications and other trusted sources. This means companies should avoid relying on a single channel and instead continuously build a diverse portfolio of information that reflects their expertise and experience.

Different AI services naturally use information in different ways. Search-based AI systems tend to prioritize recent information from clearly attributable public sources, while generative AI models increasingly synthesize information by connecting content from multiple sources within a broader context. However, regardless of the specific AI platform,one principle remains consistent: trustworthy public information must exist in sufficient quantity and quality.

For that reason, companies should move beyond maintaining a website that simply introduces their products or services. They should continuously develop high-value content such as customer case studies, technical white papers, industry insights, FAQs, expert interviews, webinars and contributed articles that demonstrate genuine expertise.

Content formats should also become more diverse. The same expertise can be communicated through articles, videos, images, infographics, presentations and other formats. This not only improves the customer experience but also provides AI with richer contextual signals to better understand the company’s capabilities.

Ultimately, I believe the most important investment companies can make is not adopting another marketing tactic, but building Digital Trust Assets.

AI generates responses based on publicly available information. Therefore, future competitiveness will depend less on learning how to optimize for AI and more on whether a company has consistently built a trusted ecosystem of information that both customers and AI can rely on.

If AI makes knowledge and information increasingly accessible to everyone, how can companies continue to differentiate themselves?

AI can distribute knowledge remarkably quickly, but it cannot replicate experience.

In the future, virtually anyone will be able to use similar AI tools to create content. As a result, competitive advantage will no longer come from possessing more information, but from interpreting that information through unique experience and insight.

Ultimately, what differentiates a company is the experience that only it has accumulated, such as : its project execution, deep industry expertise, customer relationships, practical know-how and distinctive perspective on solving problems. Those are assets that AI cannot easily replicate and they will become the foundation of sustainable competitive advantage.

Looking ahead three to five years, what AI-driven changes should companies pay the closest attention to?

The most significant change companies should be watching is not AI technology itself, but the way customers discover information and evaluate businesses.

In the past, buyers visited multiple websites and compared information through traditional search engines. Increasingly, however, they are using generative AI to summarize information, compare vendors and evaluate products before making purchasing decisions. This trend is expected to become a natural part of the B2B buying journey over the next several years.

To adapt, companies will need to rethink their content strategies. Rather than focusing solely on product features and specifications, they should consistently communicate what problems they solve, what expertise they possess within their industry and what measurable value they have delivered to customers.

Internal content management will also need to evolve. Today, websites are often managed by marketing teams, customer success stories by sales, technical documentation by engineering and press releases by public relations. Going forward, these information assets should no longer exist in isolation. They need to be connected and managed through a consistent strategic narrative.

Both customers and AI increasingly develop an understanding of companies by synthesizing information from multiple public sources. As a result, success will depend not simply on producing more content, but on managing an organization’s entire body of knowledge as a coherent, credible and consistently communicated digital asset.

This interview was translated from the original on AI Times Korea.