AI-Guided Consumer Decision Making: The Trust Shift Brands Can't Control

A new global study from Boston Consulting Group just delivered a wake-up call to every Fortune 500 insights team: AI has quietly become one of consumers' most trusted sources of information, and brands do not control it. Among consumers who rely on AI regularly during their purchase journeys, 70% ultimately buy whatever the AI recommends. That is not a marketing statistic. That is a trust transfer happening in real time, at scale, inside systems no CMO can directly manage.

Matt Britton, founder of Suzy and one of the most sought-after AI keynote speakers for Fortune 500 leadership teams, has spent the past year warning executives that the next battle for consumer choice will not happen in owned channels. It will happen inside large language models. Consumers are concentrating their trust on experts, friends and family, and, most surprisingly, AI tools, the fastest-growing source of trusted information, and brands do not control any of these trusted sources. That single finding reframes decades of brand strategy.

For years, brand sentiment tracking has been the gold standard for measuring consumer perception. Surveys, social listening, Net Promoter Score, all of it assumed that brands could shape the narrative through paid media, PR, and owned content. AI-guided consumer decision making breaks that assumption. When a shopper asks ChatGPT, Gemini, or an agentic shopping assistant to recommend "the best running shoe for flat feet" or "the most reliable SUV under $40,000," the brand has no seat at that table unless it has already earned one inside the model's training data, retrieval index, or real-time web signals.

Britton argues this is the moment insights leaders must stop treating AI as a channel and start treating it as a constituency. Being visible to consumers may increasingly depend on being visible to AI systems first. This post breaks down the data behind that shift, what it means for how Fortune 500 companies measure brand health, and the concrete steps leaders can take before their competitors claim the "AI shelf space" first.

What Is AI-Guided Consumer Decision Making?

AI-guided consumer decision making refers to the growing practice of consumers using generative AI tools, chatbots, and autonomous shopping agents to research, compare, and select products before or instead of visiting a brand's website or a retailer's shelf. Rather than clicking through search results or scrolling reviews, shoppers now describe what they need in plain language and let an AI system do the evaluation.

The scale of this shift is no longer speculative. New research from Boston Consulting Group suggests that artificial intelligence is rapidly becoming a trusted intermediary between consumers and brands, with 31% of surveyed consumers already using AI during a purchase journey, roughly three times the level reported 18 months earlier. Within that group, the loyalty behavior is even more striking. Overall, 31% of surveyed consumers already use AI at least occasionally in their purchase journeys, 19% are AI loyalists who rely on it regularly, and 70% of these loyalists ultimately buy the products that AI recommends, making AI the secret driver of choice in many consumer journeys that many brands have not planned for.

This is the core reason Matt Britton built his AI keynote presentations around a simple premise: the brands winning the next decade will be the ones that understand AI is not a tool consumers use occasionally. It is becoming the default first stop for high-consideration purchases, and its influence compounds every time a consumer's trust in it is rewarded with a good outcome.

AI Trust Brands 2026: Why Consumers Are Moving Their Confidence to Machines

The BCG research does not suggest consumers trust AI blindly. It suggests they trust it more than the alternatives currently available to them. More than half of consumers say they don't fully trust any single source of information, according to new research from Boston Consulting Group. That erosion of confidence in traditional sources, advertising, influencer content, even branded websites, has created a vacuum, and AI is filling it fast.

The forward trajectory matters as much as the current snapshot. AI is already among consumers' most trusted sources, along with experts and peers, and they expect their trust in it to increase by 15 percentage points by 2030, faster than any other source. No other information channel, not social media, not traditional advertising, not even word of mouth, is projected to grow trust at that pace.

Part of the reason is cognitive relief. Four in ten consumers feel overwhelmed by the volume of information they encounter, and they are increasingly turning to AI as a trusted source to help them cut through that noise. Britton frequently tells Fortune 500 boards that this overwhelm is the real driver of AI adoption. Consumers are not necessarily choosing AI because it is smarter than a human expert. They are choosing it because it is faster, always available, and does not try to sell them anything on the surface.

