Decoding AI Commerce: New Opportunities for Brand and Insights

In our ongoing From Chat to Checkout series on The Prompt, we've been tracking how AI is fundamentally reshaping consumer decisions. Last week, our expert panel at Conveo delved into the rise of AI-powered shopping, unearthing fascinating perspectives on what this seismic shift means for brands - and especially for insights functions.

Mastering visibility and tactics within Large Language Models (LLMs) is rapidly becoming non-negotiable for brands. For insights teams, navigating this new terrain is shaping up to be one of the most meaningful research moments in years. As Yogesh Chavda noted during the discussion, this inflection point could mark the start of a "Golden Age" for insights - an era where strategic understanding is key to helping brands thrive in an AI-mediated world. The behavioral change is profound, and the opportunity to learn from it is immense.

Here are the core ideas and discussion points that stood out across the session.

Three Pillars from Our AI Shopper Study

Niels Schilleweart, Conveo’s Head of Research, anchored the discussion by presenting three pivotal insights from Conveo’s 2025 AI-Powered Shopper Study (covering 330 interviews across eight regions):

• AI Reshapes Buying Journeys End-to-End: LLMs now touch the entire decision process, fundamentally rewriting traditional, linear decision flows.
• AI is the Preferred Source of Shopping Advice: Consumers now rely on AI over friends, family, and even store staff by a striking 2:1 margin.
• AI is Rewiring Brand Loyalty: Over half of shoppers have tried new brands based on AI recommendations, actively breaking what panelists termed "bad loyalty."

What Agentic Commerce Means for Brands

1. The Death (or Redefinition) of the Brand Funnel

One of the most provocative points came from Mike Stevens, who directly challenged the relevance of the traditional brand funnel in light of Insight #1.

“The traditional funnel that we have, we have to retire that funnel… With this now, I think the funnel is quite effectively dead.”

For years, the funnel was a useful, if imperfect, simplification. In AI-mediated journeys, that logic collapses. Consumers jump steps, merge stages, or start at the point of purchase. The brand might appear early, only at the validation stage, or not at all. 

While the funnel isn't entirely redundant at a high level, its linear assumptions are undeniably being disrupted. Old playbooks won't suffice. Adapting requires new methodologies, new data, and a new way of listening. This moment feels strikingly similar to the early days of social media: behaviors are evolving fast, rules are being rewritten, and the quick learners will gain a decisive advantage.

2. There’s a New Science to Discovery

Where traditional SEO once reigned, discoverability now also hinges on the signals AI systems can confidently parse. Brands must focus on structured metadata, granular product attributes, and accurate descriptions that allow an LLM to recommend a product with certainty. It's now a highly scientific approach to how we define and describe products: if a brand can't be perfectly understood, it can't be recommended.

Furthermore, trust is key to AI adoption. AI providers are proactively building credibility into their tools. This means high-quality user reviews and consistent, honest claims in marketing are not just nice-to-haves, they directly influence whether an AI tool like ChatGPT surfaces a brand as a trustworthy option.

3. Mental Availability Is Challenged in Real Time

AI acts as a powerful shortcut to credible alternatives, instantly reshaping a consumer’s consideration set. Our 2025 study shows the scale of this shift: 53% of shoppers try new brands based on AI, and nearly 80% have changed their in-store choices after consulting AI.

As Mike Stevens also noted, a brand might only appear at the very end of the journey, "when the agent has already shortlisted products and the consumer is essentially validating a specific SKU.” This demonstrates how mental availability can shift instantly in AI-mediated moments. Historical recognition alone is no longer enough. Visibility, credibility, and relevance - in real time - are critical. Of course, strong brand equity still matters: when AI surfaces multiple brands with similar functional attributes, the established brand often guides the final choice.

4. The Trust Chain Shifts: Brand → AI → Consumer

The panel was clear: AI is now an active validator of information. Instead of relying purely on brand claims, consumers expect AI to check, compare, and surface only trust worthy options. The chain of trust has shifted: consumers increasingly trust what the AI confirms. This significantly raises the bar for brands - product data must be accurate, consistent, and easy for AI systems to verify against external sources.

5. Brand Partnerships with AI Platforms Could Face Scrutiny

A significant theme was neutrality. People rely on AI as an unbiased advisor, not a paid channel. As brands inevitably explore partnerships, integrations, or sponsored visibility within AI platforms, consumers will likely question the impartiality of those recommendations. Insights teams must track these perceptions meticulously, as even small signs of bias can quickly undermine trust in both the AI and the partnered brand. The evolution of how AI platforms monetize their systems while maintaining consumer trust will be a key dynamic this year.

What Brands Should Do Now

• Prepare Your Product Data for AI Discovery: Treat product titles, attributes, imagery, and reviews as the new SEO. Ensure information is structured, accurate, and easily interpretable by AI systems. If AI can’t fully understand your product, it won’t confidently recommend it.
• Design for Non-Linear Journeys: Map the specific moments when people turn to AI for advice - the language they use, the context of the query, and the points where trust is either strengthened or broken. Understanding which categories are most "agent-dependent" helps brands anticipate where to influence decisions most effectively.
• Use Transparency as Brand Protection: AI will interrogate claims and surface inconsistencies. Ambiguity erodes trust. Ensuring transparency and consistency across product messaging, reviews, and supporting content is essential for maintaining brand credibility in this new era.

Insights Opportunities for the AI Commerce Era

Yogesh Chavda’s comment during the panel really made the bigger picture snap into focus: we are, unequivocally, entering a Golden Age for Insights. But this moment isn’t just about the surge in research opportunities around AI commerce—it’s about the transformation of the insights function itself.

New research capabilities now allow insights teams to explore complex behavioral shifts at unprecedented speed and scale. Platforms like Conveo make it possible to run rich, niche, and previously hard-to-execute studies efficiently. The ability to gather robust data quickly means insights can become central to decision-making, helping brands tackle backlogs and finally run the essential studies they’ve long wanted.

The AI-mediated journey that inspired this panel highlights the kind of research that AI-led platforms simplify. For the AI commerce era, that could include:

• Observing AI Interactions: Mapping AI-mediated journeys by capturing real prompts and responses through video or screen-recorded AI-led interviews.
• Brand Visibility & Selection Tracking: Monitoring which brands AI surfaces, which get overlooked, and how this shapes real-time consideration sets.
• Consumer Response to AI Partnerships: Understanding how consumers perceive and react to brand × AI provider integrations or sponsored visibility.

This is for sure is a brilliant example of a moment where insights can and should lead, giving brands the knowledge they need to shape strategies in a space that is moving fast and becoming central to commerce, yet still largely unknown.

Interested in the topic? Catch up on the session recording here.