Scientific research and laboratory

ISCO-08 2131, 2113, 3141, 3111

Research scientist, Laboratory technician, Analytical chemist, Biologist, Research associate, Laboratory manager

AI exposure36%

Headcount need, in FTE

Exposure range

Your current headcount

FTE

Need in 203095 FTE-5 FTE (-5%)

Need in 203589 FTE-11 FTE (-11%)

How AI is used on these tasks today

Automation 51%Augmentation 49%

In AI conversations about this job's tasks: the AI does the task itself (automation) or helps the person do it (augmentation).Anthropic Economic Index, April and May 2026. Occupations: Medical Scientists, Except Epidemiologists, Biological Technicians, Chemists. AEI

1. Exposure 36%Average automation potential of the job's tasks. Range for this family: 17 to 56%.ILO occupations used: Biologists, Botanists, Zoologists and Related Professionals (40%), Chemists (39%), Life Science Technicians (excluding Medical) (38%), Chemical and Physical Science Technicians (26%). ILO data

2. Strategic ceiling 100%Your call: how much of this potential do you want to capture? Nobody can set it for you.

3. Adoption speed midpoint 2030

Inherits your company stance, adjustable for this family.

4. Conversion to headcount sensitive 30%Default 30%: Research capacity never matches the hypotheses worth testing; time saved on literature and analysis mostly goes into more experiments.

Target AI skills

level 1 to 4

Foundation

Use AI assistants every day

Frame and phrase a request

Check and challenge AI outputs

Protect data and respect the rules

Applied

Rethink one's process with AI

Analyse data with AI

Produce content with AI

Delegate to and supervise AI agents

Expert

Build and integrate AI solutions

Evaluate and make AI solutions reliable

AI governance and risk management

Job skills

Growing in value

Experimental design for AI-guided screening
Critical review of AI-generated hypotheses
Lab data management and integrity
Running and troubleshooting lab automation
Scientific computing and modelling

Losing value

Manual literature reviews
Writing protocols and study reports from scratch
Routine data processing and statistics
Manual sample logging and transcription

How the job will change

Bench work stays human for a long time: preparing samples, running assays, maintaining instruments, interpreting an unexpected result. AI changes what surrounds it. Assistants review literature and patents in hours, draft protocols and study reports and process instrument data. Predictive models suggest which molecules or formulations to test first, and automated platforms run more experiments with fewer manual steps.

The job moves towards experiment design and scientific judgement. Researchers decide which AI-generated hypotheses deserve lab time and check that models are not learning from biased or poor-quality data. Data integrity and traceability become core skills, especially in regulated labs. A good scientist tomorrow is comfortable with code and statistics, and a good technician knows how to run and troubleshoot automated platforms.

2026-2027: Assistants for literature review, protocols and report drafting.
2028-2030: AI-guided screening and lab automation spread in large research centres.
2031+: More experiments per researcher; technicians move towards automation and data roles.

Watch out

Profiles combining a scientific discipline with data science are rare and expensive. Without internal training, labs will depend on a few hybrid experts while bench technicians see their tasks change without a clear path. See the seniority outlook below.

What if you hired fewer juniors?

Your 2036 seniors are the juniors you hire today.

Seniors available in 2036-5%2 FTE short

Gap above 5% from2036

Your seniority mix today

Juniors (0 to 3 yrs in the profession)25%Seniors (10+ yrs)30%

Mid-level (3 to 10 yrs in the profession, the remainder)45%

Cut in junior hiring -40%

For

Advanced settings

Juniors promoted each year25%Juniors leaving each year12%Senior gap filled by external hiring0%If every company makes the same bet, senior profiles will be scarce and expensive.

Seniority mix, % of today's headcount

Juniors25%Mid-level42%Seniors28%

2026 2036

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How the numbers are built

Every headcount figure combines four assumptions. Three come pre-filled from public research and job family defaults. The strategic ceiling is yours to set.

Public researchExposureAverage automation potential of the job's tasks, from the ILO's 2025 task-level scores.

Your decisionStrategic ceilingHow much of that potential you choose to capture. Your decision, not ours.

Your companyAdoption speedHow fast your company moves, set once for the whole company.

Job family defaultConversion to headcountHow much of the productivity gain becomes fewer people rather than more output.

Headcount effect

Seniority outlook

A flow model with three levels of experience in the profession. Promotion and exit rates are set so that today's mix stays stable when hiring does not change: any gap you see comes from the junior hiring cut alone.