This is precisely why Britton titled his book Generation AI around the idea that trust architecture, not media spend, will define brand winners going forward. A generation raised on algorithmic recommendation is now applying that same comfort to high-stakes purchase decisions, from mortgages to medical devices to enterprise software.

Agentic Commerce and Consumer Behavior: The New Front Door to Retail

Agentic commerce describes AI systems that do more than recommend. They research options, compare pricing, and in some cases complete transactions on a consumer's behalf, with permission. This is the layer where AI stops being an advisor and starts becoming a proxy shopper.

AI is becoming a new gateway to retail, changing where consumers discover products, compare options, and increasingly make purchasing decisions, as shoppers describe what they want to an AI assistant and receive recommendations based on their needs, budget, and preferences, with some able to move from that conversation toward checkout without leaving the AI platform. Full autonomy is not yet universal, but the direction of travel is unmistakable.

Adoption numbers back this up across multiple independent studies, not just BCG's. A staggering 99% of shoppers are aware of AI, and 70% have used one or more AI tools or features to assist with shopping, with ChatGPT leading in usage and recognition. Separately, a 2026 Consumer Priorities Report found that nearly three-quarters of consumers already use generative AI to some extent, and among those users, nearly 80% use tools like ChatGPT, Claude, and Gemini to research products, compare services, or plan purchases, with most saying they act on those recommendations.

The competitive implication is severe for legacy brand strategy. Shoppers are seeing only the top two-to-three options in their searches based on context and trust, in contrast to the digital shelf of over 25 items or the physical shelf of over 100 items that they've seen in the past. That is a brutal compression of consideration sets. Britton often illustrates this to executive audiences at his keynote engagements as the difference between competing on a crowded shelf and competing to be one of three names an algorithm chooses to say out loud.

This dynamic plays out differently by sector, and Britton tailors his talks accordingly. Financial services firms face agentic assistants comparing loan terms and fee structures in seconds, a topic explored in depth on his finance industry page. Real estate faces AI tools that pre-qualify listings before a human agent ever gets a call, covered on his real estate keynote page. The mechanics differ, but the underlying threat, invisibility inside the AI layer, is identical.

Generative Engine Optimization (GEO) Marketing: The New SEO Battlefield

Generative engine optimization, often shortened to GEO, is the emerging discipline of optimizing brand content, data, and digital presence so that AI systems surface, cite, and recommend a brand accurately. It is the natural successor to search engine optimization, but the rules are fundamentally different because the "search results page" no longer exists in the traditional sense.

Instead of ranking for keywords, brands now need to earn a place inside the reasoning process of a model. Consumers are increasingly asking generative AI to do the evaluation for them, asking AI to compare products, summarize reviews, explain tradeoffs, and recommend the best option instead of researching dozens of websites themselves. If a brand's product specifications, reviews, and differentiators are not structured in a way models can parse, cite, and trust, that brand simply does not exist in the conversation.

The upside for challenger brands is real. New BCG research found that in more than half of AI-assisted journeys, AI introduces consumers to new brands. This cuts both ways. Category leaders can lose share of consideration overnight if their content infrastructure is weak, while smaller competitors can leapfrog decades of brand-building simply by being better structured for AI discovery.

Britton discusses this exact dynamic on his podcast, The Speed of Culture, where he regularly interviews brand leaders navigating the shift from traditional SEO teams to GEO-focused content strategy. His consistent message: GEO is not a technical add-on for the IT department. It is a board-level priority because it determines whether a brand's story gets told accurately, told by a competitor, or not told at all.

Why Fortune 500 Insights Leaders Must Track "AI Perception Share"

Britton's most provocative recommendation to Fortune 500 clients is a new metric he calls AI perception share, the frequency and favorability with which a brand is surfaced, described, and recommended across major AI platforms relative to competitors. Traditional brand tracking studies ask consumers what they think of a brand. AI perception share asks what the machines that increasingly mediate purchase decisions think of a brand, and whether that assessment is even accurate.

