Share and intensity of work current AI systems can materially affect.
Market Research Analysts AI displacement risk
Summarization, draft segmentation, and desk research are exposed, but domain judgment, study design, stakeholder context, and synthesis make this a strong augmentation case.
Likely potential for exposed tasks to move to software after workflow integration.
The role changes most where analysis is treated as report production. It is more resilient where analysts own framing, interpretation, and decisions.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-05-02. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
30 O*NET task statements matched to SOC 13-1161. The displayed task profile combines these official task statements with the current public score model.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
Official task evidence
O*NET task matches for Market Research Analysts
The current evidence import matched 30 task statements from Task Statements 30.2. These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset 30.2
Matched tasks 30
SOC 13-1161
- Core task / ID 5434
Prepare reports of findings, illustrating data graphically and translating complex findings into written text.
- Core task / ID 5433
Collect and analyze data on customer demographics, preferences, needs, and buying habits to identify potential markets and factors affecting product demand.
- Core task / ID 5439
Conduct research on consumer opinions and marketing strategies, collaborating with marketing professionals, statisticians, pollsters, and other professionals.
- Core task / ID 5435
Measure and assess customer and employee satisfaction.
- Core task / ID 5443
Devise and evaluate methods and procedures for collecting data, such as surveys, opinion polls, or questionnaires, or arrange to obtain existing data.
- Core task / ID 5438
Measure the effectiveness of marketing, advertising, and communications programs and strategies.
Source: O*NET Resource Center, Task Statements. Raw import target:
data/raw/onet/task-statements-30-2.txt.
Task profile
Where AI changes the work
Summarize survey responses
Exposure 72, automation 52%, augmentation 66%.
Draft audience segments
Exposure 58, automation 35%, augmentation 70%.
Design research plan
Exposure 36, automation 14%, augmentation 58%.
Advise stakeholders
Exposure 25, automation 8%, augmentation 42%.
Task Exposure Automation Augmentation
Summarize survey responses 72 52% 66%
Draft audience segments 58 35% 70%
Design research plan 36 14% 58%
Advise stakeholders 25 8% 42%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
Moderate Insights Strategist
Training horizon: 3-6 months. Skill overlap 80. Wage preservation signal 104.
- Lead stakeholder framing
- Design decision-ready artifacts
- Validate model-generated themes
adjacent role
Moderate User Researcher
Training horizon: 4-9 months. Skill overlap 68. Wage preservation signal 98.
- Practice interview guides
- Build usability test plans
- Synthesize mixed evidence
Comparison guides
Compare the next move before you commit
3-6 months
Market Research Analysts to Insights Strategist
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Market Research Analysts into Insights Strategist.
4-9 months
Market Research Analysts to User Researcher
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Market Research Analysts into User Researcher.
What the AI risk score means for Market Research Analysts
The displacement pressure score for Market Research Analysts is 45. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Summarize survey responses carries 52% automation pressure, while Draft audience segments carries 70% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $76,950. Employment context: Growing knowledge-work role. Typical education: Bachelor's degree.
Wage vulnerability is 38, while transition feasibility is 76. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Moderate displacement pressure
- High productivity upside
- Human validation remains important
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Market Research Analysts, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Prompted analysis
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Research design
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Narrative synthesis
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Experiment framing
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Insights Strategist, such as lead stakeholder framing.
- By 90 days, compare internal openings and external postings for Insights Strategist or User Researcher and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Market Research Analysts
Will AI replace Market Research Analysts?
Summarization, draft segmentation, and desk research are exposed, but domain judgment, study design, stakeholder context, and synthesis make this a strong augmentation case. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Market Research Analysts work are most exposed to AI?
Summarize survey responses and Draft audience segments show the strongest automation pressure in this model. Draft audience segments and Summarize survey responses are better treated as AI-augmented work.
What should Market Research Analysts learn next?
Start with Prompted analysis, Research design, Narrative synthesis. The most practical adjacent paths in this model are Insights Strategist and User Researcher.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
International Labour Organization / 2025 Generative AI and Jobs: A Refined Global Index of Occupational Exposure McKinsey Global Institute / 2023 Generative AI and the Future of Work in America O*NET / current public database Occupation, task, skill, and work-activity data US Bureau of Labor Statistics / current public release Occupational Employment and Wage Statistics