In the first few weeks of the year, US consumers appeared to settle into a familiar, postholiday rhythm: Their feelings about the economy remained mostly unchanged from the end of 2025. Their reported spending intentions also followed typical seasonal patterns: In essential categories, intent to spend remained largely unchanged, and fewer consumers reported their intent to spend on discretionary goods and services compared with the fourth quarter.
What changed more materially in 2026 so far was not how consumers felt about the economy—but how they gathered product information and made purchase decisions. For the first time, our US ConsumerWise survey explored how consumers are adopting AI (specifically, gen AI) tools for shopping. While millions of US consumers still have not experimented with AI or adopted it into their daily lives, AI is beginning to move from early-adopter stage into the mainstream (the prevalence of AI-related Super Bowl ads this year reflected this shift).
The following charts present insights from our latest ConsumerWise research, exploring how US consumers feel about the economy in early 2026 and how AI is beginning to reshape consumer shopping habits.
US consumers’ economic confidence remained relatively flat in early 2026. Compared with late 2025, a smaller share of respondents reported feeling pessimistic, while a slightly larger share expressed neutral or mixed feelings about the economy. Overall, sentiment in the first few weeks of 2026 mirrored trends observed throughout most of the past year.
Income continued to be the strongest differentiator in economic confidence. On average, the wealthier the consumer, the more optimistic they reported feeling. We also observed some generational differences in sentiment, though these were less pronounced than differences in sentiment by income. Baby boomers had the largest share of pessimistic respondents, followed by Gen X and Gen Z, while millennials had the largest share reporting optimism.
Consumers’ expected spending over the next three months reflected typical first-quarter seasonality. Across essential categories, net spending intent, or the difference between the share of people who intend to spend more on a category and the share of people who intend to spend less, rose for some categories, such as fresh produce. Still, across several categories, net intent remained relatively flat compared with the previous quarter.
Net intent to spend was negative across all discretionary categories and declined quarter over quarter across several of these categories, consistent with a typical postholiday slowdown. Even so, there were a few seasonal bright spots. Net spend intent rose for home improvement and gardening supplies (up 11 percentage points versus the fourth quarter of 2025) and domestic flights (up five percentage points), with additional gains across several travel- and experience-related categories, including short-term rentals, hotel stays, and entertainment away from home. Overall, the data suggest that consumers are planning to spend selectively rather than pull back on discretionary spending across the board.
While their spending plans may not have diverged from seasonal patterns, consumers reported they are seeking information—much of which is related to shopping—in new ways. Among US consumers who reported using AI tools, the greatest share (38 percent) said they used AI to research and understand general topics. Consumers also said they use AI to write and improve content (22 percent) and discover or decide on brands, products, or services to purchase (19 percent).
Overall, 68 percent of survey respondents said they had used at least one AI tool in the past three months (likely an underestimate, given that consumers may use AI-based search or AI functionality within apps without realizing they are using AI). Eighty-five percent of Gen Z and millennial consumers reported adopting AI, compared with 70 percent of Gen Xers and 41 percent of baby boomers. We also found that income was the strongest determinant of AI usage: Higher-income consumers were more likely to report using the technology.
Electronics for home or personal use was the most-cited category for using AI tools to discover or evaluate brands, products, or services. Consumers who used AI to inform their purchases—let’s call them “AI-enabled shoppers”—were nearly twice as likely to do so for electronics as for vehicles. Apparel and experience-related categories, such as restaurants and travel, also ranked relatively high.
Gen Z and millennial AI-enabled shoppers were far more likely than baby boomers to use AI when shopping for fitness and sports products, as well as for beauty and personal care. Younger consumers were also more likely to use AI for groceries and household essentials, suggesting that these shoppers are beginning to consult AI even for routine purchases.
Higher-income consumers were more likely than lower-income consumers to use AI when considering fitness and sports and beauty purchases. By contrast, AI usage for groceries and entertainment purchases did not differ meaningfully by income.
Most of AI-enabled shopper activity centered on the earlier stages of the shopping journey. Sixty-two percent reported using AI to compare options—such as brands, models, prices, and reviews—making it the most common use case. Fifty-five percent said they relied on AI to learn more about a category or product, including what features to consider. Nearly half used it for discovery and inspiration, such as generating ideas for what to buy.
Fewer consumers reported using AI in later stages of the purchase process, such as building or optimizing their basket, checking out, managing repurchases, or seeking postpurchase support. Overall, the findings suggest that consumers use AI primarily for research and decision support rather than transactions or services—for now.
Even so, AI-based search tools are clearly becoming a leading source for decision-making. For consumers surveyed who use AI search, 44 percent said it is their most preferred source of information, ahead of search engines (31 percent), retailer and brand sites (9 percent), and review sites (6 percent). And in AI-generated search summaries, affiliate blogs—websites that earn commissions by promoting third-party products through tracked affiliate links—make up the greatest share of citations (50 percent), equal to the share of citations from user-generated content, academic and market research, brand and retailer sites, and news and media combined, according to data from the digital marketing platform Semrush. This suggests that brands might need to prioritize affiliates in their marketing strategy, even if doing so gives them less direct control over how their products are represented in AI-assisted journeys.
The way US consumers discover and evaluate products is evolving quickly. AI is already embedded in the early stages of the shopping journey—particularly among younger and higher-income consumers—and is beginning to influence both discretionary and routine purchases. As adoption broadens, AI-assisted search and comparison will likely play an increasingly meaningful role in how consumers navigate categories.
For consumer-packaged-goods companies and retailers, the near-term opportunity lies in ensuring their brands appear prominently in AI-assisted research and comparison—across not only owned channels but also the third-party content ecosystems that AI tools frequently draw from. Over time, as consumers become more comfortable using AI throughout the purchase process, companies may also need to rethink their strategies for consideration, basket building, and loyalty in an AI-mediated world. To contact us for more information or to read additional insights, check out our ConsumerWise page.
To see previous ConsumerWise insights, visit our page of 2025 research.
About the Authors
Christina Adams is a partner in McKinsey’s Dallas office, Kari Alldredge is a partner in the Minneapolis office, and Tom Kilroy is a senior partner in the Chicago office.
The authors wish to thank Andrew Pitakos, Eitan Urkowitz, Hannah Wagner, and Tom Skiles for their contributions to this article.
This article was edited by Alexandra Mondalek, an editor in the New York office.