पेरोल और टाइमकीपिंग क्लर्क
कार्यालय और प्रशासनिक सहायताAI एक्सपोजर
- डेटा स्रोत: BLSप्रकाशन: 2026-08
बहुत उच्च· सापेक्ष
कमचार सापेक्ष श्रेणियाँबहुत उच्चव्यवसाय-समूह स्तर का मान
मापक्रम, आधार और स्रोत
चार सापेक्ष बैंड (कम / मध्यम / उच्च / बहुत उच्च)
BLS रोज़गार पूर्वानुमान तालिका के 831 विस्तृत व्यवसायों के आधार पर। मान NEM (नेशनल एम्प्लॉयमेंट मैट्रिक्स) कोड के स्तर पर दिया जाता है, इसलिए एक ही NEM कोड वाले व्यवसायों को वही बैंड मिलता है
- डेटा स्रोत: Anthropicप्रकाशन: 2026-03
0.049
0.000यहाँ दिए गए मानों की सीमा0.745मापक्रम, आधार और स्रोत
- डेटा स्रोत: ILOप्रकाशन: 2025
0.61
0.09यहाँ दिए गए मानों की सीमा0.70व्यवसाय-समूह स्तर का मान
मापक्रम, आधार और स्रोत
जेनरेटिव AI एक्सपोजर सूचकांक, प्रकाशित रूप में 0–1
ISCO-08 यूनिट समूह — समान कोड वाले सभी व्यवसायों को यही मान मिलता है
यह इस साइट की गणना है, ILO द्वारा प्रकाशित आँकड़ा नहीं: इस साइट द्वारा ILO डेटासेट से जोड़े गए 1,012 व्यवसायों में से 3% इस मान के बराबर या उससे अधिक हैं।
यह स्रोत किस प्रकार का आँकड़ा प्रकाशित करता है
BLS की श्रेणी सापेक्ष रैंक है, निरपेक्ष स्तर नहीं, और यह प्रथम-हस्त माप भी नहीं है: यह कई प्रकाशित अध्ययनों में व्यवसाय की पर्सेंटाइल रैंकों को चार बैंडों में बांटती है। यह रोज़गार या वेतन का पूर्वानुमान नहीं है, न अपनाए जाने की संभावना, और यह स्वचालन और संवर्धन में अंतर नहीं करती।
Task-level exposure
केवल एक्सपोज़र वाले कार्य| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Compute wages and deductions, and enter data into computers.43-3051 | 0.0100100.0 | —0 |
Compile employee time, production, and payroll data from time sheets and other records.43-3051 | 0.00000.0 | —0 |
Process paperwork for new employees and enter employee information into the payroll system. | —0 | 0.00000.0 |
| Not observed on any surface — 18 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Process and issue employee paychecks and statements of earnings and deductions. | —0 | —0 |
Review time sheets, work charts, wage computation, and other information to detect and reconcile payroll discrepancies. | —0 | —0 |
Verify attendance, hours worked, and pay adjustments, and post information onto designated records. | —0 | —0 |
Record employee information, such as exemptions, transfers, and resignations, to maintain and update payroll records. | —0 | —0 |
Issue and record adjustments to pay related to previous errors or retroactive increases. | —0 | —0 |
Keep informed about changes in tax and deduction laws that apply to the payroll process. | —0 | —0 |
Provide information to employees and managers on payroll matters, tax issues, benefit plans, and collective agreement provisions. | —0 | —0 |
Complete time sheets showing employees' arrival and departure times. | —0 | —0 |
Distribute and collect timecards each pay period. | —0 | —0 |
Prepare and balance period-end reports, and reconcile issued payrolls to bank statements. | —0 | —0 |
Keep track of leave time, such as vacation, personal, and sick leave, for employees. | —0 | —0 |
Conduct verifications of employment. | —0 | —0 |
Complete, verify, and process forms and documentation for administration of benefits, such as pension plans, and unemployment and medical insurance. | —0 | —0 |
Compile statistical reports, statements, and summaries related to pay and benefits accounts, and submit them to appropriate departments. | —0 | —0 |
Coordinate special programs, such as United Way campaigns, that involve payroll deductions. | —0 | —0 |
Balance cash and payroll accounts. | —0 | —0 |
Train employees on organizations' timekeeping systems. | —0 | —0 |
Prepare and file payroll tax returns. | —0 | —0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Compute wages and deductions, and enter data into computers.O*NET Task ID 2516 | 1.0 |
Compile employee time, production, and payroll data from time sheets and other records.O*NET Task ID 2517 | 1.0 |
Review time sheets, work charts, wage computation, and other information to detect and reconcile payroll discrepancies.O*NET Task ID 2518 | 1.0 |
Verify attendance, hours worked, and pay adjustments, and post information onto designated records.O*NET Task ID 2519 | 1.0 |
Record employee information, such as exemptions, transfers, and resignations, to maintain and update payroll records.O*NET Task ID 2520 | 1.0 |
Issue and record adjustments to pay related to previous errors or retroactive increases.O*NET Task ID 2521 | 1.0 |
Complete time sheets showing employees' arrival and departure times.O*NET Task ID 2524 | 1.0 |
Post relevant work hours to client files to bill clients properly.O*NET Task ID 2525 | 1.0 |
Distribute and collect timecards each pay period.O*NET Task ID 2526 | 1.0 |
Complete, verify, and process forms and documentation for administration of benefits, such as pension plans, and unemployment and medical insurance.O*NET Task ID 2527 | 1.0 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page