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Character coming out of smartphone with cart of Christmas tree and gifts

34% of US Shoppers Plan to Use AI for Holiday Deals, YouGov Survey Finds

October 9, 2026 Rachel Kim – Technology Editor Technology

Less than half of US adults planning to shop during Black Friday and Cyber Monday intend to use artificial intelligence for their holiday purchases, according to a YouGov survey published by cnet.com. While planned AI adoption for holiday sales more than doubled over the past year from 16 percent to 34 percent, consumer hesitation remains high, with 47 percent of respondents stating they did not use AI to shop last year and have no plans to start this season.

The Tech TL;DR:

  • Planned US consumer use of AI for holiday shopping climbed to 34 percent this year, up from 16 percent last year, cnet.com reported.
  • Consumer comfort drops off sharply at checkout, with only 5 percent willing to let AI complete an approved purchase and 4 percent allowing automated transactions without prior approval.
  • Key consumer concerns include inaccurate or outdated pricing data (56 percent) and biased or sponsored recommendations designed to favor advertisers over best deals (51 percent).

Global Adoption Rates Show a Stark Divide in Consumer Trust

The YouGov data highlighted by cnet.com reveals that the United States lags significantly behind international markets regarding AI-assisted retail engagement. While only 18 percent of US adults have used AI tools to shop, 54 percent of adults in Saudi Arabia and 50 percent in India report using them. An additional 21 percent of US respondents indicated they have not used AI yet but would consider doing so. For Black Friday shoppers specifically, adoption is higher, with 30 percent having already used AI for shopping and 27 percent considering it. Conversely, 40 percent of US adults stated they would not consider using AI for holiday shopping under any circumstances.

34% of US Shoppers Plan to Use AI for Holiday Deals, YouGov Survey Finds

Consumer Boundaries Stop Hard at the Point of Purchase

Shoppers who do engage with AI generally restrict its utility to the discovery phase of retail, utilizing algorithms for product research, finding deals, and comparing alternative items. Among Black Friday shoppers surveyed by cnet.com, 43 percent expressed comfort using AI to find the best deal, 37 percent use tools to track price changes, and 34 percent rely on bots to compare similar products. However, these figures plummet as the transaction workflow advances toward checkout. Only 9 percent feel comfortable having AI add items to a digital cart, 5 percent accept AI completing an approved purchase, and a mere 4 percent trust an autonomous agent to make a purchase without direct prompting.

Data Privacy and Algorithmic Bias Fuel Holiday Hesitation

Consumer reluctance is heavily driven by apprehension over data handling and recommendation integrity. According to the cnet.com findings, 56 percent of shoppers fear AI systems possess inaccurate or outdated information, while 51 percent worry about biased or sponsored recommendations steering them toward advertiser-backed outcomes rather than actual savings.

# Sample CLI cURL request to inspect API payload headers 
# and verify no personally identifiable information (PII) is transmitted.
curl -X POST "https://api.shopping-assistant.internal/v1/query" 
     -H "Content-Type: application/json" 
     -H "Authorization: Bearer test_token_secure" 
     -d '{"query": "soccer gifts for child", "include_user_profile": false}'

To mitigate privacy risks during seasonal shopping, security analysts suggest avoiding the input of sensitive personal data—such as exact ages or specific skill levels—into consumer-facing chat interfaces. Simple queries regarding product categories are typically sufficient for discovery without compromising personal identifying details or payment credentials.

Disclaimer: The technical analyses and security protocols detailed in this article are for informational purposes only. Always consult with certified IT and cybersecurity professionals before altering enterprise networks or handling sensitive data.

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