Somewhat Resilient
Last Update: 6/19/2026
AI Resilience Score for Biostatisticians:
47.2%
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.
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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%).
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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%).
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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 forBiostatisticians
$103,300 median salary•2,000 annual openings•SOC Code: 15-2041.01
Biostatisticians are somewhat less resilient to AI impacts than most occupations, according to our analysis of 5 sources.
Biostatisticians earn a "Somewhat Resilient" label because AI is already changing real parts of their day-to-day work, like drafting statistical analysis plans, writing documentation, and automating reporting tasks that used to take significant time. The good news is that the most important parts of the job, including designing studies carefully, catching errors in AI-generated results, and explaining findings to doctors and regulators, still require a sharp human mind.
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Biostatisticians earn a "Somewhat Resilient" label because AI is already changing real parts of their day-to-day work, like drafting statistical analysis plans, writing documentation, and automating reporting tasks that used to take significant time. The good news is that the most important parts of the job, including designing studies carefully, catching errors in AI-generated results, and explaining findings to doctors and regulators, still require a sharp human mind.
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Biostatisticians
Updated Quarterly
How is AI changing Biostatisticians jobs?
Biostatisticians—the math experts who design and analyze health studies—are already seeing parts of their job change with AI, but the change so far looks more like help than replacement. In a recent paper in Statistics in Medicine, researchers describe how large language models can assist with biostatistical work and argue that the biostatistician's role is shifting toward being the "director and critic of AI" who frames the right questions and checks that the conclusions hold up. A December 2025 medRxiv review of clinical trial statistical programming found the field is transitioning from manual, study-specific coding toward metadata-driven, automated pipelines that lean on AI/ML.
Concrete examples include a March 2026 Pfizer-led study in Clinical Trials [1] on using generative AI to draft statistical analysis plans, and an Amstat News article [2] explaining how GenAI can write data set summaries, variable descriptions, or workflow notes and automate reporting—exactly the kind of monitoring, documentation, and protocol-review tasks O*NET rates as highly automatable. Regulators are pushing forward too: the FDA just launched an AI-Enabled Optimization of Early-Phase Clinical Trials pilot [3] to test how AI can speed trial decisions.
Sources
How fast is AI adoption growing for Biostatisticians?
Adoption is moving quickly because tools are commercially available and the economic payoff is huge—trials are expensive, and any week saved is worth millions. BCG's 2026 workforce model [4] projects that 50% to 55% of US jobs will be reshaped by AI in the next two to three years, with augmentation arriving faster than full substitution. Researcher uptake is already mainstream: a Wiley survey of 2,400+ researchers [5] found 85% reporting that AI has improved their efficiency.
Still, adoption is slowed by something biostatisticians specialize in—rigor. Health data is sensitive, regulators demand validated methods, and an AI hallucination in a drug trial could harm patients, so the FDA's pilot explicitly seeks input [6] on quality safeguards. The good news: skills like research design, ethical judgment, and explaining results to doctors are exactly what AI can't replace.
If you're considering this field, lean into statistical theory and AI fluency—employers are already posting hybrid "Biostatistician/AI Data Scientist" [7] roles.
Sources
Will AI replace Biostatisticians?
Not entirely. We think AI will take over some tasks, but not the whole job.
Biostatisticians earn a 47.2% AI Resilience Score from us, which puts them in a meaningful but manageable zone of disruption. AI is already handling the repetitive side of the work: drafting statistical analysis plans, writing data set summaries, and automating reporting pipelines [2]. Trials are expensive, and the pressure to save time and money means adoption is moving fast [4].
What stays human is the part that actually matters most. Biostatisticians decide which questions are worth asking, catch flawed assumptions, and explain results to doctors and regulators in ways that hold up to scrutiny. Health data is sensitive, and an AI error in a drug trial could hurt real people, so the FDA is actively seeking quality safeguards as it pilots AI in early-phase trials (statnews.com, federalregister.gov). That regulatory pressure keeps a human expert in the loop by design.
The job market picture is moderate, not booming, so this is not a field where you coast. The good news is that employers are already posting hybrid roles that blend biostatistics with AI skills [7]. If you build statistical fluency alongside AI literacy, you position yourself as the person who directs and checks the tools, which is exactly where the work is heading.
Sources
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Latest AI news for Biostatisticians
These articles highlight the evolving role of biostatisticians in integrating AI into healthcare. EDETEK’s BioStat.AI platform showcases how technology can streamline clinical data analysis, enhancing efficiency in biostatistics. Additionally, programs like the one at WashU Medicine aim to equip students with the AI skills needed to tackle real-world health challenges. As AI becomes integral to data-driven decision-making in health, biostatisticians who embrace these advancements will find themselves at the forefront of innovation, ensuring their relevance and resilience in the field.
Using advanced statistics and AI to improve health
hsph.harvard.edu • 3/31/2026
Matlin Gilman, PhD '26, studies the real-world health effects of policy decisions and builds artificial intelligence tools to advance health...
New WashU Medicine program to train data specialists to solve real-world problems
medicine.washu.edu • 2/26/2026
WashU Medicine's new BDS-AI master's program offered through the I2DB is designed to meet the growing demand for expertise in biostatistics,...
UF College of Medicine launches AI in biomedical and health sciences master’s program
news.ufl.edu • 2/4/2026
With workforce preparedness top of mind, the University of Florida College of Medicine is debuting the Artificial Intelligence in Biomedical...
EDETEK Launches BioStat.AI: The Industry's First Unified AI Platform for Clinical Data, Biostatistics, and Programming
www.prnewswire.com • 9/2/2025
PRNewswire/ -- EDETEK Inc., a global leader in digital clinical platforms and services, proudly announces the launch of BioStat.AI...
AI and Statistics: Perfect Together
sloanreview.mit.edu • 4/16/2024
People are often unsure why artificial intelligence and machine learning algorithms work. More importantly, people can't always anticipate...
More Career Info
Career: Biostatisticians
They use math and data to study health trends, helping doctors and scientists understand diseases and improve public health.
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Employment & Wage Data
Median Wage
$103,300
Jobs (2024)
32,200
Growth (2024-34)
+8.5%
Annual Openings
2,000
Education
Master'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
Teach graduate or continuing education courses or seminars in biostatistics.
2
Read current literature, attend meetings or conferences, and talk with colleagues to keep abreast of methodological or conceptual developments in fields such as biostatistics, pharmacology, life scien...
3
Design or maintain databases of biological data.
4
Prepare tables and graphs to present clinical data or results.
5
Write research proposals or grant applications for submission to external bodies.
6
Apply research or simulation results to extend biological theory or recommend new research projects.
7
Assign work to biostatistical assistants or programmers.
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.
