Survey Fraud Is On The Rise- But Is AI To Blame?
Is Rising Survey Fraud Due To AI?
Online survey fraud is on the rise with 40% of surveys done in 2025 believed to be problematic. That translates to 2 billion surveys out of 5 billion market research surveys completed each year. It’s easy to think that the increase is due to the growth of AI usage, but survey fraud has actually been a problem long before ChatGPT caught mainstream fire.
Market research’s struggle with survey fraud for over two decades is fraught with poor quality data. More than simple “errors,” fraud could potentially and significantly skew or distort findings with noise and bias. This could lead to either outright “flat” or negligible results, even unactionable insights when unraveled. Additionally, survey fraud wastes time, effort, and resources, including those expended for detecting and cleaning up fraudulent data. More importantly, it undermines confidence in the market research industry.
AI may be poised to exacerbate the issue with survey fraud, especially now that we’ve begun exploring the realms of synthetic data. Experts agree that AI fraud is apparently still in its early stages at this time but even so, organizations have already prepared measures to combat AI fraud, such as observing typing and mouse movement patterns, identifying “copy/paste” behavior, and flagging nonsensical or incoherent responses. These measures also extend to anticipating or simulating how AI agents would be designed to convincingly mimic human respondents taking surveys and avoid detection, then devising ways to preemptively counter those tactics.
Image: Towfiqu barbhuiya
What Is Human Survey Fraud?
Data quality at present is mostly under increasing threat from human fraud powered by “click farms” more than the AI kind. For all the operational efficiency and productivity it brings, building AI agents sophisticated enough to convince surveys that a “real human” is participating is actually difficult and expensive to scale at this time, while those models that can be employed in large numbers and for cheap are comparatively easy to detect. It would therefore be more cost effective for fraudsters to forego sophisticated AI agents for now and simply stick with human-powered click farms.
Of course that doesn’t stop those engaging in human survey fraud from utilizing AI along with bots, VPNs, and other contemporary technology, as their efforts have resulted in the aforementioned 40% survey fraud rate. While the picture of an overseas operation located in a room with several employees and computers comes to mind, the pandemic had pushed click farms in low-wage countries to expand to home-based setups utilizing multiple smartphones to simultaneously take part in surveys. They’ve even promoted their activities through social media by sharing experiences, information and advice on groups, forums and video-sharing sites on how to enter surveys, pass through screenings, and the like, leading the way for more fraudsters to participate and aggravate the problem.
Another considerable contributing factor to the growing fraud rate is hyperactive respondents, or professional survey takers who attempt to participate in many surveys as possible within a given period of time. They exploit systems and farm incentives by pretending to be legitimate participants and repeatedly entering the same survey with the help of VPNs, device spoofing, cookie clearing, browser emulators, and AI-generated text. Different studies on survey fraud have found hyperactive respondents in every source, panel, and exchange.
Image: Darlene Alderson
The Importance of Ownership of Data Quality
Measures and solutions against human survey fraud like verification checks, logic-based trap questions, and post-survey cleanup exist, but their effectiveness is now in question with the high fraud rate. The prevalence of hyperactive respondents indicate that the present system of vetting and filtering participants is not only falling short but lack teeth in flagging these repeat offenders.
Perhaps rethinking human survey fraud might be key in fighting or even reversing the increasing fraud rate. Online survey fraud has been around for more than twenty years already so we as an industry need to think past of it as just a mere disruption but as a systemic and consistent challenge moving forward. We anticipate the inevitable rise of AI fraud with the exponential growth of synthetic data in the coming years by arming ourselves with innovative detection methods and safeguards to face this emerging issue; why not apply the same rigor, dedication, and layered approach in combating the present threat of human survey fraud?
And instead of limiting our renewed approach to battling human survey fraud by reacting, reviewing and restructuring, why not empower ourselves with a greater focus on ownership of data quality? Rather than accept at face value that fraud has been filtered beforehand or rely that it would be handled post-survey, we assume responsibility for data quality every step of the way, evaluating participant behavior at every stage, erring on the side of caution by flagging suspected hyperactive respondents, and/or leveraging human expertise when distinguishing fraudulent responses. We can take advantage of AI and modern technologies to help us measure, track, and flag possible instances of fraudulent behavior, automating the process wherever relevant while being guided by human oversight.
Ownership of data quality can also go hand in hand with improving participant engagement and polling representivity, potentially unlocking opportunities to discover new insights that would’ve otherwise been hidden by poor quality data.
Let’s be real- fraud could never be fully removed from the survey process. But by caring about the data quality that your market research firm provides, you’re able to mitigate the dangers fraud poses while gaining value at the same time from the insights and breakthroughs you uncover with every challenge you master in this protracted campaign for survey data.
Image: Tumisu
Additional Reading:
The Fraud Problem Reshaping Survey Research
The Rising Issue of Bad Data in Online Surveys Causes and Contributing Factors
The Pervasive Threat of Tech-Enabled Fraud in Survey Research