Finance
Actuaries
Low ExposureMedian wage $130,000
Read full reading on Actuaries →
AI Exposure · 2026 Reading
Actuaries vs Risk Analysts AI Exposure
Two finance roles people weigh against each other. On the numbers, Actuaries earn more ($130,000 vs $81,100, +60%), and Actuaries carry low AI exposure against moderate for Risk Analysts. What actually separates them is the day-to-day work each one owns.
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The AI-exposure read
Actuaries vs Risk Analysts: which is more exposed to AI?
Risk Analysts carries the steeper AI-exposure profile: 56/100 versus Actuaries at 16/100. Actuaries centre on work like ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits, which sets their low exposure reading. Risk Analysts centre on work like gather financial documents related to investigations, which sets their moderate exposure reading.
The durable move for either is the same: shift toward the decisions, accountability, and specialist depth that current AI tooling cannot absorb. The fundamentals overlap. Both are finance roles drawing on the same core skill set. So the gap between them is structural, not a difference of skill set. On pay, Actuaries sit at $130,000 median in the United States; Risk Analysts at $81,100. In both cases the durable move is the same: shift toward the judgment, accountability, and system-design work that current AI tooling cannot absorb.
Pay gap
$48,900
Actuaries earn more (+60%)
Exposure gap
40 pts
Risk Analysts more exposed
Lower-risk pick
Actuaries
Lower automation exposure
Overlap and Divergence
Where Actuaries and Risk Analysts meet, and where they part
Shared traits show where lateral moves between the roles are most plausible and where the same durability strategies apply to both. Divergence points are the structural differences that change the migration paths, the durable skill sets, and the next-six-months moves.
What's the same
Shared structural traits
- Both are finance roles drawing on the same core skill set.
- Both are seeing AI tooling absorb the routine, repeatable parts of the workflow.
- Both keep their value in the judgment, accountability, and relationship work AI cannot own.
What's different
Key divergence points
- Actuaries centre on work like ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits, which sets their low exposure reading.
- Risk Analysts centre on work like gather financial documents related to investigations, which sets their moderate exposure reading.
- The durable move for either is the same: shift toward the decisions, accountability, and specialist depth that current AI tooling cannot absorb.
AI Exposure Spectrum
Where each role sits on the compression curve
The bar below maps the three risk zones AI Career Index uses. The marker for each role shows roughly where its routine-production layer falls under current AI tooling.
Actuaries
Risk Analysts
High exposure
Moderate
Low exposure
40 to 60% of routine tasks
20 to 40%
Under 20%
Inside the Work
What Actuaries and Risk Analysts actually do
The top task statements each role carries in the O*NET occupation database. The verbatim text comes from the US Department of Labor's structured occupational data, so the gap between these two lists is the structural gap between the two jobs as the labour market formally records them.
A typical week as
Actuaries
A typical week for actuaries mixes model-building, scenario analysis, and the conversations with stakeholders who act on the numbers: budget owners, investment committees, or audit partners. Tooling like Akur8, Earnix, ChatGPT now sits in the day-to-day workflow. The low-exposure reading reflects the role's reliance on judgment, licensure, accountability, or physical presence that current AI tooling cannot substitute.
A typical week as
Risk Analysts
A typical week for risk analysts mixes model-building, scenario analysis, and the conversations with stakeholders who act on the numbers: budget owners, investment committees, or audit partners. Tooling like Hebbia, Rogo, AlphaSense now sits in the day-to-day workflow. The medium-exposure reading reflects a split between substitutable production work and durable judgment-bearing work; where the role sits on that split decides whether it compresses or appreciates.
Finance
Actuaries
- Ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits.
- Collaborate with programmers, underwriters, accounts, claims experts, and senior management to help companies develop plans for new lines of business or improvements to existing business.
- Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates.
- Design, review, and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums.
- Determine, or help determine, company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public.
O*NET-SOC code · 15-2011.00
Banking
Risk Analysts
- Gather financial documents related to investigations.
- Interview witnesses or suspects and take statements.
- Prepare written reports of investigation findings.
- Document all investigative activities.
- Create and maintain logs, records, or databases of information about fraudulent activity.
