Will AI replace geneticists?

Some tasks are already being done by AI or machines; the rest still needs a person. About 3h 31m of a typical shift is made up of tasks that AI or robots have done on their own in real use somewhere. That doesn't mean those hours are automated in a typical workplace. The breakdown: 5m done by people with AI help, 3h 31m that AI mostly does alone. The other 4h 24m (55%) stays with people. Separately, BLS expects about 4.7% more of these jobs by 2035 (all jobs: +3.5%).

AI shows up regularly in 7 of 24 tasks, about 3h 36m of a typical shift. The biggest ones:

• 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. (58m a shift, AI mostly does it alone)
• Prepare results of experimental findings for presentation at professional conferences or in scientific journals. (42m a shift, AI mostly does it alone)
• Evaluate genetic data by performing appropriate mathematical or statistical calculations and analyses. (37m a shift, AI mostly does it alone)
• Review, approve, or interpret genetic laboratory results. (32m a shift, AI mostly does it alone)
• Search scientific literature to select and modify methods and procedures most appropriate for genetic research goals. (21m a shift, AI mostly does it alone)

Not in workplaces like this one, based on a 2026 review of robot deployments. 2 more tasks have only been done in factory setups built around the machine, so they stay with people here. For 1 physical task, no robot has shown it can do the work yet.

4h 24m of a typical shift, or 55%, goes to tasks with no AI or robot evidence yet. No AI usage or robot deployment has shown up for these so far. The biggest:

• Supervise or direct the work of other geneticists, biologists, technicians, or biometricians working on genetics research projects. (42m a shift)
• Write grants and papers or attend fundraising events to seek research funds. (37m a shift)
• Extract deoxyribonucleic acid (DNA) or perform diagnostic tests involving processes such as gel electrophoresis, Southern blot analysis, and polymerase chain reaction analysis. (32m a shift)
• Collaborate with biologists and other professionals to conduct appropriate genetic and biochemical analyses. (26m a shift)
• Maintain laboratory notebooks that record research methods, procedures, and results. (21m a shift)

Much of it comes down to where and how the work happens. In-person, hands-on and high-stakes work is where AI and robots have made the least headway so far. In the official O*NET survey of people in this job:

• 60% talk face to face with others every day

For the 1 task in this job where AI shows up and timing data exists, a typical request takes about 12h 43m for a person alone and about 1h 3m with AI. These are Claude's own estimates from real conversations in April and May 2026 (Anthropic Economic Index). They describe single requests, not whole workdays, and time saved on a task doesn't mean jobs are cut. The biggest gaps:

• Prepare results of experimental findings for presentation at professional conferences or in scientific journals (about 12h 43m alone, 1h 3m with AI)

On Indeed, job postings in the Scientific Research & Development sector are at 84% of their February 2020 level (all U.S. postings: 104%), up 19.9% from a year earlier, as of Oct 9, 2026. BLS separately expects about 4,300 openings a year in this job through 2035. Across all U.S. postings, 7.3% now mention AI skills. Sector postings cover more than this one job and move for many reasons besides AI.

The median pay is about $98,920 a year ($47.56 an hour), 94% above the median for all U.S. jobs ($50,980). Most people in this job earn between $60,430 and $168,010 a year; that range covers the middle 80%. Pay figures are from BLS, May 2025, and vary a lot by state and employer. Pick a state to compare:

BLS projects growth of 4.7% from 2025 to 2035, compared with 3.5% growth for all jobs. That's about 62,000 jobs in 2035. It expects about 4,300 openings a year, mostly from people retiring or changing careers. These projections don't single out AI as a cause.

About 56,000 people in the U.S., roughly 0.04% of all workers (BLS, May 2025). That makes it the 369th largest of the 796 jobs on this site. BLS expects about 62,000 in 2035.

The most common requirement is post-doctoral training: about 36% of people in the job said so in the official O*NET survey. O*NET rates the job at level 5 of 5 for preparation, which usually means: graduate degree. Requirements vary by state and employer, especially for licensed work.

These come from the job's official skill ratings and from the tasks that AI and robots touch least today. Building them keeps you strong in the parts of the work that still need a person:

• Skills that matter more here than in most jobs: Science, Mathematics, Learning Strategies, Active Learning
• Get strong at the parts of the job that stay with people (listed above), which take 4h 24m of a typical shift
• Tools employers list: R, Python, C++, Git, GitHub
• Learn to use AI well on the tasks where it already shows up in this job (listed above)

These use similar skills, with less of a typical shift touched by AI or robots. Matches come from 109 official ratings of skills, knowledge and work activities, and each needs the same or less preparation unless the official list relates the jobs directly:

• Molecular and Cellular Biologists (21m touched, $99k median pay)
• Medical Scientists (17m touched, $103k median pay)
• Biochemists and Biophysicists (43m touched, $127k median pay)
• Epidemiologists (19m touched, $87k median pay)
• Microbiologists (1h 10m touched, $88k median pay)

Each task carries its own evidence label. For this job: 7 observed in real AI use, 17 with no AI or robot evidence found. The minutes per task are estimates, not measured hours, and "no evidence" doesn't prove a task is safe.