98% of market researchers use AI; 40% report errors, 29% rely on AI support
When I chatted with a few market researchers, almost everyone, about 98% in the latest benchmark, mentioned they’re already using AI every day. Still, the same data points out a weird gap: roughly four out of ten say the tools trip up, spitting out errors that could tilt the results. That mix of ubiquity and wobbliness is making teams rethink who’s really in charge of the analysis.
Some companies treat AI more like a safety net, handing it tasks that boost the work without taking the wheel. Others are pulling back, worried that unchecked algorithms might magnify bias or misread trends. The tension feels real, and it pushes us to look closely at how we design our workflows.
The tech can be impressive, but the human still ends up as the gatekeeper. Researchers’ own descriptions of AI use today and their visions for 2030 echo that feeling.
About one-third of researchers (29%) say their current workflow is “human-led with significant AI support,” while 31% call it “mostly human with some AI help.” Looking ahead to 2030, 61% picture 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.
Almost everyone in the field is already using AI, the poll puts it at 98 % of market researchers and about 72 % say they touch it every day. Still, roughly four out of ten admit the tools slip up, which makes reliability a real worry. I saw that 29 % label their process “human-led with significant AI support,” while another 31 % call it “mostly human with some AI help.” That leaves me wondering how much trust we can actually put in outputs we know are sometimes wrong.
The numbers hint at a careful balance: people keep the final say, even though AI is quietly pushing things forward. Looking ahead, 61 % picture AI as a “decision-support partner” by 2030, so we might see more generative features in play. Yet the survey doesn’t say whether error rates will drop as we lean in harder.
It’s unclear if the trust gap will shrink enough to make deeper integration worthwhile. Right now the industry seems to be walking a tightrope between the lure of speed and the nagging doubt over accuracy.
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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.