This matters because AI models can misrepresent, under-represent, or completely omit a brand based on outdated training data, thin web presence, or poor structured data. That makes AI more than another marketing channel. It is becoming a decision layer. A decision layer that a brand cannot see into, audit in real time, or directly petition is a governance risk, not just a marketing gap.

Suzy, the consumer intelligence platform Britton founded, has built its research methodology around exactly this blind spot, helping brands understand not just what consumers say in surveys but how AI systems are actually representing them at the moment of decision. Learn more about how enterprise teams are using this approach at Suzy's platform.

Fortune 500 companies that treat this as a curiosity rather than a core measurement discipline are, in Britton's words, flying blind into their largest addressable channel. The following list captures the operational shifts leaders need to prioritize immediately:

• Audit how leading AI platforms currently describe your brand, products, and pricing versus competitors
• Build structured, verifiable product data that AI systems can cite with confidence
• Establish a cross-functional GEO team spanning marketing, data, and legal
• Monitor AI perception share on a recurring basis, not as a one-time project
• Invest in third-party expert content and reviews, since AI systems weight independent validation heavily

Key Takeaways for Business Leaders

• Measure AI perception share alongside traditional brand sentiment, since nearly a third of consumers already use AI during purchase journeys and that adoption has roughly tripled in eighteen months.
• Prioritize generative engine optimization as a board-level initiative rather than a marketing side project, given that AI introduces consumers to new brands in more than half of AI-assisted journeys.
• Audit how AI platforms currently represent your brand's products, pricing, and differentiators to identify gaps before competitors close them.
• Invest in structured, citable content and third-party validation, since trust in AI is expected to grow faster than any other information source through 2030.
• Train executive teams on agentic commerce mechanics now, before autonomous purchasing agents move from early adoption to mainstream default.

Frequently Asked Questions

What is AI-guided consumer decision making?

AI-guided consumer decision making is the growing pattern of consumers relying on generative AI tools and chatbots to research, compare, and choose products during their purchase journey. Recent global research shows nearly a third of consumers already use AI this way, and among frequent users, the majority act on the AI's specific recommendations.

How does generative engine optimization differ from traditional SEO?

Traditional SEO optimizes for ranking on a search results page with links a human clicks through. Generative engine optimization focuses on structuring brand data, reviews, and content so AI models can accurately parse, cite, and recommend a brand within a conversational answer, often without the consumer ever visiting a website.

Why do consumers trust AI more than traditional brand marketing?

Many consumers feel overwhelmed by the sheer volume of information and conflicting sources they encounter daily, and they turn to AI to simplify that noise into a clear recommendation. AI is also perceived as less commercially motivated than paid advertising, even though the underlying training data and partnerships can still carry bias.

What is agentic commerce and how does it affect brand strategy?

Agentic commerce refers to AI systems that can research options, compare products, and complete purchases on a consumer's behalf with permission, moving shopping from browser tabs into a single conversational interface. Brands must ensure their product data is accurate and discoverable within these systems, since consumers may never see a traditional storefront during the decision process.

Ready to Prepare Your Organization for the AI Trust Shift?

The data is unambiguous: AI has become the fastest-growing trusted source in the consumer decision journey, and it is happening inside systems most Fortune 500 brands do not measure, audit, or influence directly. Matt Britton has spent his career translating exactly this kind of inflection point into board-ready strategy, from the rise of social commerce to the current shift toward AI-guided consumer decision making. Companies that wait for more certainty before acting will find the AI perception battle already decided without them.

Matt Britton is available for keynote engagements, executive workshops, and advisory sessions on AI-guided consumer behavior, generative engine optimization, and the future of brand trust. Visit Matt Britton's speaker platform to explore keynote topics, or learn more about his AI keynote presentations tailored specifically for Fortune 500 leadership teams navigating this shift in real time.