Occupation · 2026 assessment

AI Evaluation Engineer

The AI Evaluation Engineer role combines repeatable operations with decisions that require professional context. The index measures task exposure to AI, software automation and robotics—not the probability that the occupation disappears.

Low risk level Search jobs ↗

How risk may change

A forecast estimate, not a guaranteed scenario.

22%2026

28%2028

35%2030

45%2035

Which tasks are exposed

Risk applies to individual tasks—not to a person or an entire occupation.

Task	Risk
Generating routine code and configuration	47%
Preparing tests and technical documentation	43%
Classifying errors and analyzing logs	37%
Data migrations and routine integrations	37%
Architecture and technical trade-offs	16%
Security and production accountability	5%

What the score means

The score reflects process repeatability, data digitization, automated verification, the physical environment and the economic incentive to deploy technology.

The index reflects potential technology exposure of occupational tasks and is not the probability that a particular person will lose their job.

AI exposure

The share of cognitive, textual, visual or analytical work that current AI systems can technically assist with or perform.

35%

Robotics

The extent to which robots, autonomous machinery and computer vision can perform physical operations in a prepared environment.

Routine work

The share of operations that repeat, follow stable rules and produce a predictable result.

31%

Digitalization

How much of the input, workflow and output already exists in digital form.

40%

Business incentive

The economic incentive to automate based on task volume, labor cost, frequency and implementation cost.

27%

Human moat

Protection created by accountability, trust, empathy, licensing, negotiation and unpredictable real-world environments.

86%

Task map

AI replaces ↔ AI augments

Each task is positioned by AI capability and the degree of human involvement still required.

Human advantage

Work with AI

Low technology impact

Automate

How much AI can perform the task → How much a human is needed →

1Generating routine code and configurationAI 47% · human 73%
2Preparing tests and technical documentationAI 43% · human 83%
3Classifying errors and analyzing logsAI 37% · human 74%
4Data migrations and routine integrationsAI 37% · human 75%
5Architecture and technical trade-offsAI 16% · human 79%
6Security and production accountabilityAI 5% · human 93%

Why technology can change this work

tools automate data preparation, experiments and parts of modelling
models automatically compare scenarios, prices, returns and risks
code, configuration and documentation are already digital
routine code, tests and technical text can be generated automatically
many outputs can be checked with tests and static analysis

What protects the occupation

choosing the right objective, data and model-quality criteria
validation of assumptions and accountability for recommendations
a large share of value comes from human judgement, trust or personal accountability
architecture decisions and production accountability
understanding business constraints and legacy systems
security and complex system integration

United States · before tax

Average pay and outlook

Estimated nominal monthly pay. The scenario reflects sector, demand and task resilience; it is not a guarantee of income.

2026$11 950per month

2035$17 300scenario estimate

Find jobs ↗The partner link may contain referral parameters. Data benchmark: U.S. Bureau of Labor Statistics ↗

Practical next step

Where to move next

Do not restart from zero: carry your experience forward and add scarce skills.

Job search and transitions

Find work with a lower risk index

Compare adjacent paths and open a current search for the selected occupation.

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