PYMNTS report finds generative AI users start with low-risk tasks and shift to financial planning, health and learning as confidence grows.
Alpha Score of 33 reflects weak overall profile with poor momentum, poor value, moderate quality, moderate sentiment.
Consumers who spend more time with generative AI gradually trust it with bigger decisions, according to a PYMNTS Intelligence report.
The report, "The End of Casual AI: How Consumers Are Turning Prompts Into Daily Power Tools," tracks how usage patterns change as experience grows. New users typically start with low-risk tasks like product recommendations. A bad recommendation on a computer mouse costs a few dollars. Financial planning or health management is a different category – the stakes are higher, and users wait until they have confidence in the technology and their own ability to direct it.
Experience changes what people ask. Seasoned users treat AI less like a search engine and more like a working partner that organizes information, compares options and explains complex topics. The report found that experienced users rely on AI for learning, health information and financial management at significantly higher rates than newcomers. Those tasks reward ongoing back-and-forth rather than a single prompt.
Product discovery sits at an interesting point. Experienced users still ask AI what to buy, but they are less likely than newcomers to call it essential for that task. That suggests room for improvement in shopping recommendations, product comparisons and the path from research to purchase. For merchants and commerce platforms, the opportunity is to build experiences that earn lasting trust, not occasional visits.
22% of Gen Z consumers use credit to build a financial profile, the report noted. Billtrust CTO said a 1% AI error rate can create 100 problems a day. DraftKings shows rewards in dollars to simplify redemption.
Taken together, the findings point to experience as a primary driver of AI adoption. Consumers who use the technology more continue broadening their use cases, often turning to specialized platforms for different needs. For banks, FinTechs and payment providers looking to expand their AI footprint, the implication is clear: a range of applications for customers at different experience levels matters more than a single tool.
Drafted by a large language model from the source reporting linked above, then screened by automated publishing checks. It is not read by a journalist before publication. Some articles cite our Alpha Score. Verify prices and figures against the original source. Educational coverage, not personalized advice.