EmergingAI economics, labour and social research

AI Market Structure Researcher

Also called AI Competition Economist

An AI Market Structure Researcher studies who holds power in AI markets and why. They turn questions about concentration, access and competition into evidence a company can use in strategy, policy and partnership decisions.

What they do

They define the market under study, then test how it behaves. That might mean who controls compute, models, data or distribution, and how switching costs and bundling shape choices. They gather evidence from surveys, interviews with buyers and builders, pricing and usage data, and task analysis of how work is done. They build econometric models and write down the mechanism they think is at work. They test the result against different market definitions. They then turn findings into a study that a non-economist can act on. The work often sits inside strategy, policy or research teams under other titles.

What a strong hire delivers

In the first months, a strong hire delivers a clear map of the market the company operates in and where its position is strong or exposed. They produce a first market study with the economic mechanisms stated openly, plus a short note on data gaps and what would change the conclusions. They also leave behind a repeatable method the team can rerun as the market shifts.

How you can tell they are good

Ask for a past study and have them walk through it. Strong people explain why they defined the market as they did and what happened when they changed it. They name the mechanism, not just the correlation. They are candid about weak data and say what they could not conclude. Be cautious of confident answers with no stated limits, or work that is only descriptive.

Why it is hard to fill

Hardly anyone holds this title. The work is usually done by economists, policy analysts or strategy staff who picked it up alongside other duties. The core skill, industrial organisation and platform economics, is specialist, and few people have applied it to AI. Many candidates have the theory but not the field research, or the reverse. Expect to judge on work samples, not job titles.

Where to find them

Look first to economists trained in industrial organisation, working in competition consultancies, regulators, think tanks and university research groups. Platform economists at large technology firms are another source. Labour researchers, sociologists and evaluation scientists with strong survey and interview skills can also fit, particularly when paired with someone strong on econometrics. Policy teams at AI companies often hold quiet talent.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for an AI Market Structure Researcher

  1. Describe a market study you led. How did you define the market, and what did you do when that definition was challenged?

    A strong answer shows a reasoned definition, a test of alternatives and an honest account of how results changed. Worry if they treat the definition as obvious or never tested it.

  2. What economic mechanisms could explain concentration in AI markets, and how would you tell them apart with evidence?

    Look for specific mechanisms such as scale effects, switching costs, access to inputs and network effects, each with a testable implication. Worry about vague claims that big firms simply win.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are hiring an AI Market Structure Researcher to help us understand how competition, concentration and access work in the markets we build in. You will produce rigorous studies that shape our strategy and how we speak to policymakers, partners and customers.

What you will do

  • Define the markets we operate in and test those definitions against alternatives
  • Build econometric analyses of concentration, pricing, access and switching
  • Run surveys and interviews with buyers, builders and other market participants
  • Write market studies that state the economic mechanisms explicitly
  • Document data limits and how they affect conclusions
  • Brief leadership and policy colleagues in plain language

What you will bring

  • Published or internal market studies that show your reasoning end to end
  • Applied industrial organisation or platform economics
  • Strong causal inference and experimental design
  • Experience combining quantitative data with interview or survey research
  • Clear writing for non-specialist readers
  • Honest handling of weak data and uncertain results

Nice to have

  • Experience in a regulator, competition consultancy or policy team
  • Familiarity with how AI products are built and sold
  • Work involving worker or community participation in research

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Public policy and economicsAdvancedAnalyse institutional choices and distributional effects
  • Causal inferenceAdvancedSeparate causal claims from predictive associations
  • Experimental designWorkingChoose comparisons that identify credible effects
  • Worker and community participationWorkingInclude affected workers and communities in decisions

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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