AI Consumer Index: Why AI Shoppers Are Already Your Top Buyers

A new number just reset the AI timeline for every retail and CPG executive in America: $37 billion. That is the amount of additional annual spending Numerator has tied directly to AI-engaged households through its newly launched AI Consumer Index, a measure that connects AI sentiment and usage with verified, receipt-level purchase data. The Index identifies Health & Beauty, Apparel, and Electronics as categories with the greatest potential for AI-enabled shopping disruption, with $37 billion in additional annual spending among AI-engaged households underscoring the scale of the impact.

For years, boardrooms have debated AI shopping disruption as a hypothetical. Numerator's data proves it is already a balance-sheet reality. With more than 30% of U.S. households now using AI weekly, these insights offer an early view into where AI-enabled shopping could gain traction. That is not a niche of early adopters. That is nearly a third of the American consumer base, and they spend meaningfully more than everyone else.

This is exactly the kind of signal Matt Britton has spent his career decoding. As founder of Suzy and one of the country's most in-demand AI keynote speakers, Matt Britton has built his reputation on identifying consumer shifts before they show up in quarterly earnings calls. Matt Britton's research consistently shows that the companies who win are the ones who treat emerging consumer behavior as a present-tense growth lever, not a future risk to monitor.

The AI Consumer Index gives Fortune 500 insights leaders a rare gift: a clean, quantified definition of who the AI-engaged shopper is and exactly how much more valuable they are. The question Matt Britton poses to every executive audience is simple. If you already know this segment outspends your average customer, why is your product data, loyalty program, and search strategy still built for 2019?

What Is the AI Consumer Index and Why Does It Matter Now?

The AI Consumer Index is a new benchmarking tool from Numerator that measures how AI-engaged consumers spend compared to the average U.S. shopper. The AI Consumer Index comes from Numerator's Total Commerce Panel and benchmarks household spending among three AI-engaged consumer groups—regular AI users, consumers with positive AI sentiment, and consumers who use AI while shopping—against the average U.S. shopper, with findings based on July 2026 fielding. Rather than relying on self-reported surveys alone, Numerator layers AI attitudes and behaviors on top of verified, panel-based purchase data drawn from more than 170,000 consumers, according to the report.

The result is a scoring system where each Index score is benchmarked against the average U.S. consumer (100), allowing brands to quickly identify where AI-engaged shoppers over- or under-index across categories, retailers, and brands. That structure matters because it moves the AI conversation out of theory and into something a CFO can model. Insights teams no longer need to guess whether AI engagement correlates with spend. The Index already did the math.

Matt Britton frequently tells audiences at keynote events that the biggest mistake large organizations make is waiting for "proof" before acting on a trend. Numerator just delivered the proof. Numerator quantified the value of AI-engaged households and learned that AI-engaged households spend approximately $2,000 more annually across CPG, General Merchandise, and QSR than the average U.S. household, making AI-engaged shoppers a disproportionately valuable consumer cohort.

Where AI Shopping Disruption Is Already Happening

The Index flags three categories as ground zero for near-term disruption: Health & Beauty, Apparel, and Electronics. AI-engaged consumers spend above average in Electronics, Apparel, Footwear & Accessories, and Health & Beauty, categories where product discovery and consideration could be influenced by AI. These are categories defined by high consideration, frequent comparison shopping, and a constant stream of new product launches, exactly the conditions where a shopper is most likely to open a chatbot before opening a product page.

Retailers are not experiencing this disruption uniformly. eCommerce and value retailers could see AI reshape shopping behavior before traditional grocers, with Costco, TJX Companies, and Amazon over-indexing among AI-engaged consumers, while traditional grocers Ahold Delhaize and Albertsons under-index. Even restaurant brands are not immune. Urban-oriented restaurant chains could see greater exposure to AI disruption, as Chipotle, Panera Bread, and Jack in the Box over-index among AI-engaged households, while Arby's, Culver's, and Dairy Queen see below-average spending.

