AI agents have not only arrived in the market research industry - they are starting to take over. From survey design to data analysis, AI agents are completing multi-step tasks with little to no human intervention.
And while the use of agentic AI in market research is already ubiquitous, it can be hard to understand why it is being used in some cases.
AI Agents & Market Research
This list highlights some of the recent applications of AI agents in the market research and insights sector. However, it is just scratching the surface in terms of what is currently out there, and what we can expect in the not-so-distant future.
So why are there already so many different market research AI agents? Agentic AI is all about achieving a desired outcome by completing specific tasks. This means it is great at things like content creation, supply chain management, and even financial transactions.
Market research, on the other hand, has one very broad goal: to figure out how things work. There are so many different ways you can go about this, whether that's interviewing individuals and analyzing the open-ended responses, or collecting customer feedback survey data and crunching the numbers.
So, to break down market research into a select few tasks that could be completed by an AI agent is, for all intents and purposes, impossible.
This has given rise to a robust ecosystem of market research AI agents. Companies are designing agents that perform a select portion of the market research process, such as data collection, segmentation, and simulations. This means there is a huge amount of competition and innovation in the space.,
Strategy & Insight Generation Agents
1. Displayr - AI Research Agent
Use case: An AI-powered research assistant that can 50-500x manual reporting workflows
Displayr’s Research Agent is an AI-powered assistant, designed to automate the grunt work that comes with survey reporting (think everything from data analysis to reporting). It's also a way to eliminate the 'cold start' that slows down so many researchers - no more looking at an empty screen, instantly draft a report, then work from there. The AI can:
- Identify the right data to use
- Analyze it using statistical techniques
- Create visualizations and charts
- Summarize the results
- Deliver strategic recommendations
Survey & Interview Design Agents
2. Fastuna - Yasna.AI and Automoderator 2.0
Use case: Conversational agent for survey and guide creation
Researchers simply describe their project’s goals, and Fastuna’s AI composes detailed discussion guides and questionnaires. The upgraded Automoderator adapts in real-time during interviews, formulating questions based on the respondent's answers.
3. Pureprofile + Nexxt Intelligence (inca)
Use case: Conversational survey agent
Pureprofile leverages Nexxt Intelligence's "inca" agent to deliver chatbot-style surveys that boost engagement while analyzing open-ended responses at scale.
4. Metaforms
Use case: Survey programming co-pilot
Metaforms' AI agent streamlines survey programming for Forsta/Decipher users, reducing build time by up to 70%. It can also turn emailed sample requests into structured feasibility plans using natural language inputs, review collected data and create reports using AI.
Data Collection & Qualitative Interviews Agents
5. Outset
Use case: Video interview agent
Outset's agents conduct video interviews at scale, merging the depth of qualitative interviews with survey-like speed. The platform automatically extracts insights and compiles reports.
6. Discuss
Use case: Autonomous interview management
Discuss is building out AI agents manage the full interview lifecycle - from finding participants to running interviews and analyzing feedback - cutting manual work significantly. The agent processes responses in real-time to ensure more targeted questions throughout the interview.
7. Rival Technologies - Multi-Agent AI Framework
Use case: Modular agents across the MR process
Conversational research firm Rival’s framework introduces agents for data collection, planning, analysis, and reporting. The first agent focuses on unstructured data in the hope of making it easier for researchers to process qualitative feedback at scale. The aim for Rival Technologies is to continue to create modular agents that will eventually be unified into a “Super Agent” to manage end-to-end research, while still enabling human oversight.
8. Qualtrics Experience Agent
Use case: Real-time experience management
Qualtrics is currently extending its conversational feedback experience by assembling an agent that will be capable of interacting directly with customers as they complete feedback surveys. The aim of these Experience Agents is to close the loop and resolve concerns before they turn into negative feedback.
Data Analysis & Synthesis Agents
9. Morning Consult - MorningConsult.AI
Use case: Instant brand tracking
Morning Consult has recently rolled out MorningConsult.AI as a way to provide instant brand tracking. Built on 80 million survey interviews, this AI delivers real-time insights into how brands compare across markets, demographics, competitors, and media channels. The platform also leverages AI agents to assist with tasks like trend analysis and brand reports.
10. Quantilope - quinn AI Agent
Use case: Insight discovery and report building
Quantilope’s “quinn” agent analyzes survey data, builds charts and dashboards, and offers expert-level suggestions for methodologies and storylines.
11. Zappi - Concept Creation Agents
Use case: New product development
Zappi’s AI agents help brands rapidly create and test product concepts by leveraging historical test results and proprietary datasets. The agents pull data from prior concept tests and customer expertise inputs to provide consumer-informed concepts at rapid speed.
12. QualifyAI
Use case: End-to-end qual research
QualifyAI has created agents trained on 20+ years of qualitative research experience are used to generate communications insights, audience segmentations, and idea testing - completing qualitative research at previously unattainable speed and value.
13. Cohere + Ottogrid
Use case: Document-based analysis
Agentic AI outfit Cohere recently acquired automated research company Ottogrid with a view of creating agents that help workers better enrich their data and scale operations.
Search & Decision Support Agents
14. Alation + Numbers Station
Use case: Enterprise data querying
This merger brings together Numbers Station’s AI agents with Alation’s governance tools to make complex data more accessible across enterprises. The aim is to create more agentic AI workflows that operate with enterprise-grade governance and context.
15. Onyx
Use case: Knowledge retrieval
Onyx’s AI agent searches through vast internal documents and knowledge bases using parallel exploration to provide detailed, contextual answers. From a market research standpoint, this will allow for teams to answer technical and non-technical questions based on data from tools tools like Salesforce, SharePoint, and Gong.
16. Gorgias
Use case: Support & insights agent
Originally built for support, Gorgias’ AI teammate can respond instantly to queries, automate tasks, and stay on-brand - all powered by a company’s internal knowledge and systems. The agent is described as a fully autonomous AI teammate, specializing in eCommerce brands.
Marketing & Segmentation Agents
17. Uniphore - Marketing Agents
Use case: Audience insights and segmentation
Uniphore offers agents like Audience Segmentation Agent and Product Knowledge Agent that help marketers explore customer data and create segments using plain English prompts. This will help marketers segment audiences from their customer data platform (CDP) faster and with greater accuracy.
18. Crayon
Use case: Competitive intelligence
Crayon applies AI to track competitors’ moves in real-time and deliver actionable insights, helping brands stay ahead in fast-moving markets.
Simulations & Synthetic Research Agents
19. Aaru
Use case: Simulated consumer behavior
Synthetic data firm Aaru uses a multi-agent system to simulate human behavior. The tool models how people behave and delivers predictive insights based on hundreds of different traits across demographics and psychographics.
20. Spur
Use case: UX & product testing
Not dissimilar to Aaru's use of synthetic data, Spur leverages AI agents to replicate human behavior, instead focusing on navigating websites to detect bugs, improve experience, and optimize conversion paths, especially for eCommerce and travel platforms. Dubbed the first AI QA engineer, the product utilizes video replays to assist in bug reporting.
Automated Insight Surfacing Agents
21. Contentsquare - Sense
Use case: AI insight engine
Contentsquare's Sense AI agents surface relevant insights automatically. The technology combines generative AI with behavioral data across web and mobile to run complex analysis workflows and deliver insights that have been tailored to specific business goals.
Ready to see how Displayr's Research Agent can revolutionize your survey analysis? Book a demo today.
