How likely is AI to replace Data Scientists?

Published research puts Data Scientists at 64 out of 100 for AI displacement risk, in the transitioning band. The number is a weighted consensus of 7 research sources and describes the typical version of the role, not any individual.

Do researchers agree on the risk for Data Scientists?

Broadly, yes. Individual estimates for Data Scientists run from 52 to 69 out of 100 across the 7 sources behind this score, a fairly tight range. More recent and higher confidence studies carry more weight in the final number.

Which technology roles face similar AI exposure?

The closest published technology roles to Data Scientists by score are Data Warehousing Specialists (62/100), Business Intelligence Analysts (61/100), and Mathematical Science Occupations, All Other (61/100). Each has its own page with the research behind its number.

Occupation baseline · Research consensus

Will AI replace Data Scientists?

Transitioning

Baseline AI displacement risk for Data Scientists, aggregated from 7 research sources.

What this score means

Data Scientists is among the more exposed roles in Technology. A large share of the work, especially its routine and text heavy parts, is already within reach of current AI, though the harder judgment calls still need a person. At 64 out of 100 it scores 9 points above the Technology average of 55. Across the 7 sources behind this baseline, individual estimates run from 52 to 69, so the score is a weighted consensus rather than any single figure.

The number is a consensus estimate for the typical version of the role, built from published academic and industry research scored occupation by occupation. It is not a prediction about any individual. How scoring works

What this job actually involves

Exposure follows the work itself rather than the job title, so it is worth seeing what the role is made of. These are the tasks O*NET records for Data Scientists, most central first, showing 12 of 16.

01Analyze, manipulate, or process large sets of data using statistical software.
02Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
03Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
04Clean and manipulate raw data using statistical software.
05Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
06Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
07Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
08Design surveys, opinion polls, or other instruments to collect data.
09Identify business problems or management objectives that can be addressed through data analysis.
10Identify relationships and trends or any factors that could affect the results of research.
11Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.
12Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.

Task statements from O*NET by the National Center for O*NET Development, used under CC BY 4.0. The tasks are descriptive; the exposure score above is ours.

The research behind this score

This baseline aggregates 7 research sources that scored Data Scientists for AI and automation exposure. More recent, higher confidence studies carry more weight in the final number.

01Anthropic Economic Index 2026 - AI Task Exposure · 2026Anthropic
02Crashing Waves vs. Rising Tides: Preliminary Findings on AI Automation from Thousands of Worker Evaluations of Labor Market Tasks · 2026Mertens, Thompson et al., MIT FutureTech (2026)
03Global Automation Atlas: Task Substitution Exposure by Occupation · 2026Garg, Crosta, Baier (2026), arXiv:2605.17086
04The AI Jobs Transition Framework: Mapping AI's Near-Term Impact on Jobs · 2026OpenAI Economic Research (2026)
05Generative AI and Jobs: A Refined Global Index of Occupational Exposure · 2025International Labour Organization, Working Paper 140 (2025)
06Working with AI: Measuring the Applicability of Generative AI to Occupations · 2025Tomlinson, Jaffe et al., Microsoft Research (2025)
07GPTs are GPTs: Labor Market Impact Potential of LLMs · 2024Eloundou, Manning, Mishkin, Rock (Science, 2024)

Common questions

How likely is AI to replace Data Scientists?: Published research puts Data Scientists at 64 out of 100 for AI displacement risk, in the transitioning band. The number is a weighted consensus of 7 research sources and describes the typical version of the role, not any individual.
Do researchers agree on the risk for Data Scientists?: Broadly, yes. Individual estimates for Data Scientists run from 52 to 69 out of 100 across the 7 sources behind this score, a fairly tight range. More recent and higher confidence studies carry more weight in the final number.
Which technology roles face similar AI exposure?: The closest published technology roles to Data Scientists by score are Data Warehousing Specialists (62/100), Business Intelligence Analysts (61/100), and Mathematical Science Occupations, All Other (61/100). Each has its own page with the research behind its number.

Also covers

Analytics Consultant · Applied Scientist · Data Analyst · Data Analytic Scientist · Data Analytics Manager · Data Analytics Scientist · Data Analytics Specialist · Data Architect and related titles

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Informational guidance based on published research, not professional career or financial advice. Scores update as new research is ingested.