This pattern lines up with what other researchers are finding across the AI shopping landscape. One industry trust report found electronics and apparel sit at opposite ends of the confidence spectrum, noting that "Apparel sits at opposite ends of two indices" as both a research-confidence ceiling and an AI-trust floor. Matt Britton points to this nuance often in his talks on Gen Z consumer behavior: the categories where AI influence is growing fastest are not always the categories where consumers fully trust AI's final recommendation yet. That gap is where brands win or lose share.

Three category dynamics stand out for business leaders building 2026 strategy:

• Health & Beauty faces the steepest exposure because routine, replenishment-style purchases are easy for an AI agent to automate once trust is established.
• Apparel sees high AI usage for discovery and styling, yet the lowest trust scores for final purchase recommendations, creating a narrow window where brand storytelling still matters.
• Electronics commands the highest AI trust of any category, making it the most likely vertical to see agent-led purchasing scale first.

The $2,000 Question: How Much More Do AI-Engaged Shoppers Really Spend?

Beyond the headline $37 billion figure, Numerator's household-level data answers a question every CMO has been asking privately: does AI engagement actually predict higher spend, or is it just noise? The data says it predicts spend clearly. Although AI adoption varies across generations and income groups, regular AI users spend 5-13% more per household than non-users across the categories Numerator tracks.

That spending premium is not confined to a single platform or use case. Numerator has found that over 30% of U.S. households use AI weekly, contributing nearly 32% of spend across CPG, GM and QSR. In other words, a group that represents roughly three in ten households is already responsible for nearly a third of category spend. That is the definition of a high-value segment hiding in plain sight, and it is precisely the kind of data point Matt Britton builds into his keynote content for Fortune 500 clients evaluating AI keynote presentations for their leadership offsites.

Sentiment is also compounding the effect. More than three-quarters (76%) of consumers who view AI positively use it daily or weekly, compared with just 17% of consumers with neutral or negative sentiment. That 59-point gap tells insights leaders something actionable: brand sentiment toward AI itself, not just AI capability, is now a predictor of commerce behavior. Companies that help consumers feel confident about AI are indirectly building a larger addressable audience of high-spend shoppers.

Why Trust Remains the Biggest Barrier to Agentic Commerce

Agentic commerce, the practice of AI systems researching, comparing, and in some cases completing purchases on a consumer's behalf, is advancing faster than most retail organizations have planned for. But adoption is uneven, and trust is the governor on the engine. Trust remains a significant barrier to AI-enabled commerce, as nearly half of consumers (48%) are concerned about how their personal data is collected and used, while 41% cite payment security concerns.

Still, actual shopping use of AI is growing quickly among the most engaged users. AI-assisted shopping remains early, but adoption rises sharply among regular users: nearly one in ten U.S. households report using AI while shopping, with usage doubling among regular AI users, pointing to regular AI users as an early audience for AI-enabled shopping experiences. That doubling effect is the clearest early signal that agentic commerce will not arrive evenly. It will concentrate first among the households already most comfortable with AI in other parts of their lives.

Separate research on AI shopping trust reinforces how real the gatekeeper effect has become. One study found that among consumers who already shop with AI, over half have abandoned a purchase after an AI assistant raised a concern, while roughly 40% say AI's suggestions are well-suited to their needs often or always. That dual role, as both recommender and filter, means brands no longer control the full narrative at the point of consideration. An AI system now sits between a brand's message and a consumer's wallet, and it decides what gets surfaced.

Matt Britton's position on this is direct: brands that treat AI trust as a customer service issue are thinking too narrowly. It is a data infrastructure issue. If a brand's product attributes, reviews, and specifications are not structured in a way large language models can parse accurately, that brand effectively becomes invisible to a growing share of high-value shoppers, regardless of how strong its in-store or traditional ecommerce presence remains.

