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Comparison · dataset August 2026

Actuary vs Data Scientist: which is more exposed to AI?

Effectively tied: 1 point separates Actuarys from Data Scientists.

Actuary scores 66% time-weighted AI exposure and Data Scientist scores 65% — close enough that the headline number tells you almost nothing. The difference lives underneath it: Actuarys lose the most ground on "process and validate claims data" (91%), while for Data Scientists it is "clean and transform datasets" (88%). The two sit in different families — Business & Finance and Computer & Math — so any move between them is a career change, not a lateral step.

1PP GAP

Seven dimensions, side by side.

METRICACTUARYDATA SCIENTISTDELTA
AI exposure66%65%1pp gap
Resilience score62/10064/1002pt gap
Substitutable work time52%54%Fully automatable today
Human-critical work time34%24%Models score poorly here
Median salary$118k$118kLevel
10-year growth22%35%Data Scientist
US workforce28k202kBLS OEWS
Task level

What actually creates the gap.

Both roles hand a similar slice of the week to substitutable work — 52% for Actuarys, 54% for Data Scientists — but it is different work. Actuary exposure concentrates in "process and validate claims data"; Data Scientist exposure concentrates in "clean and transform datasets". Two roles can share a score and face completely different disruption timelines.

Actuary
MOST EXPOSED TASKS
  • Process and validate claims data91% · 16% time
  • Build actuarial models and simulations86% · 24% time
  • Write actuarial reports and memos74% · 12% time
HUMAN-CRITICAL CORE
  • Communicate risk to boards and regulators18% · 8% time
  • Advise on pricing and reserve strategy22% · 12% time
  • Interpret and apply regulatory frameworks32% · 14% time
Data Scientist
MOST EXPOSED TASKS
  • Clean and transform datasets88% · 14% time
  • Write analysis code and notebooks84% · 16% time
  • Generate charts and exploratory summaries82% · 10% time
  • Build baseline predictive models78% · 14% time
HUMAN-CRITICAL CORE
  • Communicate uncertainty to stakeholders14% · 8% time
  • Frame business and research questions18% · 10% time
  • Decide deployment and governance trade-offs22% · 6% time
What transfers

Both roles lean on cognitive, procedural, judgement — that is the part of your experience that travels intact. The real divide is creative: Data Scientists score 54 there against 36 for Actuarys, an 18-point spread. That is the gap you would actually have to close.

DIMENSIONACTUARYDATA SCIENTIST
Creative3654
Switching between them
LowDIFFICULTY

Data Scientist appears in our dataset as a mapped adjacent career for Actuarys: the move lowers exposure by 1 points, landing at 65%. Switch difficulty reads low — capability profiles are 9 points apart on average.

Score your own exposure in 8 questions →

Common questions.

Is Actuary or Data Scientist more at risk from AI?

Actuary. It scores 66% time-weighted AI exposure against 65% for Data Scientist — a 1-point gap. 52% of actuary work time is already fully substitutable by current models, versus 54% for Data Scientists.

Which pays more, Actuary or Data Scientist?

They are level. Both roles carry a median of $118k. Actuary ranges $78k–$184k; Data Scientist ranges $78k–$178k.

Can a actuary switch to being a data scientist?

Data Scientist appears in our dataset as a mapped adjacent career for Actuarys: the move lowers exposure by 1 points, landing at 65%. Switch difficulty reads low — capability profiles are 9 points apart on average.

Which role is growing faster, Actuary or Data Scientist?

Data Scientist, at 35% projected ten-year growth versus 22% — a 13-point difference. Growth and AI exposure are separate signals: a role can grow in headcount while the content of the work is substantially rewritten.

Methodology
Scores are time-weighted across each role's canonical O*NET tasks, graded against current frontier-model capability. How we score.