US dataswitch to UK
Economists
studying economic and statistical data in area of specialization, developing programs or policy recommendations to achieve environmental goals in cost-effective ways and preparing and delivering presentations to communicate economic and environmental study results. If that's your week, this page is about your job.
The honest answer
This job is splitting in two: studying economic and statistical data in area of specialization is work AI now does quickly and cheaply, and supervising research projects and students' study projects is work it can't touch.
Which half fills your week decides your exposure. The ledger below shows which rows you can move toward.
Your week, as this page understands it
Conduct research, prepare reports, or formulate plans to address economic problems related to the production and distribution of goods and services or monetary and fiscal policy. May collect and process economic and statistical data using sampling techniques and econometric methods. The job title says “economists”. The real job is the part underneath: supervising research projects and students' study projects. That is the thing someone has to be right about.
The exposed part of this job is specific, and we won’t pretend it is coming back. But economists is not one task. It is 34 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is supervising research projects and students' study projects, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 41%
- changing shape
- 42%
- staying human
- 17%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 59 out of 100 (53–65 allowing for uncertainty): partial exposure, across 34 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.
How we know this
What is measured: Every published task statement for economists is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- 3 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
14 tasksTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Studying economic and statistical data in area of specialization
This is reading one thing and writing another: economic in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Study economic and statistical data in area of specialization, such as finance, labor, or agriculture.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Working through economic and statistical data in a specialist field is exactly what analysis tools do well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Writing technical documents or academic articles to communicate study results or economic forecasts
This is reading one thing and writing another: technical documents in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Write technical documents or academic articles to communicate study results or economic forecasts.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Writing up study results and forecasts into technical documents is a strong fit for drafting tools.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Compiling, analyzing
This is reading one thing and writing another: data in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Compile, analyze, and report data to explain economic phenomena and forecast market trends, applying mathematical models and statistical techniques.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Building statistical models and writing up the forecast is highly automatable given the data.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Collecting and analyzing data to compare the environmental implications of economic policy or practice alternatives
This is reading one thing and writing another: data in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Collect and analyze data to compare the environmental implications of economic policy or practice alternatives.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Comparing policy alternatives against collected data is structured analysis software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Changing shape
14 tasksTasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.
Conducting research on economic and environmental topics
The software now makes the first pass at research, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Conduct research on economic and environmental topics, such as alternative fuel use, public and private land use, soil conservation, air and water pollution control, and endangered species protection.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Environmental economics research is well documented, but framing the question and defending the method needs an economist.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Studying the socioeconomic impacts of new public policies
The software now makes the first pass at the socioeconomic impacts of new public policies, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Study the socioeconomic impacts of new public policies, such as proposed legislation, taxes, services, and regulations.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Impact studies use documented methods, but judging how a specific policy will land needs real expertise.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Providing advice and consultation on economic relationships
The software now makes the first pass at advice, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Provide advice and consultation on economic relationships to businesses, public and private agencies, and other employers.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: General economic advice can be drafted, but clients pay for judgment from an adviser they trust.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Staying human
6 tasksTasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.
