The AI-Empowered Customer: How Brands Must Adapt to the Era of Agentic Commerce

As artificial intelligence evolves from a passive tool for query resolution into an active participant in the consumer journey, the foundational relationship between brands and their customers is undergoing a seismic shift. No longer are retailers simply competing for human attention; they are increasingly navigating a landscape where AI agents—acting as autonomous intermediaries—shape, recommend, and eventually execute purchasing decisions.

Ahead of his appearance at the upcoming CustomerX conference on October 14, Ian Macfarlane, acting Global SEO lead at H&M, explores the implications of this "AI-empowered" consumer. In a wide-ranging discussion, Macfarlane highlights why the rise of Generative Engine Optimization (GEO), the challenge of brand disintermediation, and the enduring power of human trust will define the next decade of retail.

The Core Shift: From Human Marketing to Machine Interaction

The concept of the "AI-empowered customer" describes a pivotal transformation in ecommerce: the shift from direct-to-consumer (D2C) relationships toward a model where AI agents act as gatekeepers.

"We are witnessing a huge shift in ecommerce," says Macfarlane. "It is no longer just about selling directly to the end consumer. Brands are increasingly being disintermediated by AI robots. This is an enormously scary prospect for established brands, which have significantly more equity at stake."

This transition forces a fundamental existential question upon marketing leaders: What does it mean to be a brand when your consumer is not necessarily a human being, but an algorithm? Brands are no longer just using AI to optimize their operations; they are now actively marketing to an AI. This requires a shift in strategy from emotional storytelling—which resonates with human psychology—to a more data-centric, rational approach that satisfies the requirements of Large Language Models (LLMs).

The Evolution of Search: Why SEO Teams are the New Frontline

In the immediate aftermath of ChatGPT’s public debut, industry analysts predicted the "death of search," suggesting that traditional SEO was obsolete. However, the reality has proven to be the opposite. As AI becomes embedded in search engines, the need for expertise in visibility and discovery has only intensified.

The Rise of GEO

Generative Engine Optimization (GEO) has emerged as the essential framework for brands to remain visible within AI-generated summaries. Macfarlane argues that the professionals best suited to manage this transition are those who have spent years mastering traditional SEO.

"The people with the best ability to do the work required to make your brand visible in AI search are your SEO team," he explains. "SEOs have always worked cross-functionally. While their scope now encompasses brand PR, reputation management, and complex data architecture, the core objective remains the same: ensuring the brand is discoverable where the consumer is looking."

The Multi-Channel Optimization Mandate

Retailers can no longer afford to optimize only for traditional search. A modern, robust strategy must account for:

Traditional Search: The "blue link" legacy still holds significant weight for transactional intent.
GEO: Ensuring brand presence within AI Overviews and chatbots.
On-site Search: Optimizing internal recommendation engines to mirror the personalization consumers expect elsewhere.
Platform-Specific Search: Social media, marketplace-specific search (like Amazon or TikTok), and local maps data.

Chronology of Search: From Blue Links to Recommendations

To understand where we are going, it is helpful to review how we arrived here. The trajectory of search can be categorized into four distinct eras:

The Era of Ten Blue Links: The foundational period where keyword density and backlink authority dictated success.
The Era of Vertical Discovery: The emergence of specialized formats like Google Maps, Shopping, and Image search.
The Era of Answer-Box Optimization: The precursor to AI, where brands competed to provide direct snippets in response to "zero-click" queries.
The Era of AI-Agentic Commerce: The current stage, where platforms not only help users find products but actively recommend and potentially purchase them.

"At each stage, brands have become increasingly disintermediated," notes Macfarlane. "Look at Google’s AI Overviews, which provide pros and cons for a brand. That is a significant reputational challenge that requires constant monitoring and management."

The Trust Gap: Why Human Intuition Still Holds Sway

Despite the rapid advancement of agentic commerce—where AI performs the actual transaction—consumer adoption remains a variable. Trust remains the primary currency of the digital age.

The "Robot Intern" Problem

Macfarlane cautions against overestimating the speed of consumer adoption. "Even I am not comfortable giving what is essentially an overenthusiastic robot intern my credit card and letting it run wild," he admits. The fear of hallucinated recommendations or poor purchasing decisions means that human oversight is still heavily preferred for high-stakes or high-value items.

The Role of Brand Equity

In an environment where AI makes the shortlist, brand reputation acts as a mental shortcut. If an AI suggests a brand a consumer already knows and trusts, the friction to purchase is significantly lower. Conversely, if an AI recommends a "no-name" brand, the consumer is forced to conduct their own manual verification, defeating the purpose of the AI assistant. Therefore, building a respected, recognizable brand is arguably the most effective SEO strategy for the AI era.

Implications for Physical Retail and Future Strategy

If the digital experience is becoming increasingly automated and "machine-optimized," what is the role of the physical store?

The Return to the Real

"In an increasingly digital world, the real world matters more than ever," says Macfarlane. Consumers are actively seeking non-digital experiences. For fashion retail, the tactile element—the ability to touch and feel fabric—remains a barrier that AI cannot currently overcome.

Physical stores also serve as critical data points. Brands must ensure their "local" digital presence—store hours, locations, and inventory availability—is perfectly synchronized with the data sources that LLMs consume. If an AI provides outdated or incorrect information about a store, the result is a disaffected, lost customer.

Shifting from Categories to Occasions

The most significant change in consumer behavior is the move from category-based searching (e.g., "red dress") to occasion-based searching (e.g., "what should I wear to a winter wedding in Italy?").

Because AI is adept at processing complex, multi-layered queries, consumers are providing more context than ever before. For brands, this represents an opportunity to map their products to specific life moments. By understanding which occasions are most relevant to their customers, brands can curate content and PR strategies that satisfy the AI’s need for context-rich, authoritative information.

Conclusion: Preparing for the Unknown

As the industry looks toward the next five years, Macfarlane offers a note of caution: "Marketing is changing faster than it ever has. Trying to predict exactly what is going to happen in five years is a fool’s game."

The best strategy for retailers today is not to attempt to build a rigid five-year roadmap, but to focus on fundamental principles:

Master the Fundamentals: Ensure all digital and physical data is accurate and optimized for machine consumption.
Focus on Trust: Invest in brand reputation, as it is the primary factor that encourages consumer adoption of AI-led recommendations.
Embrace the "Agentic" Mindset: Begin mapping the customer journey to include the AI intermediary, not just the human end-user.

While AI is transforming the "how" of shopping, the "why"—understanding human needs, desires, and occasions—remains a distinctly human task. As we move toward the event at CustomerX, the consensus is clear: the brands that win will be those that successfully bridge the gap between machine-driven efficiency and human-centered trust.

Ian Macfarlane will explore the impact of AI-powered search and agentic commerce in detail at CustomerX on October 14. To join the conversation, register for the event via the official portal.