Will AI replace Biostatisticians?

AI can do 93% of the work Biostatisticians do at least twice as fast. People already use it for 4 of their 25 tasks, while 19 more are ready but barely used so far. 2 still need a person.

AI is already doing this4 · 18% of time

People already use AI for these tasks in real work, based on Anthropic's analysis of how Claude is used.

  • Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.Mostly automated8% of time
  • 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 sciences, and social sciences.Mostly automated5% of time
  • Prepare articles for publication or presentation at professional conferences.Mostly assisted4% of time
  • Collect data through surveys or experimentation.Mostly automated1% of time

AI could do this next19 · 75% of time

AI can speed these up by at least half, but real use has not caught up yet. These are next in line.

  • Analyze clinical or survey data, using statistical approaches such as longitudinal analysis, mixed-effect modeling, logistic regression analyses, and model-building techniques.14% of time
  • Write program code to analyze data with statistical analysis software.12% of time
  • Prepare tables and graphs to present clinical data or results.6% of time
  • Draw conclusions or make predictions, based on data summaries or statistical analyses.5% of time
  • Design research studies in collaboration with physicians, life scientists, or other professionals.5% of time
  • Review clinical or other medical research protocols and recommend appropriate statistical analyses.5% of time
  • Prepare statistical data for inclusion in reports to data monitoring committees, federal regulatory agencies, managers, or clients.4% of time
  • Calculate sample size requirements for clinical studies.4% of time
  • Develop or implement data analysis algorithms.4% of time
  • Write research proposals or grant applications for submission to external bodies.2% of time
  • Determine project plans, timelines, or technical objectives for statistical aspects of biological research studies.2% of time
  • Plan or direct research studies related to life sciences.2% of time
  • Monitor clinical trials or experiments to ensure adherence to established procedures or to verify the quality of data collected.2% of time
  • Assign work to biostatistical assistants or programmers.1% of time
  • Develop or use mathematical models to track changes in biological phenomena, such as the spread of infectious diseases.1% of time
  • Design surveys to assess health issues.1% of time
  • Design or maintain databases of biological data.1% of time
  • Analyze archival data, such as birth, death, and disease records.1% of time
  • Apply research or simulation results to extend biological theory or recommend new research projects.1% of time

Still needs a person2 · 7% of time

No real AI use, no proven AI speedup and no robot that can do it yet. This is the part of the job to build on.

  • Provide biostatistical consultation to clients or colleagues.6% of time
  • Teach graduate or continuing education courses or seminars in biostatistics.1% of time

Your week is not the average

Describe what you actually do and get a personal report: your own tasks, what AI can already do, what stays yours and a 90 day plan.

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What this means

AI can already do almost all of this work at least twice as fast. Real use is still behind at 15 out of 100, so the change here is only getting started. Expect the role to shift toward deciding what to do, checking AI's work and owning the result.

What to do next

  • Do the 4 tasks AI is already handling with AI yourself. Your peers already are, and it is quickly becoming the baseline.
  • Get ahead on the 19 tasks AI could do next. These move as tools improve, so learning them early pays off.
  • Build on the 2 tasks that stay human. This is where your judgment, skill and relationships matter most.
Statisticians99%Data Scientists95%Business Intelligence Analysts95%Operations Research Analysts98%Actuaries99%Bioinformatics Technicians99%

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