Preparing and delivering presentations to communicate economic and environmental study results
The value here is that a specific person handles presentations and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Prepare and deliver presentations to communicate economic and environmental study results, to present policy recommendations, or to raise awareness of environmental consequences.” (O*NET task statement)
How this row was scored
Exposure score: 39 out of 100 (32–46 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Slides and scripts can be drafted quickly, but delivering them convincingly needs a person in the room.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Explaining economic impact of policies to the public
The value here is that a specific person handles economic impact of policies and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Explain economic impact of policies to the public.” (O*NET task statement)
How this row was scored
Exposure score: 39 out of 100 (32–46 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Clear explanations can be drafted, but the public listens to a person they find credible.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Supervising research projects and students' study projects
The value here is that a specific person handles research projects and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Supervise research projects and students' study projects.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Supervising researchers and students depends on knowing each person's work and coaching them.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Show the other 24 tasks
Monitoring or analyzing market and environmental trends
shifting to AIThis is reading one thing and writing another: market in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Monitor or analyze market and environmental trends.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Tracking market and environmental indicators and spotting the trend is data work software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Developing economic models, forecasts or scenarios to predict future economic and environmental outcomes
shifting to AIThis is reading one thing and writing another: economic models, forecasts or scenarios in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Develop economic models, forecasts, or scenarios to predict future economic and environmental outcomes.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Building forecasting models and scenarios is quantitative work with plenty of published method to draw on.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Reviewing documents written
shifting to AIThis is reading one thing and writing another: documents written in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Review documents written by others.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reading a colleague's document and giving useful comments is well within reach of current tools.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Forecasting production and consumption of renewable resources and supply, consumption and depletion of non-renewable resources
shifting to AIThis is reading one thing and writing another: production in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Forecast production and consumption of renewable resources and supply, consumption, and depletion of non-renewable resources.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Forecasting resource supply and depletion is modeling work built on published data.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Identifying and recommending environmentally friendly business practices
shifting to AIThis is reading one thing and writing another: friendly business practices in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Identify and recommend environmentally friendly business practices.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Good practice in this area is widely documented, so a solid recommendation list can be produced quickly.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Developing systems for collecting, analyzing and interpreting environmental and economic data
shifting to AIThis is reading one thing and writing another: systems in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Develop systems for collecting, analyzing, and interpreting environmental and economic data.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Designing data collection and analysis systems is well-documented technical work.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Developing environmental research project plans
shifting to AIThis is reading one thing and writing another: environmental research project plans in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Develop environmental research project plans, including information on budgets, goals, deliverables, timelines, and resource requirements.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Drawing up a research plan with budgets, deliverables and timelines is well-structured planning work.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Performing complex, dynamic and integrated mathematical modeling of ecological, environmental or economic systems
shifting to AIThis is reading one thing and writing another: complex, dynamic and integrated mathematical modeling of ecological in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Perform complex, dynamic, and integrated mathematical modeling of ecological, environmental, or economic systems.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Complex mathematical modeling of economic and ecological systems is code, which these tools write well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Writing social, legal or economic impact statements to inform decision makers for natural resource policies, standards or programs
shifting to AIThis is reading one thing and writing another: social, legal or economic impact statements in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Write social, legal, or economic impact statements to inform decision makers for natural resource policies, standards, or programs.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Impact statements follow a documented format, and a named official signs off the finished statement.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Conducting research on economic issues
shifting to AIIt is the same call made over and over on research, with a right answer to check it against. That is what a model is trained on.
importance 4 · CoreSource: “Conduct research on economic issues, and disseminate research findings through technical reports or scientific articles in journals.” (O*NET task statement)
How this row was scored
Exposure score: 65 out of 100 (58–72 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: The writing and literature work is well supported, but original research still needs the economist's judgment.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Formulating recommendations, policies or plans to solve economic problems or to interpret markets
changing shapeThe software now makes the first pass at recommendations, policies or plans, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Formulate recommendations, policies, or plans to solve economic problems or to interpret markets.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Recommendations can be drafted, but choosing between them needs experience of how the specific market behaves.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Developing economic guidelines and standards
changing shapeThe software now makes the first pass at economic guidelines, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Develop economic guidelines and standards, and prepare points of view used in forecasting trends and formulating economic policy.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Drafting forecasting guidelines is straightforward; deciding the institution's position is a judgment call.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Writing research proposals and grant applications to obtain private or public funding for environmental and economic studies
