Statisticians: daily tasks & AI impact
This page breaks Statisticians into the top 15 daily O*NET tasks and scores each for Generative AI automation probability. Those task scores roll up to an overall vulnerability index of 59/100 (Moderate automation risk). Struck-through rows are ≥80% automatable; highlighted safer rows are under 30% or primarily physical.
High-automation exposure
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Durable human work
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.
| Task | Importance | AI probability | Nature |
|---|---|---|---|
| Analyze and interpret statistical data to identify significant differences in relationships among sources of information. Core | 4.67 | — | — |
| Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy. Core | 4.67 | — | — |
| Report results of statistical analyses, including information in the form of graphs, charts, and tables. Core | 4.52 | — | — |
| Determine whether statistical methods are appropriate, based on user needs or research questions of interest. Core | 4.5 | — | — |
| Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data. Core | 4.48 | — | — |
| Develop and test experimental designs, sampling techniques, and analytical methods. Core | 4.38 | — | — |
| Identify relationships and trends in data, as well as any factors that could affect the results of research. Core | 4.33 | — | — |
| Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students. Core | 4.29 | — | — |
| Design research projects that apply valid scientific techniques, and use information obtained from baselines or historical data to structure uncompromised and efficient analyses. Core | 4.26 | — | — |
| Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering. Core | 4.25 | — | — |
| Evaluate sources of information to determine any limitations, in terms of reliability or usability. Core | 4.1 | — | — |
| Process large amounts of data for statistical modeling and graphic analysis, using computers. Core | 4.05 | — | — |
| Develop software applications or programming for statistical modeling and graphic analysis. Core | 3.94 | — | — |
| Report results of statistical analyses in peer-reviewed papers and technical manuals. Core | 3.85 | — | — |
| Plan data collection methods for specific projects, and determine the types and sizes of sample groups to be used. Core | 3.81 | — | — |
What remains human
No tasks currently fall under the safe threshold for this occupation.
FAQ
Which Statisticians tasks are most exposed to AI?
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Which Statisticians tasks are safest from Generative AI?
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
How should I read the Statisticians task table?
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.