Building an Agent-Ready Strategy Before Competitors Do

The practical challenge for Fortune 500 insights and marketing teams is translating index data into operational change. Matt Britton, author of Generation AI and a frequent voice on The Speed of Culture podcast, frames the opportunity around three priorities that apply across verticals, including real estate and financial services audiences he regularly addresses.

First, audit product data for AI readability. Numerator's generational research has already caught brands getting overlooked by AI systems that rely on public content instead of verified purchase data, even when those brands dominate actual sales. That mismatch between AI recommendation lists and real consumer preference is a solvable problem, but only for brands that invest in structured, accurate data feeds now.

Second, build loyalty programs that reward AI-assisted discovery, not just traditional purchase paths. If a meaningful share of high-value customers are researching through AI before buying, loyalty mechanics need to recognize and incentivize that journey rather than ignore it. Third, monitor category-specific trust signals continuously. Electronics, Apparel, and Health & Beauty each show distinct trust and spend patterns, which means a one-size-fits-all AI strategy will underperform compared to category-tailored approaches.

Key Takeaways for Business Leaders

• Prioritize Health & Beauty, Apparel, and Electronics for immediate AI readiness audits, since these categories show the largest spend gaps in Numerator's Index.
• Quantify the AI-engaged segment within your own customer base using loyalty and CRM data to estimate the equivalent of that $2,000-per-household spending premium.
• Invest in structured, verified product data so AI systems recommend what consumers actually buy rather than what is simply most published online.
• Address data privacy and payment security concerns directly in customer-facing AI experiences, since trust remains the top barrier to deeper engagement.
• Treat AI shopping disruption as a current-quarter planning issue, not a future-state innovation project, given that AI-engaged households already represent billions in measurable spend.

Frequently Asked Questions

What is the AI Consumer Index?

The AI Consumer Index is a benchmarking tool launched by Numerator that connects AI engagement, including sentiment, weekly usage, and AI-assisted shopping, with verified household purchase data. It scores AI-engaged consumer groups against the average U.S. shopper (indexed at 100) to show where AI-enabled shopping is already influencing real spend across categories, retailers, and brands.

How much more do AI-engaged shoppers spend than average consumers?

According to Numerator, AI-engaged households spend approximately $2,000 more annually across CPG, General Merchandise, and QSR than the average U.S. household . Collectively, this AI-engaged segment accounts for an estimated $37 billion in additional annual spending concentrated most heavily in Health & Beauty, Apparel, and Electronics.

Which retail categories are most exposed to AI shopping disruption?

AI-engaged consumers spend above average in Electronics, Apparel, Footwear & Accessories, and Health & Beauty, categories where product discovery and consideration could be influenced by AI. These categories combine frequent comparison shopping with high consideration, making them the most likely places for AI agents to influence purchase decisions first.

Is agentic commerce already changing how people shop?

Yes, though adoption remains concentrated among the most engaged AI users. AI-assisted shopping remains early, but adoption rises sharply among regular users, with nearly one in ten U.S. households reporting using AI while shopping and usage doubling among regular AI users. Trust around data privacy and payment security remains the primary factor slowing broader adoption.

The Window to Act Is Open Now

The AI Consumer Index does not describe a distant future. It describes current, verified consumer behavior that is already worth $37 billion a year. Matt Britton's message to Fortune 500 leaders is consistent: the brands that win the next decade will be the ones who build agent-ready data, loyalty, and trust strategies while this segment is still underpriced by the broader market.

Waiting for more certainty is itself a strategic decision, and it is the wrong one. Matt Britton has spent his career helping executive teams convert consumer signals like this into board-ready action plans, and the AI Consumer Index is one of the clearest signals to emerge all year. Organizations ready to move should explore how a Matt Britton keynote can align leadership around this opportunity, or visit Matt Britton's speaker page to book him for an upcoming event.

The companies that treat AI-engaged shoppers as today's highest-value customers, not tomorrow's hypothetical disruption, will be the ones writing next year's growth story.