changing shapeThe software now makes the first pass at research proposals, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Write research proposals and grant applications to obtain private or public funding for environmental and economic studies.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Proposal drafts come out usable, but tailoring the case to a specific funder still takes real work.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Examining the exhaustibility of natural resources or the long-term costs of environmental rehabilitation
changing shapeThe software now makes the first pass at the exhaustibility of natural resources, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Examine the exhaustibility of natural resources or the long-term costs of environmental rehabilitation.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Published data helps, but estimating resource exhaustion and long-run rehabilitation costs involves large judgment calls.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Conducting research to study the relationships among environmental problems and patterns of economic production and consumption
changing shapeThe software now makes the first pass at research, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Conduct research to study the relationships among environmental problems and patterns of economic production and consumption.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: The literature is rich, but connecting environmental problems to production patterns needs original analytical judgment.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Developing programs or policy recommendations to achieve environmental goals in cost-effective ways
changing shapeThe software now makes the first pass at programs, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Develop programs or policy recommendations to achieve environmental goals in cost-effective ways.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Options can be drafted, but choosing a workable policy depends on knowing the local politics and constraints.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Assessing the costs and benefits of various activities
changing shapeThe software now makes the first pass at the costs, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Assess the costs and benefits of various activities, policies, or regulations that affect the environment or natural resource stocks.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: The cost-benefit method is documented, but valuing environmental effects involves contested judgment calls.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Developing programs or policy recommendations to promote sustainability and sustainable development
changing shapeThe software now makes the first pass at programs, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Develop programs or policy recommendations to promote sustainability and sustainable development.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Sustainability recommendations can be drafted, but the workable ones depend on local circumstances.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Teaching theories, principles and methods of economics
changing shapeThe software now makes the first pass at theories, principles and methods of economics, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Teach theories, principles, and methods of economics.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Economics teaching material is abundant, but students learn from a teacher responding to them live.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 4/4.
Interpreting indicators to ascertain the overall health of an environment
changing shapeThe software now makes the first pass at indicators, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 2 · SupplementalSource: “Interpret indicators to ascertain the overall health of an environment.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Indicators are documented, but reading them as a picture of one environment's health needs local knowledge.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Demonstrating or promoting the economic benefits of sound environmental regulations
changing shapeThe software now makes the first pass at the economic benefits of sound environmental regulations, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Demonstrate or promote the economic benefits of sound environmental regulations.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Arguments can be drafted, but persuading an audience of the case depends on the person making it.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Teaching courses in environmental economics
staying humanThe value here is that a specific person handles courses and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Teach courses in environmental economics.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Course material is easy to prepare, but teaching a class is live work with students.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Providing litigation support, such as writing reports for expert testimony or testifying as an expert witness
staying humanThis work happens in the physical world: litigation support, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Provide litigation support, such as writing reports for expert testimony or testifying as an expert witness.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (11–25 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Expert reports can be drafted, but being the expert witness means a named person answering for the analysis.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Testifying at regulatory or legislative hearings concerning the estimated effects of changes in legislation or public policy
staying humanThis work happens in the physical world: regulatory, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Testify at regulatory or legislative hearings concerning the estimated effects of changes in legislation or public policy, and present recommendations based on cost-benefit analyses.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (3–17 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Written evidence can be drafted, but testifying at a hearing means an expert appearing in person.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
What this job pays, and how many people do it
- Median pay
- $124,720a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 17,790in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)
What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.
Why this is shifting
The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: technical documents in, a record out. The rows above are exactly that shape: studying economic and statistical data in area of specialization and writing technical documents or academic articles to communicate study results or economic forecasts. What it cannot do is be trusted in person, which is what research projects run on: someone specific doing it and standing behind it. Which is why this page talks about your tasks changing, not your job ending.
Your move
Over a pint: what I’d tell you if you were my friend
Your week is splitting in two, and which half fills it is the whole question. Studying economic and statistical data in area of specialization is going; supervising research projects and students' study projects is not.
So, given all that: 41% of this job's task weight sits in rows the software is already learning, 42% in rows that change shape rather than disappear, and 17% in rows it is nowhere near. That is the position, measured across 34 scored tasks. It is not a forecast about you.
The occupation is an average and you are not, so the first job below is finding out where your own week actually sits.
This week: one thing
Print the task ledger above and put your own hours next to each row. Roughly, in pen, in one sitting. Then look at which group your hours actually pile up in. Twenty minutes, this week.
