98% of market researchers use AI; 40% report errors, 29% rely on AI support
Almost every market researcher—98% according to the latest benchmark—has woven AI into the daily grind. Yet the same study flags a stark paradox: four in ten users say the tools still stumble, producing errors that can skew insights. That mismatch between ubiquity and reliability is reshaping how teams think about responsibility and oversight.
Some firms have begun treating AI as a safety net rather than a replacement, assigning it tasks that augment, not dictate, the analytical process. Others are pulling back, wary that unchecked algorithms could amplify bias or misinterpret data trends. The tension is palpable, and it forces a hard look at workflow design.
While the tech is impressive, the human element remains a gatekeeper. This reality is reflected in how researchers currently describe their AI involvement and in the way they picture the technology’s role a decade from now.
About one‑third of researchers (29%) describe their current workflow as “human‑led with significant AI support,” while 31% characterize it as “mostly human with some AI help.” Looking ahead to 2030, 61% envision AI as a “decision‑support partner” with expanded capabilities including generative featu
About one-third of researchers (29%) describe their current workflow as "human-led with significant AI support," while 31% characterize it as "mostly human with some AI help." Looking ahead to 2030, 61% envision AI as a "decision-support partner" with expanded capabilities including generative features for drafting surveys and reports (56%), AI-driven synthetic data generation (53%), automation of core processes like project setup and coding (48%), predictive analytics (44%), and deeper cognitive insights (43%). The report describes an emerging division of labor where researchers become "Insight Advocates" -- professionals who validate AI outputs, connect findings to stakeholder challenges, and translate machine-generated analysis into strategic narratives that drive business decisions.
The survey shows near‑universal adoption—98 % of market researchers now use AI, and 72 % do so daily. Yet four in ten admit the tools produce errors, a gap that raises immediate concerns about reliability. About one‑third (29 %) describe their workflow as “human‑led with significant AI support,” while another 31 % say it’s “mostly human with some AI help.” How much confidence can practitioners place in outputs that are known to be flawed?
The data suggest a cautious balance: humans still dominate decision‑making, even as AI nudges the process forward. Looking ahead, 61 % of respondents envision AI as a “decision‑support partner” by 2030, implying broader roles for generative features. Still, the survey does not clarify whether error rates will improve as reliance grows.
Unclear whether the trust gap will narrow enough to justify deeper integration. For now, the industry appears to be navigating between enthusiasm for efficiency and lingering doubts about accuracy.
Further Reading
- 28 AI marketing statistics you need to know in 2025 - SurveyMonkey
- 44 NEW Artificial Intelligence Statistics (Oct 2025) - Exploding Topics
- 60+ Generative AI Statistics You Need to Know in 2025 - AmplifAI
- The GenAI Divide: State of AI in Business 2025 - MLQ.ai
Common Questions Answered
What percentage of market researchers currently use AI, and how often do they engage with it?
According to the benchmark, 98 % of market researchers now use AI, and 72 % of them engage with AI tools on a daily basis. This near‑universal adoption highlights AI's integration into routine research workflows.
How prevalent are errors in AI tools among market researchers, and what impact does this have on confidence in the outputs?
Four in ten (40 %) market researchers report that AI tools produce errors that can skew insights. This significant error rate raises concerns about reliability and prompts practitioners to maintain human oversight to ensure confidence in the results.
What proportion of researchers describe their workflow as "human‑led with significant AI support," and how does this compare to other workflow models?
About one‑third of researchers (29 %) describe their workflow as "human‑led with significant AI support," while an additional 31 % characterize it as "mostly human with some AI help." These figures show that most teams still prioritize human judgment, using AI as an augmenting tool rather than a replacement.
What future capabilities do market researchers anticipate for AI by 2030, and which features are expected to be most widely adopted?
Looking ahead to 2030, 61 % of respondents envision AI as a "decision‑support partner," with 56 % expecting generative features for drafting surveys and reports, 53 % anticipating AI‑driven synthetic data generation, 48 % foreseeing automation of core processes like project setup and coding, and 44 % expecting expanded predictive analytics. These capabilities are seen as the next wave of AI integration in market research.