DOL · DOL-39 · record R1305

QCEW NAICS Autocoder

Department of Labor · BLS

Overview

Development stage: PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Used for survey processing for statistical purposes
Start date: 2025-06-01 (day precision)Source: 06/01/2025 00:00:00
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Other: Applied Mathematical SciencesSource: Other - Applied Mathematical Sciences
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The primary data source for the Quarterly Census of Employment and Wages (QCEW) is administrative data from state unemployment insurance programs. Some of these records are submitted without a valid North American Industry Classification System (NAICS) code.

Expected benefits

The tool is intended to reduce the burden on human reviewers of these uncoded records by recommending the most likely NAICS codes. It also reduces the burden on the program office by reducing printing and mailing costs of soliciting unclassified data.

System outputs

The model is a random forest classifier trained on millions of QCEW records. It outputs the NAICS codes with the highest predicted probability given a business name.

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): BLS Internal System
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: No
Demographic features: k) None of the above
Training and evaluation data: QCEW records (legal name, trade name, and NAICS fields)
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported