Somewhat Resilient
Last Update: 6/19/2026
AI Resilience Score for Biological Scientists:
39.4%
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.
Low
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.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
AI Resilience Report forBiological Scientists, All Other
$93,330 median salary•4,800 annual openings•SOC Code: 19-1029.00
Biological Scientists, All Other are somewhat less resilient to AI impacts than most occupations, according to our analysis of 6 sources.
Biological scientists are labeled "Somewhat Resilient" because AI is genuinely changing how the work gets done, even if it is not replacing scientists altogether. Robots and machine learning tools can now run hundreds of experiments automatically and spot patterns in data far faster than any human, which means some of the repetitive, hands-on lab tasks that used to fill a scientist's day are being handled by machines.
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Biological scientists are labeled "Somewhat Resilient" because AI is genuinely changing how the work gets done, even if it is not replacing scientists altogether. Robots and machine learning tools can now run hundreds of experiments automatically and spot patterns in data far faster than any human, which means some of the repetitive, hands-on lab tasks that used to fill a scientist's day are being handled by machines.
Read full analysisAnalysis of Current AI Resilience
Biological Scientists
Updated Quarterly
How is AI changing Biological Scientists jobs?
Right now, biology research is being augmented more than replaced — AI is becoming a powerful lab partner, not a substitute scientist. In a widely discussed February 2026 piece, Nature reported that AI-driven autonomous robots are coming to biology laboratories, but researchers insist that human skills remain essential. A great example comes from the Joint BioEnergy Institute at Berkeley Lab [1], where scientists built an automated pipeline that uses robotics to create and test hundreds of genetic designs in parallel, with machine learning algorithms analyzing results to suggest the next set of designs — a system that moves 10 to 100 times faster than conventional methods.
Plant biologists are next: the American Society of Plant Biologists' Plant Biology 2026 conference [2] is spotlighting "AI-driven seed design" and prime editing as core tools for climate-ready crops. In bioprocess labs, The Medicine Maker [3] describes the trend as "modular automation with human oversight" — meaning humans still set goals, interpret weird results, and judge what matters.
Sources
How fast is AI adoption growing for Biological Scientists?
Adoption is moving fast in well-funded labs but slowly elsewhere. On the speed-up side, robotic platforms and protein-prediction models like AlphaFold are commercially available, and AI life-sciences spending has ballooned — one industry tracker pegged the AI life-sciences market at $69 billion [4] in May 2026. On the slow-down side, Brookings cautions [5] that the evidence on how AI is affecting the labor market today is inconclusive, and claims about harmful impacts on particular groups of workers are premature.
Robot labs are expensive, biology experiments are messy and hard to standardize, and safety, ethics, and regulation slow rollout — especially in clinical or environmental work. The BLS 2024–34 projections [6] still expect strong demand for biological-science roles, with postsecondary biology teaching alone projected to grow 7.3%. The hopeful takeaway: AI handles the repetitive pipetting and pattern-spotting, while humans bring curiosity, judgment, and the creative leaps that turn data into discovery — exactly the skills worth building in school.
Sources
Will AI replace Biological Scientists?
Not entirely. We think AI will take over some tasks, but not the whole job.
Biology research is being augmented more than replaced right now. At Berkeley Lab, scientists built an automated pipeline using robotics and machine learning to create and test hundreds of genetic designs in parallel, moving 10 to 100 times faster than conventional methods [1]. AI life-sciences spending has grown enormously, and tools like protein-prediction models are already in commercial use [4]. That is real disruption to day-to-day lab work.
Still, what stays human is significant. Biological experiments are messy and hard to standardize. Humans set the research goals, interpret unexpected results, and make the creative leaps that turn raw data into meaningful discovery. In bioprocess labs, the prevailing model is modular automation with human oversight, not full replacement [3]. Brookings also cautions that claims about AI's harmful labor-market impact on specific workers remain premature [5].
Our 39.4% AI Resilience Score reflects this tension honestly. The human contribution pillar is low, meaning routine tasks are genuinely at risk. But demand and earning flexibility hold up reasonably well through 2034 [6]. The practical advice: lean into judgment, curiosity, and cross-disciplinary thinking, because those are the skills AI cannot replicate and employers will keep paying for.
Sources
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Latest AI news for Biological Scientists
These articles highlight how AI is transforming the field of biology, offering new tools and methods for biological scientists. For instance, NVIDIA's BioNeMo platform is helping leaders streamline drug discovery, while generative AI tools can predict protein structures, crucial for understanding biological functions. As AI continues to reshape research methodologies, aspiring biological scientists can leverage these advancements to enhance their work and contribute to groundbreaking discoveries, ensuring they remain resilient and adaptable in a rapidly evolving job market.
NVIDIA BioNeMo Platform Adopted by Life Sciences Leaders to Accelerate AI-Driven Drug Discovery
nvidianews.nvidia.com • 1/12/2026
NVIDIA today announced a major expansion of NVIDIA BioNeMo™, an open development platform that enables lab-in-the-loop workflows to develop...
Measuring AI’s capability to accelerate biological research in the wet lab
openai.com • 12/16/2025
OpenAI introduces a real-world evaluation framework to measure how AI can accelerate biological research in the wet lab.
AI and genomics pave the way to new data-driven scientific discoveries
sangerinstitute.blog • 10/29/2025
Artificial intelligence (AI) is reshaping how we analyse biological data – from predicting protein structures to uncovering insights from...
Why We’re Going All In on Biology and AI
chanzuckerberg.com • 6/24/2025
Priscilla Chan on how CZI is using AI to understand cell biology and build tools like TranscriptFormer and Cytoland to accelerate biomedical...
Generative AI tool marks a milestone in biology
news.stanford.edu • 2/19/2025
Scientists have developed a generative AI tool that can predict the form and function of proteins coded in the DNA of all domains of life.
More Career Info
Career: Biological Scientists, All Other
They study living things and how they work, conducting experiments and research to discover new information that can improve health, agriculture, or the environment.
Parent Careers
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