- What you end up holding
- your own week, on one page, sorted into what is shifting and what is not
- How long it takes
- about twenty minutes
If printing it isn’t practical: Read the rows off this page and write the same list on the back of an envelope. Same twenty minutes, same page, and it works just as well said out loud to someone who knows the job. The point is your hours next to the rows, not the paper it is on.
Over the next 90 days
Volunteer toward the durable end, visibly. Over the next ninety days put your hand up for the work in the bottom group (supervising research projects and students' study projects) and let people see you doing it. Not a new project: the same job, with your mix deliberately tilted. The point is that when the rota or the reorganisation comes, the version of you people picture is the one doing the part that stays.
Over the next 12 months
Claim a specialism at the durable end and let the other end go. Over a year, deliberately become the person who handles supervising research projects and students' study projects, and deliberately stop being the first choice for the rows in the top group. That trade costs something, because the exposed work is often the comfortable work. Decide it on purpose rather than by drift. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.
The roads out of here, and why I am not sending you down them
I looked at the obvious moves out of this job, and here is what I found.
I checked the 12 nearest US occupations to economists (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was environmental scientists and specialists, including health: only about 2% of its durable work is work you already do and it pays 34.1% less. Your own job splits about 41/59: that share of the list sits in the top exposure band and the rest does not. On this evidence the honest move is inside the job rather than out of it. Become the person who owns “conduct research on economic and environmental topics”, and let the exposed end go.
How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.
3 moves I checked and rejected
These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.
Environmental Scientists and Specialists, Including Health
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already forecast production and consumption of renewable resources and supply, consumption, and depletion of…, and their equivalent is to prepare plans to manage renewable resources. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $82,220 against your $124,720, 34.1% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Biological Scientists, All Other
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already write research proposals and grant applications to obtain private or public funding for…, and their equivalent is to write grant applications to obtain funding. Across both published task lists that is about 1% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 1% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $98,920 against your $124,720, 20.7% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Anthropologists and Archeologists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already write research proposals and grant applications to obtain private or public funding for…, and their equivalent is to write grant proposals to obtain funding for research. Across both published task lists that is about 1% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 1% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $70,770 against your $124,720, 43.3% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 41% of its task weight, across 34 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The whole-job doom story
Nothing on this page says this job ends. It says the mix inside it moves. Half the rows above are unchanged or changing shape, and the plan is about which half your week sits in. That is a very different problem, and a solvable one.
Panic-buying a course
Do the twenty-minute sorting exercise first. Most people who buy a course before they have done it buy the wrong one, and the free services listed below will tell you the same thing without charging for it.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Actuaries, economists and statisticians is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
In UK official statistics this job is counted as Actuaries, economists and statisticians. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for economists, and we are not going to point you at the nearest one and call it a fit.
There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 41% of the work on this page is already inside what they can do.
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
The AI Authority is a general community about working with AI, not a course for economists. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.
Noted, and thank you. We’ll email you if a Space for economists launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.
No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace Economists?
- Not as a job, but it is already doing parts of the work. Across the 34 official task statements scored for Economists (United States, SOC 19-3011), 41% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 59 out of 100 (range 53–65, band: partial). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Economists” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Study economic and statistical data in area of specialization, such as finance, labor, or agriculture” (83/100, very high); “Compile, analyze, and report data to explain economic phenomena and forecast market trends, applying mathematical models and statistical techniques” (83/100, very high); “Monitor or analyze market and environmental trends” (83/100, very high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
- Which tasks in “Economists” stay human?
- About 17% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Testify at regulatory or legislative hearings concerning the estimated effects of changes in legislation or public policy, and present recommendations based…” (10/100, minimal); “Provide litigation support, such as writing reports for expert testimony or testifying as an expert witness” (18/100, minimal); “Supervise research projects and students' study projects” (26/100, low). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
- What should someone working in “Economists” do about AI?
- Start from the ledger rather than the headline: 41% of this job's weighted core work is exposed, and roughly 17% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
- How is the AI exposure score for Economists calculated?
- Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 34 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
Worth knowing about these figures
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 3 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.