Last Update: 3/13/2026
Your role’s AI Resilience Score is
Median Score
Changing Fast
Evolving
Stable
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.
What does this resilience result mean?
These roles are undergoing rapid transformation. Entry-level tasks may be automated, and career paths may look different in the near future.
AI Resilience Report for
They help organize and check data to support researchers and analysts in making sense of numbers and statistics for reports or projects.
This role is changing fast
The career of a statistical assistant is changing fast because many of the routine tasks like data entry and simple analysis are being automated by tools like OCR and RPA. AI is stepping in to help with things like suggesting formulas and summarizing findings, which means the repetitive parts of the job are being handled by machines.
Read full analysisLearn more about how you can thrive in your career
Learn more about how you can thrive in your career
This role is changing fast
The career of a statistical assistant is changing fast because many of the routine tasks like data entry and simple analysis are being automated by tools like OCR and RPA. AI is stepping in to help with things like suggesting formulas and summarizing findings, which means the repetitive parts of the job are being handled by machines.
Read full analysisContributing Sources
We aggregate scores from multiple models and supplement with employment projections for a more accurate picture of this occupation’s resilience. Expand to view all sources.
AI Resilience
AI Resilience Model v1.0
AI Task Resilience
CareerVillage's proprietary model that estimates how resilient each occupation's tasks are to AI automation and augmentation
Microsoft's Working with AI
AI Applicability
Measures how applicable AI tools (like Bing Copilot) are to each occupation based on real usage patterns
Anthropic's Observed Exposure
AI Resilience
Based on observed patterns of how Claude is being used across occupational tasks in real conversations
Will Robots Take My Job
Automation Resilience
Estimates the probability of automation for each occupation based on research from Oxford University and other academic sources
Althoff & Reichardt
Economic Growth
Measured as "Wage bill" which is a long term projection for average wage × employment. It's the total labor income flowing to an occupation
Low Demand
We use BLS employment projections to complement the AI-focused assessments from other sources.
Learn about this scoreGrowth Rate (2024-34):
Growth Percentile:
Annual Openings:
Annual Openings Pct:
Analysis of Current AI Resilience
Statistical Assistants
Updated Quarterly • Last Update: 2/17/2026

What's changing and what's not
Statistical assistants do tasks like entering data, running simple analysis, compiling stats, organizing papers, and making charts [1] [2]. Many of these chores are already helped by software. For example, Optical Character Recognition (OCR) and robotic process automation (RPA) can auto-fill forms or move data between systems.
Spreadsheets and statistics programs (Excel, SPSS, R, etc.) handle calculations and graphs, so human workers mostly guide or interpret results [2]. Even AI tools are starting to help: some generative AI can suggest formulas or summarize findings, but experts still oversee its work. [3] [4]. In fact, studies find that AI is mainly automating very repetitive tasks right now – things like simple coding or data entry – while leaving higher-level decisions to people [3] [5].
In other words, machines handle the boring parts, but humans still check accuracy and make judgments. Researchers note that data jobs often need people to label or verify outputs (for example, checking that a chart or report looks right) [4] [3].

AI in the real world
AI tools for clerical and data work are widely available, so companies could use them quickly. However, adoption can be mixed. On one hand, automating data entry or chart-making can save time and money, especially when tasks are routine.
On the other hand, many businesses move slowly because they still need trust and oversight. A recent survey found that bosses want a human “in the loop” – they prefer workers who know how to work with AI rather than rely on it completely [3] [5]. Also, because statistical assistant roles often use fairly common software, the cost of switching to new AI tools might be higher than simply hiring people at today’s wages.
In some industries, companies even outsource data work to lower-cost labor overseas rather than invest in new AI systems [4]. Social and legal factors matter too: if data are private, firms must be careful with AI. All these reasons mean change can be gradual.
Still, experts are hopeful: as training and trust improve, AI will more often augment each task (help with it) rather than fully replace it, leaving humans free to do the creative and critical thinking that AI isn’t good at.

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Median Wage
$51,440
Jobs (2024)
6,500
Growth (2024-34)
-2.5%
Annual Openings
800
Education
Bachelor's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
AI-generated estimates of task resilience over the next 3 years
Send out surveys.
Interview people and keep track of their responses.
Select statistical tests for analyzing data.
Check survey responses for errors, such as the use of pens instead of pencils, and set aside response forms that cannot be used.
Participate in the publication of data or information.
File data and related information and maintain and update databases.
Check source data to verify completeness and accuracy.
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.

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