■ CRITICAL RISK ■ Sales & Marketing
Largely, yes. The gathering, tabulating, and summarizing that filled most research hours is now machine work, and clients increasingly ask an AI before they commission a study. The insight-and-judgment layer survives — thinner, more senior, and expected to move at AI speed.
“AI surveys millions while you're still designing a focus group.”
Our AI replacement risk score — how we score jobs
The classic market research workflow runs: take a client's business question, design a survey or focus group, field it through a panel provider, clean the responses (screening out the bots and the people answering 'yes' to everything), run the crosstabs, and turn it all into a deck with a story — market sizing, brand tracking, concept tests, pricing studies. Analysts live in survey platforms like Qualtrics, panel marketplaces, and an ocean of PowerPoint. The deliverable is nominally insight; operationally it's often 60 slides due Thursday.
AI has invaded every stage at once. Language models draft questionnaires and discussion guides in minutes. Survey platforms auto-generate analysis and summaries of open-ended responses — the coding of verbatims that once consumed junior-analyst weeks now runs in seconds. Social listening and review-mining tools deliver continuous consumer sentiment without fielding anything. The stranger frontier: synthetic respondents, where models simulate consumer panels, controversial but already marketed as a cheap first pass. Meanwhile desk research — the competitive landscape and market-sizing sections of every report — is exactly what AI research assistants produce on demand. When the client can generate a plausible market overview themselves before lunch, the agency's tabulation-and-summary tier loses its price.
What holds is the part that was always scarce: research design that avoids garbage-in (a biased sample summarizes beautifully), moderating live conversations where a skilled human notices the hesitation before an answer, and the judgment to tell a client their beloved concept tested badly and why. Trust matters too — decisions involving millions in launch spend want a named human vouching for the method. But those skills sit atop far fewer billable hours. Our 94 reflects a pyramid whose base — the junior analysts running tabs and drafting slides — is being automated out from under the apex.
Automatability: our editorial assessment of current and near-term AI capability
Serious pressure is current, not pending. Automated verbatim coding and AI-generated summaries are standard features in survey platforms today, synthetic-respondent products are on the market, and research agencies are restructuring around smaller teams. Through 2030 expect the junior tabulate-and-summarize tier to largely vanish and project timelines to compress from weeks to days, with employment concentrating in research design, moderation, and client advisory. The WEF's Future of Jobs surveys have repeatedly grouped routine analytical roles among those facing displacement, and this field fits the pattern.
The industry isn't dying — companies want more consumer insight, not less — but the labor model is being gutted. Work that billed junior-analyst weeks (coding verbatims, running tabs, drafting decks) now takes machine minutes, so agencies need far fewer people per project. Revenue may hold while headcount falls. The career risk is concentrated at the entry level, where the automatable tasks were the whole job.
Vendors are selling exactly that — simulated panels of AI 'consumers' — and it's genuinely useful as a cheap early screen for obviously bad concepts. It's also genuinely dangerous as a substitute for real humans, since models reflect their training data, not your actual market's quirks. Expect a hybrid norm: synthetic first-pass, real fieldwork for decisions with money on the line. The human moderator survives; the routine field study shrinks.
Escape the tabulation layer as fast as possible — it's the part being automated. Push for exposure to study design, sampling methodology, and client meetings. Learn qualitative moderation, which is scarce and human. And become the office expert in AI research tools; the analyst who delivers a study in two days using the new stack is more valuable than one defending the two-week version.
For casual questions, they already do — a competitive overview that once justified a small desk-research contract is now a prompt. Agencies keep the work where being wrong is expensive: launch decisions, pricing, brand strategy, anything requiring defensible primary data and a methodologist who can stand behind it. The market bifurcates into free-and-instant versus rigorous-and-human, with much less billable middle.