UK AI Exposure · Professional occupations
Actuaries, economists and statisticians
Actuaries, economists and statisticians apply theoretical principles and practical techniques to assess risk and formulate probabilistic outcomes in order to inform economic and business policy, and to analyse and interpret data used to assist in the formulation of financial, business and economic policies in order to maximise growth or improve business performance.
- Employees (UK)
- 43k
- Median annual pay
- £51,520
- Exposure score ?
- 3.8/10 Low 10.0/10 Very high strict reading · with tools is 10.0/10 with-tools reading · strict is 3.8/10
- Wage exposure
- £842m £2.22bn
Higher exposure than 92% of the 379 UK occupations we scored.
What this score means
A handful of tasks in this role are touchable by AI, mostly around paperwork, scheduling and basic writing. The shape of the role stays the same - some parts just get faster.
If you're in this role, here's what to do now
Pick the two or three most repetitive things in your week and try an LLM on them. Most people underestimate what Claude or ChatGPT can already do for admin-shaped work. The time you get back is the dividend.
Almost every routine task in this role is within reach of today's language models. Roles at this level are getting rebuilt - often not by disappearing, but by one person using AI to do three or five people's output.
If you're in this role, here's what to do now
You don't need to be afraid. You need to be the person doing the rebuilding. The operators who learn to direct AI at scale in this kind of work become hugely valuable. The ones who wait to be told what to do get told what to do - and that thing is often 'we don't need as many of you anymore.'
Where a project with Alex usually starts for this role
These are the highest-importance tasks a language model can already handle directly today. In a typical engagement the first wins come from building workflows around these, so they stop eating your team's time.
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Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.
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Calculate sample size requirements for clinical studies.
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Write program code to analyze data with statistical analysis software.
These are the highest-importance tasks AI can already handle when paired with the right tools and context. In a typical engagement the first wins come from building workflows around these — usually the difference between an LLM that can technically do the job and one that actually does it inside your business.
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Draw conclusions or make predictions, based on data summaries or statistical analyses.
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Analyze clinical or survey data, using statistical approaches such as longitudinal analysis, mixed-effect modeling, logistic regression analyses, and model-building techniques.
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Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.
Every role has three or four wedges like these. Finding them takes an hour. Turning them into a workflow your team actually uses takes a few days. Talk to Alex about a project →
The full task breakdown
Every O*NET task for this occupation, split by what AI can already do unaided versus what still needs a human. Importance is O*NET's 1–5 rating of how central each task is to the role.
Tasks via O*NET "Biostatisticians" (15-2041.01).
What AI can already do
8 of 25 tasks · unaided
Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.
Calculate sample size requirements for clinical studies.
Write program code to analyze data with statistical analysis software.
Develop or implement data analysis algorithms.
Prepare articles for publication or presentation at professional conferences.
Write research proposals or grant applications for submission to external bodies.
Design or maintain databases of biological data.
Assign work to biostatistical assistants or programmers.
Where humans still hold the line
17 of 25 tasks
Draw conclusions or make predictions, based on data summaries or statistical analyses.
Analyze clinical or survey data, using statistical approaches such as longitudinal analysis, mixed-effect modeling, logistic regression analyses, and model-building techniques.
Read current literature, attend meetings or conferences, and talk with colleagues to keep abreast of methodological or conceptual developments in fields such as biostatistics, pharmacology, life sciences, and social sciences.
Design research studies in collaboration with physicians, life scientists, or other professionals.
Prepare tables and graphs to present clinical data or results.
Provide biostatistical consultation to clients or colleagues.
Review clinical or other medical research protocols and recommend appropriate statistical analyses.
Determine project plans, timelines, or technical objectives for statistical aspects of biological research studies.
Prepare statistical data for inclusion in reports to data monitoring committees, federal regulatory agencies, managers, or clients.
Plan or direct research studies related to life sciences.
Monitor clinical trials or experiments to ensure adherence to established procedures or to verify the quality of data collected.
Collect data through surveys or experimentation.
Apply research or simulation results to extend biological theory or recommend new research projects.
Develop or use mathematical models to track changes in biological phenomena, such as the spread of infectious diseases.
Analyze archival data, such as birth, death, and disease records.
Design surveys to assess health issues.
Teach graduate or continuing education courses or seminars in biostatistics.
Tasks via O*NET "Biostatisticians" (15-2041.01).
What AI can already do
25 of 25 tasks · with tools
Draw conclusions or make predictions, based on data summaries or statistical analyses.
Analyze clinical or survey data, using statistical approaches such as longitudinal analysis, mixed-effect modeling, logistic regression analyses, and model-building techniques.
Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.
Calculate sample size requirements for clinical studies.
Read current literature, attend meetings or conferences, and talk with colleagues to keep abreast of methodological or conceptual developments in fields such as biostatistics, pharmacology, life sciences, and social sciences.
Design research studies in collaboration with physicians, life scientists, or other professionals.
Prepare tables and graphs to present clinical data or results.
Write program code to analyze data with statistical analysis software.
Provide biostatistical consultation to clients or colleagues.
Review clinical or other medical research protocols and recommend appropriate statistical analyses.
Develop or implement data analysis algorithms.
Determine project plans, timelines, or technical objectives for statistical aspects of biological research studies.
Prepare statistical data for inclusion in reports to data monitoring committees, federal regulatory agencies, managers, or clients.
Plan or direct research studies related to life sciences.
Prepare articles for publication or presentation at professional conferences.
Monitor clinical trials or experiments to ensure adherence to established procedures or to verify the quality of data collected.
Write research proposals or grant applications for submission to external bodies.
Design or maintain databases of biological data.
Collect data through surveys or experimentation.
Apply research or simulation results to extend biological theory or recommend new research projects.
Develop or use mathematical models to track changes in biological phenomena, such as the spread of infectious diseases.
Assign work to biostatistical assistants or programmers.
Analyze archival data, such as birth, death, and disease records.
Design surveys to assess health issues.
Teach graduate or continuing education courses or seminars in biostatistics.
Where humans still hold the line
0 of 25 tasks
When AI is paired with workflow tools, every task in this role is reachable. That doesn't mean the role disappears — it means almost all the routine surface area can be compressed.
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Methodology
This role's exposure score comes from Eloundou et al's 2023 GPT task labels, aggregated by O*NET importance within each O*NET-SOC code, then bridged to UK SOC 2020 via ISCO-08 (ONS Vol 2 coding index) and US SOC 2010 (BLS crosswalk). Employment and median pay come from ONS ASHE Table 14.7a, 2025 provisional. ASHE covers employees only, so self-employed workers are not counted.
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