We don't like beating dead horses at Weavely, so we'll avoid writing a generic introduction on how artificial intelligence is the "future" of survey research. We wrote this article with a single question in mind: do AI-generated surveys outperform those created by humans? We'll start by going through some data on the use of AI within the insights industry and some practical applications. Most importantly, we'll run you through some of the research that has been done comparing AI vs. human surveys.
AI Surveys: Looking Past the Hype
OK, everyone on LinkedIn is constantly talking about AI. But are your peers actually using AI technology in their research process? Consider the graph below, which is taken from User Interview's "State of User Research Report (2024)". Most notably, the proportion of researchers (including product managers, researchers, UX designers, etc.) that use AI in their research jumped from 20% in 2023 to a whopping 57% in 2024.
Furthermore, Nature conducted a survey on AI use among 1600 scientific researchers. They found that 30% of researchers use AI in their work. Surprisingly, as shown in the graph below, even researchers that don't use AI clearly see its advantages. Moreover, everyone seems to agree that AI will play a prominent role in research in the next decade.
Practical Applications of AI in Survey Creation
So how do you go about leveraging AI to build surveys? Here are three examples to apply to your data collection process.
Generating and Rephrasing Survey Questions
Probably the most obvious application of AI: creating and optimising questions for surveys. You don't even need to be a prompting genius to reap the benefits here. Some basic prompts will enable you to create survey questions or optimise survey structures. You can also feed existing questions to AI and have them checked for clarity and bias. In case that sparks your interest, we've written a more hands-on article on this topic.
Data Analysis
This isn't one of those "use AI for everything" blog articles. If most of the data you collected comes from closed-ended questions you don't really need AI to create a detailed analysis, just use charts and graphs! However, we all know how tedious it can be to run through unstructured answers to open-ended questions. LLMs are prime candidates here to save time during the analysis phase of your research. Concretely, you can let tools like ChatGPT analyse responses, categorise them, perform sentiment analysis, etc.
Generating and Testing Survey Responses
It's one thing to create a survey, but an entirely different thing to gather sufficient survey results. We all know the pain of getting too few responses and being unable to draw any actionable insights from them. Luckily, AI can help you meet your survey goals even if your target audience is non responsive. LLMs are great at impersonating particular personas, and serious research has shown the effectiveness of combining human data and responses with AI-generated ones. In fact, we've written an entire article discussing the pros and cons.
AI Survey Generator vs. Humans: Who Writes Better Questions?
So AI can power entire parts of your survey creation process. But is that also a good idea? Or more specifically, are AI-generated survey questions better than human ones? It's a tough question to answer conclusively, so we'll try to be as nuanced as possible.
AI vs. Human Content in General
AI is shaking up content creation, but does it actually outperform human effort? Let’s get straight to the numbers.
A survey of 700 U.S. consumers found people prefer AI-generated content over human-written pieces. In six different tests, ranging from blog post introductions to social media captions, AI consistently outperformed human writers. Even in subjective cases, like an intro for a post about the best cat food, AI beat humans 54% to 46%. The survey data suggests that AI-generated content is often perceived as clearer, more structured, and easier to digest.
But preference doesn’t always translate to performance. A five-month study by NP Digital compared AI-written and human-written blog content and found a stark difference in traffic. Articles written by humans attracted 5.44 times more visitors than those generated by AI. And when factoring in the time spent writing, human-created content still had the edge: for every minute invested, human articles generated 4.10 visitors, while AI-written pieces lagged behind at 3.25. In other words, AI might rapidly produce "correct" content. But it lacks the depth and emotional nuance that people can instil in their work.
So, what does this mean for survey design? If AI can generate well-structured content that people prefer but struggle to engage with at scale, how does that translate to the way it writes survey questions? That’s what we’ll explore next.
Human vs. AI Questions: The Experiment
When it comes to crafting AI surveys, AI has speed on its side, but does it have the same level of quality and nuance as a human researcher? Let’s look at the research.
A study comparing AI-generated and human-written medical exam questions found that AI could produce 50 multiple-choice questions in just over 20 minutes, whereas human experts took 211 minutes for the same task. That’s a huge efficiency boost, but speed isn’t everything. When researchers evaluated the quality of the questions, AI’s output was slightly weaker. It scored 7.56 out of 10 in relevance, compared to 7.88 for human-crafted questions. While that might not seem like a huge gap, the difference was statistically significant. AI-generated questions also tended to be more generic and lacked the contextual depth that human experts naturally incorporated. AI can help those looking to speed up survey creation, but it still requires human refinement.
Another study by FlexMR put an AI survey generator to the test against human researchers to see how well it could generate survey questions for market research. The AI-produced questions were grammatically correct, logically structured, and on-topic, but they lacked depth. While human researchers designed questions that followed a natural flow and considered how respondents might interpret them, AI-generated questions were often too rigid or surface-level.
The biggest issue is AI's struggle with contextual relevance. It produces technically valid questions but has trouble linking them together meaningfully within a broader survey draft. The study found that AI was useful as a brainstorming tool, but human oversight was necessary to refine and structure the final survey to uncover key insights.
So, what’s the verdict? AI can absolutely help create surveys faster, but quality still depends on human input. AI tends to produce well-structured but generic questions, while human researchers ensure depth, flow, and contextual accuracy. If you’re looking for a valuable tool to speed up survey creation, AI is a great option. But a hybrid approach is still the way to go for truly insightful surveys.
Popular AI Survey Makers
Looking to build a survey using AI? You can have your pick from many online AI tools: Jotform, Weavely, Typeform, Cognito, Hotjar AI, SurveyMonkey Genius, and more. If you’re curious about how they stack up, we break them down in detail in our comprehensive guide on AI form builders.
Frequently Asked Questions
Can You Use AI for Surveys?
General-purpose LLMs such as ChatGPT can help you design surveys. Dedicated platforms such as Weavely will build entire surveys for you.
Is There an AI that Does Surveys?
Yes! AI powered survey generators like SurveyMonkey Genius, Typeform AI, and Weavely help create, analyze, and optimize surveys with minimal effort.
How to Create a Survey with AI?
Use an AI powered survey maker like Weavely or Jotform AI to generate questions, refine wording, and structure your survey for better engagement and insights.
Can AI-generated questions fully replace human-crafted ones?
Not entirely. AI can generate structured, clear questions, but human input ensures relevance, context, and emotional nuance in survey design.
