Mostly Resilient
Last Update: 8/30/2026
AI Resilience Score for Biostatisticians:
51.8%
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
$105,650 median salary•1,900 annual openings•SOC Code: 15-2041.01
Biostatisticians are somewhat more resilient to AI impacts than most occupations, according to our analysis of 6 sources.
Biostatistics is holding up really well against AI because the most important parts of the job, like deciding whether a drug is truly safe and effective, still require human judgment that regulators and the industry are not willing to hand over to a machine. AI is stepping in to handle the tedious, time-consuming coding and report-writing tasks (cutting timelines from 8 to 14 weeks down to 5 to 8 weeks), which actually frees biostatisticians to focus on the higher-level thinking that matters most.
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Biostatistics is holding up really well against AI because the most important parts of the job, like deciding whether a drug is truly safe and effective, still require human judgment that regulators and the industry are not willing to hand over to a machine. AI is stepping in to handle the tedious, time-consuming coding and report-writing tasks (cutting timelines from 8 to 14 weeks down to 5 to 8 weeks), which actually frees biostatisticians to focus on the higher-level thinking that matters most.
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Biostatisticians
Updated Quarterly
How is AI changing Biostatisticians jobs?
If you're worried that AI is coming for biostatistics jobs, here's some reassuring news: right now, AI is mostly acting like a helper rather than a replacement. Biostatistics has traditionally been one of the most manual parts of clinical research, with statistical analysis still heavily reliant on manual programming, bespoke workflows, and labour-intensive quality control, with one recent study requiring more than 21,000 lines of code to generate submission-ready outputs. AI tools are now taking on that grunt work.
For example, McKinsey reports that generative AI can draft clinical study reports [1] from a protocol, statistical analysis plan, and tables in minutes, cutting timelines from eight to 14 weeks down to five to eight weeks while achieving 98 percent or more accuracy. IQVIA leaders also describe how AI now supports biostatistics and data analysis during trial closeout [2], along with simulating trials before they start. But experts stress human judgment still rules: Veristat's AI innovation lead says [3] AI should not be determining whether a drug is safe or effective, and it's not responsible to let AI decide whether the primary endpoint of a pivotal trial has succeeded.
How fast is AI adoption growing for Biostatisticians?
Adoption is real but cautious. A 2025 Tufts CSDD survey cited by Pharmaceutical Statistics-adjacent research [4] found 36.9% of organizations reported no current AI/ML use, 30.3% were beginning implementation or piloting, and only 10.7% had fully implemented AI/ML. Regulation is the biggest brake — the FDA and EMA both demand traceability, bias controls, and human oversight.
But the American Statistical Association argues statisticians will remain essential [5] as trusted interpreters of AI-generated results. In fact, the U.S. Bureau of Labor Statistics projects strong growth for data-heavy roles [6], with employment of data scientists projected to increase 33.5 percent between 2024 and 2034. The takeaway for young people: learn the stats fundamentals and the AI tools — Deloitte's 2026 outlook [7] sees AI improving cycle times, not eliminating the scientists who design and defend the studies.
Sources
Will AI replace Biostatisticians?
No. We don't think AI will replace Biostatisticians, though we do expect the job to change.
Biostatistics has always been deeply technical and detail-heavy, and AI is now handling a real share of the grunt work. Generative AI can draft clinical study reports in minutes, cutting timelines from eight to 14 weeks down to five to eight weeks while hitting 98 percent or more accuracy [1]. AI also supports trial simulations and data analysis during trial closeout [2]. That is genuinely significant automation, and it will reshape day-to-day work.
But the judgment calls stay human. Experts are clear that AI should not be deciding whether a drug is safe or effective or whether a pivotal trial's primary endpoint succeeded [3]. The FDA and EMA both require traceability, bias controls, and human oversight, which keeps biostatisticians in the loop by regulatory necessity. The American Statistical Association argues statisticians will remain essential as trusted interpreters of AI-generated results [5].
Our 51.8% AI Resilience Score reflects that balance: meaningful pressure from AI, but a role that holds up. The practical advice for anyone entering this field is straightforward. Learn the statistical fundamentals deeply, get comfortable with AI tools, and position yourself as the person who designs, defends, and explains the work that AI helps produce.
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Latest AI news for Biostatisticians
These articles highlight emerging opportunities for biostatisticians amid the rise of AI in healthcare. For instance, WashU's new master's program focuses on training specialists to tackle real-world medical challenges using biostatistics and AI, addressing a growing job market. Similarly, EDETEK's launch of BioStat.AI exemplifies how AI tools can streamline clinical data analysis, enhancing biostatisticians' roles. As AI continues to evolve, biostatisticians equipped with these skills will be resilient and vital in shaping future healthcare solutions.
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,...
New WashU Medicine program to train data specialists
source.washu.edu • 2/26/2026
The master's program in biomedical data science and artificial intelligence is one of few such programs in the U.S. It offers a flexible...
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...
ANTICIPATE prepares hospitals for pandemics using artificial intelligence
press.vub.ac.be • 1/20/2026
Interdisciplinary project brings together expertise in AI, epidemiology, biostatistics, health economics, and molecular diagnostics.
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...
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
$105,650
Jobs (2025)
31,300
Growth (2025-35)
+11.0%
Annual Openings
1,900
Education
Master's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2025-2035
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
Plan or direct research studies related to life sciences.
3
Write research proposals or grant applications for submission to external bodies.
4
Design research studies in collaboration with physicians, life scientists, or other professionals.
5
Determine project plans, timelines, or technical objectives for statistical aspects of biological research studies.
6
Provide biostatistical consultation to clients or colleagues.
7
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...
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.
