Technology — like AI — has transformed how we work, but it's also changing how we approach everything from planning dates and vacations to shopping and gift-giving.
And this holiday season, American shoppers are leaning on technology to help them make smarter, more value-driven decisions as they navigate a new landscape shaped by tariffs, inflation and rising costs.
The rise of AI shopping assistants
Today’s shoppers, especially Gen Z and Millennials, are embracing AI tools that promise to simplify and optimize the retail experience.
A recent consumer survey of 1,000 people across the US — conducted by TEAM LEWIS — found that nearly one in three Americans (32%) say they’re likely to use AI for shopping, with adoption rates soaring to 76% for Gen Z and 78% for Millennials.
So, what are these digital natives using AI for? Everything from price comparisons and personalized recommendations to budget tracking and real-time alerts.
In short, AI-powered shopping assistants have changed how consumers approach purchases. Instead of relying solely on instinct or manual research, shoppers now use digital tools to:
- Track spending and stay within budget
- Compare prices and product features across retailers
- Receive personalized recommendations based on preferences and past behavior
- Get real-time alerts on price drops and sales
These features help consumers prioritize needs over wants, wait for the best deals and maximize savings — making every dollar count, especially in a challenging economic climate.
But there's a hidden dependency powering AI assistants: the product data retailers provide.
Related must-read: The 5 Biggest Retail Trends in 2026
The data trust challenge
While AI tools offer tremendous value, their effectiveness depends entirely on the quality of the data they use. Unfortunately, many consumers report that their experiences with AI shopping assistants have fallen short. TEAM LEWIS found that:
- 39% say they’ve received inaccurate or misleading information
- 14% have encountered major issues, like buying the wrong product
The holiday wish list for AI features, price comparisons, real-time alerts and budget tracking can only deliver if the underlying product data is accurate, complete and up-to-date. Missing details, outdated specs and inconsistent attributes can lead to poor recommendations and erode consumer trust.
Why retail data management matters
Retailers are at a turning point. As more consumers rely on AI to guide their shopping decisions, brands must ensure their product data is trustworthy and reliable.
Master data management (MDM) solutions play a critical role in this process, centralizing and governing product information to eliminate errors and inconsistencies.
When retailers invest in robust data management, they help AI tools deliver accurate recommendations, build consumer confidence and foster long-term loyalty. MDM is the key to shifting AI-powered shopping from a convenience to a competitive advantage.
But retailers that don't prioritize data quality risk being filtered out of AI recommendations, limiting visibility among the growing number of shoppers using AI-powered tools. Simply put, data quality is a non-negotiable.
The future of shopping: Smarter, trusted, and data-driven
AI-powered shopping assistants are here to stay, and their influence will only grow. For consumers, they offer unprecedented control and insight. For retailers? The challenge is clear: deliver the data trust that makes AI experiences truly valuable.
The question isn't whether AI will reshape retail — it's whether your data is ready for it.
See the Real Cost of Bad Data in Retail
Learn more about what causes bad customer data, the consequences and how you can avoid bad customer data pitfalls in retail.
