Geneticists

Evaluate genetic data by performing appropriate mathematical or statistical calculations and analyses.

AI: Fully automatable - AI and statistical software are already capable of performing mathematical and statistical analyses on genetic datasets end-to-end, including variant calling, association testing, and visualization, given appropriate data and parameters.

Create or use statistical models for the analysis of genetic data.

AI: Fully automatable - AI systems in 2025 can design, fit, and apply statistical models to genetic datasets and produce interpretable results with high reliability, given appropriate data and oversight.

Design and maintain genetics computer databases.

AI: Fully automatable - AI tools in 2025 can fully design, implement, and maintain genetics databases, including schema design, ETL, indexing, and routine maintenance with automation and human oversight.

Review, approve, or interpret genetic laboratory results.

AI: Partial - AI can interpret genetic test results and classify many variants using up-to-date databases and guidelines, yet clinical approval and final interpretation require expert oversight due to uncertainty, edge cases, and regulatory requirements.

Evaluate, diagnose, or treat genetic diseases.

AI: Partial - AI can support evaluation and suggest diagnostic possibilities and treatment options for genetic diseases, but cannot independently perform legally and ethically required clinical diagnosis or prescribe/treat without qualified clinician responsibility.

Maintain laboratory notebooks that record research methods, procedures, and results.

AI: Partial - AI can transcribe, structure, and auto-fill laboratory notebook entries and metadata but cannot reliably replace the human responsibility, on-the-spot observations, and regulatory sign-off required for official lab records.

Write grants and papers or attend fundraising events to seek research funds.

AI: Partial - AI can draft and edit grant proposals and papers and generate persuasive materials, but high-stakes fundraising and relationship-building at events still require human networking, judgment, and trust-building.

Attend clinical and research conferences and read scientific literature to keep abreast of technological advances and current genetic research findings.

AI: Partial - AI systems can monitor literature, summarize advances, and process conference content, but attending for live networking, asking domain-specific questions, and integrating tacit knowledge from talks remain human activities.

Supervise or direct the work of other geneticists, biologists, technicians, or biometricians working on genetics research projects.

AI: Partial - AI can support supervision by monitoring progress, suggesting workflows, and flagging issues, but cannot fully assume leadership, responsibility, personnel management, and complex ethical decisions involved in directing teams.

Search scientific literature to select and modify methods and procedures most appropriate for genetic research goals.

AI: Partial - AI can rapidly search, synthesize, and recommend methods from the literature and suggest protocol adaptations, but selecting and validating modifications for specific research goals still needs expert oversight.

Collaborate with biologists and other professionals to conduct appropriate genetic and biochemical analyses.

AI: Partial - AI can contribute analyses, design experiments, and facilitate multidisciplinary communication, yet active collaboration often requires hands-on lab work, interpersonal negotiation, and domain judgement that humans provide.

Prepare results of experimental findings for presentation at professional conferences or in scientific journals.

AI: Partial - AI can generate figures, draft manuscripts and slides, and format materials for conferences or journals, but ensuring correct interpretation, novelty claims, and adherence to scientific standards requires human review.

Instruct medical students, graduate students, or others in methods or procedures for diagnosis and management of genetic disorders.

AI: Partial - AI can produce teaching materials, simulate cases, and provide feedback, but in-person instruction, hands-on mentoring, and clinical judgment in training remain primarily human responsibilities.

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.

AI: Partial - As of 2025 AI can generate hypotheses, analyze omics data, and propose experimental plans for gene regulation and protein interactions, but it cannot physically perform wet‑lab experiments or fully replace expert experimental judgment and tacit lab skills.

Extract deoxyribonucleic acid (DNA) or perform diagnostic tests involving processes such as gel electrophoresis, Southern blot analysis, and polymerase chain reaction analysis.

AI: Partial - While many wet-lab steps (DNA extraction, PCR, electrophoresis) can be automated with robotic platforms and AI-driven protocols in some facilities, physical sample handling, troubleshooting, and regulatory oversight mean these tasks are not universally fully automatable.

Maintain laboratory safety programs and train personnel in laboratory safety techniques.

AI: Partial - AI can create training materials, simulate safety scenarios, and monitor compliance via sensors, but maintaining safety programs and hands‑on training responsibilities still require human leadership and in-person oversight.

Conduct family medical studies to evaluate the genetic basis for traits or diseases.

AI: Partial - AI can design study protocols, analyze pedigree and clinical genetic data, and assist interpretation, but it cannot fully carry out patient recruitment, consent, and in‑person clinical coordination alone.

Verify that cytogenetic, molecular genetic, and related equipment and instrumentation is maintained in working condition to ensure accuracy and quality of experimental results.

AI: Partial - AI can monitor instrument telemetry, predict maintenance needs, and flag calibration issues, but physical maintenance, repairs, and regulatory sign‑offs require human technicians and accountability.

Confer with information technology specialists to develop computer applications for genetic data analysis.

AI: Partial - AI can translate genetics requirements into technical specifications and generate application prototypes, yet effective multi‑stakeholder conferencing and final decisions typically need human facilitation and negotiation.

Analyze determinants responsible for specific inherited traits, and devise methods for altering traits or producing new traits.

AI: Partial - AI can identify candidate genetic determinants and suggest editing strategies or breeding targets, but devising, validating, and ethically implementing methods to alter or create traits requires experimental work and regulatory/human oversight.

Develop protocols to improve existing genetic techniques or to incorporate new diagnostic procedures.

AI: Partial - AI can propose optimized protocols and simulate procedural changes, but developing, validating, and approving new or improved laboratory diagnostic protocols still requires wet‑lab validation and expert oversight.

Design sampling plans or coordinate the field collection of samples such as tissue specimens.

AI: Partial - AI can optimally design sampling schemes and coordinate logistics digitally, but on‑the‑ground sample collection and coordination often need human teams and situational judgement.

Plan curatorial programs for species collections that include acquisition, distribution, maintenance, or regeneration.

AI: Partial - AI can design and draft curatorial programs using data, models, and regulations but cannot fully manage on-the-ground acquisitions, legal coordination, and hands-on regeneration tasks.

Participate in the development of endangered species breeding programs or species survival plans.

AI: Partial - AI can model genetics and propose breeding strategies for species survival plans but cannot fully run live breeding programs or manage all biological, ethical, and institutional responsibilities.