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AI exposure report
Will AI replace Geneticists?
Some of your tasks will be automated. People who use AI will have the edge.
Task exposure to today's AI
Moderate exposure
This is the occupation's typical task mix. Your own score can be up to 30 points higher or lower depending on how you work: routine share, people contact, judgment and how much you already use AI.
Get your personal scoreWill AI replace Geneticists?
Not entirely. Today's AI tools can take on about 46% of the typical work in this occupation, mostly: prepare results of experimental findings for presentation at professional conferences or in scientific journals. The parts that stay human include: Supervise or direct the work of other geneticists, biologists, technicians, or biometricians working on genetics research projects.; Plan or conduct basic genomic and biological research related to areas such as regulation of gene expression, protein interactions, metabolic networks, and nucleic acid or protein complexes.; Extract deoxyribonucleic acid (DNA) or perform diagnostic tests involving processes such as gel electrophoresis, Southern blot analysis, and polymerase chain reaction analysis..
People who learn to use AI for the automatable parts keep the edge. The 3-phase plan below shows where to start.
Which tasks AI can take on
The largest tasks in this occupation, their share of the working week, and how much of each today's AI tools can do.
+ 18 more tasks (47% of the week) in the full test.
Your human edge
- Supervise or direct the work of other geneticists, biologists, technicians, or biometricians working on genetics research projects.
- Plan or conduct basic genomic and biological research related to areas such as regulation of gene expression, protein interactions, metabolic networks, and nucleic acid or protein complexes.
- Extract deoxyribonucleic acid (DNA) or perform diagnostic tests involving processes such as gel electrophoresis, Southern blot analysis, and polymerase chain reaction analysis.
AI tools to try
ChatGPT / Claude for literature and writingAI research tools (e.g. Elicit, Consensus, Semantic Scholar)Copilot for data analysis code (Python, R)Related roles
A 3-phase AI learning plan
Phase 1
Faster literature and writing
- Literature search and summaries with AI, always checked against the papers.
- Drafts of methods, reports and grant text.
- Reference management and formatting.
Project
Use AI to screen 100 abstracts on your gene of interest and draft a 2-page grant background section, verifying every claim and citation against the source papers.Phase 2
AI for data analysis
- Analysis code in Python or R written with AI help.
- Visualisation and statistics explained step by step.
- Reproducibility: version code and prompts.
Project
Rebuild one past RNA-seq or variant analysis as an AI-assisted, version-controlled R/Python pipeline with logged prompts, and compare runtime and figures to your original results.Phase 3
AI as a research method
- Classification, extraction or modelling with AI on your data.
- Validate against human labels or ground truth.
- Ethics, data protection and disclosure of AI use.
Project
Fine-tune or prompt an AI model to extract phenotype-variant pairs from 200 de-identified records, score accuracy against your own labels, and write an AI-use disclosure statement.