Somewhat Resilient
Last Update: 6/19/2026
AI Resilience Score for Geneticists:
40.1%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
AI Resilience Report forGeneticists
$93,330 median salary•4,800 annual openings•SOC Code: 19-1029.03
Geneticists are somewhat less resilient to AI impacts than most occupations, according to our analysis of 5 sources.
Geneticists earn a "Somewhat Resilient" label because AI is genuinely changing a big chunk of their day-to-day work, especially the number-heavy analysis and data interpretation that used to take weeks, but human judgment is still essential for the parts that matter most. Tools like AlphaGenome and robotic self-driving labs are speeding up gene discovery and experiment design at a rapid pace, meaning geneticists who do not adapt to working alongside these tools may find their workflows significantly disrupted.
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Geneticists earn a "Somewhat Resilient" label because AI is genuinely changing a big chunk of their day-to-day work, especially the number-heavy analysis and data interpretation that used to take weeks, but human judgment is still essential for the parts that matter most. Tools like AlphaGenome and robotic self-driving labs are speeding up gene discovery and experiment design at a rapid pace, meaning geneticists who do not adapt to working alongside these tools may find their workflows significantly disrupted.
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Geneticists
Updated Quarterly
How is AI changing Geneticists jobs?
Right now, AI is mostly working alongside geneticists, not replacing them—but the augmentation is moving fast. Models like Google DeepMind's AlphaGenome, which made headlines in early 2026 for predicting how DNA sequences affect gene activity, are aiming to do for DNA what AlphaFold did for proteins, dramatically speeding up tasks like interpreting variants and designing experiments. In Nature Genetics, researchers describe how AI co-scientists can act as virtual research collaborators in statistical genetics, accelerating genetic discovery and translation, helping with the math-heavy analysis that used to take weeks.
The American Society of Human Genetics is hosting ASHG 2026 sessions on AI-enhanced, multiomic tools [1] to solve rare and undiagnosed diseases, showing the field officially embracing these tools. Robotic "self-driving labs" are also arriving: the Department of Energy's OPAL project at Berkeley Lab [2] is using robotic systems, AI agents and models, and standardized data-sharing platforms to accelerate the biotechnology pipeline all the way from gene discovery to commercialized technology, and a debated 2026 paper covered by Nature asks whether AI-driven autonomous robots are coming to biology laboratories, but researchers insist that human skills remain essential. That last point matters: protocol design, judgment on lab results, and supervising teams still depend on human geneticists.
Sources
How fast is AI adoption growing for Geneticists?
Adoption is happening quickly because the tools are commercially available, the economic payoff is huge—Drug Target Review [3] now calls 2026 "the year AI stops being optional in drug discovery"—and labs are under pressure to do more with limited budgets. A Harvard Business Review analysis [4] of how AI is reshaping the labor market suggests highly technical, data-rich jobs are seeing the fastest workflow changes. But there are real brakes: clinical genetics is heavily regulated, patient DNA data is sensitive, and bad predictions can hurt people, so hospitals and journals demand careful validation.
The good news for students: tasks ranking lowest for automation—supervising teams, interpreting results, and hands-on lab work—are exactly the human-judgment skills employers will still need, even as AI handles the number-crunching.
Sources
Will AI replace Geneticists?
Not entirely. We think AI will take over some tasks, but not the whole job.
Geneticists are already working alongside powerful AI tools, and that collaboration is only deepening. Systems like AlphaGenome are accelerating how researchers interpret DNA variants and design experiments, and 2026 is being called the year AI stops being optional in drug discovery [3]. Robotic self-driving labs, like the OPAL project at Berkeley Lab, are automating parts of the biotechnology pipeline that used to require significant human hours [2]. Our AI Resilience Score of 40.1% reflects this reality: meaningful disruption is coming, and geneticists who ignore these tools will fall behind.
But the job is not going away. The tasks hardest to automate are exactly the ones that define good genetics work: supervising teams, interpreting ambiguous results, and making judgment calls in regulated clinical settings where a wrong prediction can harm a patient. A Harvard Business Review analysis notes that highly technical, data-rich roles are seeing the fastest workflow changes [4], but change is not the same as replacement. The American Society of Human Genetics is actively building these tools into professional practice [1], which signals a field evolving rather than disappearing. Students entering genetics today should lean into the human skills AI cannot replicate.
Sources
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Latest AI news for Geneticists
These articles highlight how AI is revolutionizing geneticists' roles, making it essential for future professionals to embrace these technologies. For instance, the integration of AI in Myriad Genetics' prostate cancer test enhances precision in patient care, demonstrating the increasing demand for geneticists skilled in AI applications. Additionally, the potential of AI in gene therapy research showcases opportunities for innovation in genetic engineering. By staying informed and adaptable, students can build resilient careers in this evolving field.
Myriad Genetics Launches Prolaris® + AI, the First Prostate Cancer Test to Combine Genomics and Digital Pathology Artificial Intelligence (AI)
finance.yahoo.com • 5/30/2026
New PATHOMIQ AI integration helps clinicians tailor active surveillance with greater confidenceSALT LAKE CITY, May 26, 2026 (GLOBE NEWSWIRE)...
Next-Generation Cardiology: AI, Genetics, and Personalised Medicine — HSE University
www.hse.ru • 3/4/2026
More than 400 specialists from Russia and other countries participated in the "Genetics and the Heart" Congress hosted by HSE University.
Current and Future Applications of Artificial Intelligence in Clinical Genetics
www.cureus.com • 1/1/2026
Artificial Intelligence (AI) is transforming medicine, and its influence on clinical genetics cannot be ignored. From variant analysis and...
AI in Biotechnology Research Report 2025: An $11.4 Billion Market by 2030, Dominated by NVIDIA, Tempus AI, Recursion Pharmaceuticals, Schrodinger, and Sophia Genetics
finance.yahoo.com • 10/20/2025
AI in biotechnology is rapidly transforming genetic engineering, personalized medicine, and drug discovery by enabling faster and precise...
Artificial Intelligence in Genetics
www.cureus.com • 1/10/2024
AI has great potential in genetic engineering and gene therapy research. AI is a powerful tool for creating new hypotheses and helping with experimental...
More Career Info
Career: Geneticists
They study genes and DNA to understand how traits are passed down, helping to solve health problems and improve lives.
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Employment & Wage Data
Median Wage
$93,330
Jobs (2024)
63,700
Growth (2024-34)
+1.2%
Annual Openings
4,800
Education
Bachelor's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Extract deoxyribonucleic acid (DNA) or perform diagnostic tests involving processes such as gel electrophoresis, Southern blot analysis, and polymerase chain reaction analysis.
2
Evaluate genetic data by performing appropriate mathematical or statistical calculations and analyses.
3
Supervise or direct the work of other geneticists, biologists, technicians, or biometricians working on genetics research projects.
4
Instruct medical students, graduate students, or others in methods or procedures for diagnosis and management of genetic disorders.
5
Maintain laboratory safety programs and train personnel in laboratory safety techniques.
6
Evaluate, diagnose, or treat genetic diseases.
7
Collaborate with biologists and other professionals to conduct appropriate genetic and biochemical analyses.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