O*NET-SOC code · 13-2099.04
Day-to-Day Work Split
How Actuaries and Risk Analysts actually spend the week
Roughly how each role splits its week across the three layers AI Career Index tracks. Routine production is the layer AI tooling compresses fastest. The bigger that slice, the more exposed the role.
Actuaries
20%
45%
35%
Risk Analysts
40%
35%
25%
Routine production · What AI absorbs first
Judgement and decisions · Mostly durable
Relational and accountability · AI cannot reach
Role Profiles
Actuaries and Risk Analysts side by side
The high-level positioning for each role: category, AI exposure band, and median wage. Use this as the orientation point before reading the structural divergence below.
Also Known As
Alternate titles and US footprint
The alternate titles each role goes by in job listings, plus the size of each role's US labour-market footprint. Useful when the title on a job description does not match either role exactly: the alternate-title list shows which canonical role the listing actually belongs to.
Actuaries
Job listings also call this
Pricing ActuaryReserving ActuaryPension ActuaryCasualty Actuary
US employment
26,670workers
Risk Analysts
Job listings also call this
Fraud Risk AnalystFraud AnalystFraud Data AnalystFraud Strategy AnalystFraud Detection AnalystFraud Prevention Analyst
US employment
132,130workers
Employment figures are from the US Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 release. BLS reports employment at the SOC-code level: roles sharing a SOC code share an employment count by definition.
The Verdict
Which one should you pick?
Most readers come here for an answer, not just a comparison. Here is the structural read on which role wins on durability, and which one wins on what each is best at.
For durability
Pick Actuaries
Sits further from the routine-production layer AI tooling compresses fastest. The structural exposure is lower, the wage path is more defensible.
For shared skills
Lateral moves are real
Both are finance roles drawing on the same core skill set.
If you stay in Risk Analysts
Migrate up the stack
Risk Analysts face more exposure but retain durable migration paths into senior, accountability-bearing seats. The next 6 months of intentional moves matters more than years of tenure.
At-a-Glance Comparison
Actuaries vs Risk Analysts on the structural drivers
The dimensions that determine how the two roles diverge under AI: exposure band, US median wage, top durable skill, and the most relevant structural attributes. Each row is sourced from the role's full reading.
At-a-glance comparison
–
Actuaries
Risk Analysts
AI exposure score
16 /100
56 /100
Risk band (2026)
Low Exposure
Moderate Exposure
Real-world AI adoption
5.4%
22%
Routine tasks AI-substitutable
under 20 percent
20 to 40 percent
Median annual wage (US)
$130,000
$81,100
Entry-level wage (10th pct)
$78,570
$48,460
Senior wage (75th pct)
$170,650
$110,410
Total US employment
26,670
132,130
Top durable skill
Complex deal structuring and negotiation
Board and committee-level risk governance
O*NET-SOC code
15-2011.00
13-2099.04
Reviewed by AI Career Index Research · Methodology v3 · 2026 ·Read the methodology →
AI tool overlap
The AI tools actually doing the work in each role
Where the same tool already appears in both workflows, the substitution path is shared. Where they diverge, the compression vectors do too.
Both roles use
No tool overlap. The AI tooling for each role is structurally distinct.
Only Actuaries
- Akur8AI-driven insurance pricing and rate-modelling.
- EarnixAI-powered insurance-pricing optimisation.
- ChatGPTReserve-memo drafting, regulatory-filing language, and methodology explanation.
- Python with CopilotAI-assisted reserving model and stochastic simulation code.
- Milliman AriusAI-augmented loss-reserving and predictive modelling.
- FIS ProphetActuarial modelling platform with AI-driven calculation acceleration.
Only Risk Analysts
- RogoInvestment-banking workflow assistant for analysts and associates.
- HebbiaDocument AI for diligence, credit memos, and source-cited research.
- AlphaSenseAI market intelligence search across filings and transcripts.
- nCinoCloud banking platform with AI for lending, credit, and onboarding.
- Zest AIMachine-learning credit underwriting and lending decisions.
- ComplyAdvantageAI-driven AML, sanctions, and financial-crime screening.
FAQ
Common questions
Go Deeper
Want the full structural reading?
Each individual role page goes deeper than the comparison view: automation risk, AI tools currently affecting the role, the structural skill map, the 6-month action plan, and the full occupation data block. Read both readings to make a fully informed call between Actuaries and Risk Analysts.
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