Daniel Benton, managing director at WPP Media, has highlighted a significant transformation underway in brand discoverability driven by the widespread adoption of artificial intelligence (AI). This shift, he argues, is reshaping how consumers find and evaluate brands online, moving beyond traditional search paradigms to a new era of AI-driven discovery.

Two decades ago, online brand discovery was dominated by search engines, which relied primarily on keywords and rankings to connect consumers with brands once they knew what they were seeking. Brands optimized their marketing strategies around search visibility and measurable traffic, fostering growth through this well-understood model. However, Benton notes that the current landscape is evolving into something more complex, where AI tools are not just facilitating discovery but also synthesizing, summarizing, and evaluating information for consumers.

In this emerging environment, consumers increasingly depend on large language models (LLMs) and AI chat interfaces to digest vast amounts of content, compare options, and understand choices without manually navigating multiple pages or links. With Australia experiencing one of the highest rates of AI adoption globally, usage is surging despite lingering concerns about trust and risk. A recent KPMG survey found that while 83 percent of Australians believe AI will provide benefits, only 30 percent feel the benefits outweigh the risks, and just 46 percent express trust in AI systems. Despite these reservations, platforms like ChatGPT have seen traffic increase by more than 50 percent year-to-date.

Benton emphasizes that this tension—between rapid adoption and cautious trust—has profound implications for how brands appear in online ecosystems shaped by AI. Unlike previous models where brand messaging was controlled primarily by the company itself, AI systems integrate a wide array of public information, including news coverage, user reviews, expert opinions, social media conversations, and influencer content. This comprehensive aggregation affects AI’s “understanding” of a brand and influences whether it is recommended or favored during consumer decision-making processes.

Importantly, this evaluation occurs before consumers consciously engage with a brand, signifying a shift in where brand influence begins. AI's ability to align or expose discrepancies between brand promises and consumer experience strengthens consumer confidence or skepticism accordingly.

Benton cautions that many businesses remain focused on traditional digital metrics such as clicks and site visits, potentially overlooking where consumer decisions increasingly take place—in AI-generated summaries and conversations that deviate from conventional marketing funnels. As AI becomes a critical decision-making tool in high-consideration purchasing categories, brands must adapt.

To navigate this new landscape, Benton advocates for comprehensive audits of brand presence within AI environments, leveraging large datasets to identify sentiment gaps and the likelihood of brand recommendation. Such insights can inform strategies to improve the content that AI systems access and interpret, emphasizing the importance of creating accessible, consistent content that supports positive brand perception.

Furthermore, Benton points to the rising role of paid media within AI platforms as a forthcoming frontier for brand growth, particularly with companies like OpenAI introducing advertising capabilities in the Australian market. Early experimentation and strategic experimentation with these channels could position brands advantageously.

In conclusion, Benton stresses that the disruption brought by AI in brand discoverability is not incremental but structural, fundamentally altering how growth is achieved in every category. Brands that fail to understand and shape their presence in this AI-driven environment risk losing relevance and market share as consumer decision-making increasingly unfolds within AI systems.