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.
- Collect taxes from individuals or businesses according to prescribed laws and regulations.74
- Direct service of legal documents, such as subpoenas, warrants, notices of assessment, and garnishments.74
- Confer with taxpayers or their representatives to discuss the issues, laws, and regulations involved in returns, and to resolve problems with returns.73
- Maintain records for each case, including contacts, telephone numbers, and actions taken.73
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.
- Impose payment deadlines on delinquent taxpayers and monitor payments to ensure that deadlines are met.01
- Check tax forms to verify that names and taxpayer identification numbers are correct, that computations have been performed correctly, or that amounts match those on supporting documentation.02
- Determine appropriate methods of debt settlement, such as offers of compromise, wage garnishment, or seizure and sale of property.03
- Maintain records for each case, including contacts, telephone numbers, and actions taken.04
- Examine and analyze tax assets and liabilities to determine resolution of delinquent tax problems.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Tax Preparers
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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.
