Shopify-native platform Glu.ai is betting on a major shake-up in how consumers discover products, as AI-powered recommendation engines begin to displace traditional search.
The company, led by former AWS and Microsoft AI expert Sangeeta Mudnal, has launched its Generative Engine Optimisation (GEO) offering in Australia, targeting mid-market brands looking to surface inside AI-generated answers across platforms including ChatGPT, Google AI Overviews, Gemini and Perplexity.
The move comes as product discovery rapidly shifts away from keyword-led search towards conversational queries, where consumers ask increasingly specific questions and receive curated recommendations rather than lists of links. In that environment, brands are no longer competing for rankings but for inclusion.
Mudnal argues the change represents a structural reset for eCommerce, particularly for brands that have traditionally lacked the marketing budgets to compete with larger retailers.
“For decades, scale and media budgets determined who won in search,” she said. “Now the gatekeepers have changed – and they’re looking for something entirely different.”
Industry forecasts suggest traditional search volumes are set to decline as AI “answer engines” become the default interface for discovery. Instead of browsing, consumers are turning to AI assistants to interpret their needs and recommend products directly, placing new emphasis on how clearly a brand can be understood by machines.
Glu’s platform is designed to address that shift by analysing product pages and catalogues, identifying gaps in clarity and context, and generating content that better aligns with how AI systems interpret and evaluate information. The goal is to transform product listings into structured, machine-readable assets that can be confidently surfaced in recommendations.
That shift also exposes a potential weakness among larger retailers. Many enterprise businesses, built for the SEO era, operate with vast catalogues and legacy systems that make it difficult to maintain consistent, high-quality data across thousands of products. By contrast, smaller and mid-sized brands are often better positioned to adapt quickly, updating product content and implementing structured data without the same operational friction.
“This is the levelling,” Mudnal said. “A $15 million brand with excellent product clarity can outrank a $500 million competitor with poor data hygiene.”
For brands, the implications are significant. Visibility is becoming less about how much is spent on media and more about how effectively products are described, structured and validated across the web. Product pages are no longer just conversion tools but critical inputs into AI systems that determine what gets recommended.
The shift is also forcing a rethink of traditional SEO strategies. Keyword optimisation is giving way to intent-driven content, structured data and broader signals of authority, as AI models cross-reference multiple sources to assess credibility. Inconsistent or incomplete information can weaken those signals, reducing the likelihood of being surfaced.
At the same time, early movers may gain an outsized advantage. As AI systems learn which brands to trust within specific categories, those that establish strong, consistent data now could shape how recommendations are formed in the future.
As AI becomes a primary interface for commerce, the competitive dynamic is changing. The brands that succeed may not be the ones with the biggest budgets, but those that can most clearly communicate what they offer — not just to consumers, but to the machines increasingly acting on their behalf.
“In 2026, visibility is no longer a question of how much you can spend,” Mudnal said. “It’s how well you can be understood.”
