A new survey of 938 U.S.-based retail investors shows artificial intelligence is becoming a mainstream tool for many individual market participants.
The poll found that 62% of respondents have turned to AI tools to help shape their investment decisions. Engagement patterns vary: roughly one in four use AI on a regular basis, another 27% use it occasionally, and the remainder are in earlier stages of experimentation with these technologies.
Among those who have integrated AI into their process, a majority report positive effects on performance. Sixty-five percent say AI has improved their results, with 17% saying the improvement was significant and 48% saying it was somewhat beneficial. By contrast, 33% say AI made no difference to their returns, and 2% report that performance worsened after using AI-based tools.
Chat-style interfaces rank among the more commonly used tools: 54% of survey participants said they have used AI chatbots such as ChatGPT for investment-related research. The most frequent uses of AI cited in the survey are stock or asset research, with more than 60% of respondents selecting that function, and roughly one-third saying they use tools to parse market news or to generate trading ideas. These results suggest AI is primarily supporting foundational research and idea generation for many retail investors.
Trust in AI-generated output is cautious rather than wholehearted. More than half of respondents - 54% - said they trust AI only somewhat and therefore verify AI findings with additional sources. Smaller shares reported higher confidence levels: 20% said they trust AI mostly, and 4% said they trust it completely. Nearly one in four respondents reported limited or no trust in AI analyses.
Looking ahead, most respondents expect their AI use to grow. Fifty-five percent said they plan to increase their reliance on AI tools, and 38% said they anticipate using them significantly more. This points to further integration of AI features within retail investor workflows as platforms continue to add such capabilities.
Investors cited several clear advantages that are driving adoption. Nearly 40% said AI enables faster analysis of market data. Other commonly cited benefits include reducing emotionally driven decision-making (15%) and identifying opportunities earlier (14%). Still, 20% of those surveyed said they do not see a real advantage from AI tools.
Concerns about AI were also prominent in the survey responses. The most frequently named risk was incorrect or misleading recommendations, cited by 39% of respondents. Market herding was flagged by 24% as a worry, while 21% expressed concern about over-reliance on automation. Eight percent pointed to a lack of transparency in AI models, and another 8% said they had no concerns about AI in investing.
Behavioral measures in the data reinforce a measured approach to the technology. Only 22% of respondents said they use AI very often; 37% reported they use it sometimes, and 16% said they use it rarely. Those figures suggest that for most retail investors AI currently functions as a supplementary tool rather than a constant presence in their process.
Survey participants also described how AI features are being rolled out across platforms, making more advanced analytical capabilities accessible to ordinary investors. While the survey underscored rising adoption, it also showed that many users remain vigilant about validating AI outputs and balancing automated insights with independent checks.
Finally, the survey included promotional information about premium AI-driven services and their performance claims, as well as marketing for subscription options and advanced AI utilities tailored to financial markets. Respondents were also presented with prompts about the best investment opportunities in 2026 and products that pair institutional-grade data with AI-powered analysis; these items were framed as features available to subscribers.
Overall, the findings portray an investor base that is rapidly adopting AI tools for research and idea generation, sees tangible benefits in many cases, but approaches the technology with caution and verification. Most investors expect to increase their use of AI, even as concerns about accuracy, herding, automation dependence, and model transparency persist.