How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Analyze monthly department budgeting and accounting reports to maintain expenditure controls.74
- Direct the preparation of regular and special budget reports.74
- Match appropriations for specific programs with appropriations for broader programs, including items for emergency funds.74
- Testify before examining and fund-granting authorities, clarifying and promoting the proposed budgets.74
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Examine budget estimates for completeness, accuracy, and conformance with procedures and regulations.01
- Interpret budget directives and establish policies for carrying out directives.02
- Provide advice and technical assistance with cost analysis, fiscal allocation, and budget preparation.03
- Review operating budgets to analyze trends affecting budget needs.04
- Analyze monthly department budgeting and accounting reports to maintain expenditure controls.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Accountant
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Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
