C

Moderate AI Risk (43–48%)

Industry occupation-mix grade — shared by every Retail-Family Clothing Stores employer tracked

BLS + SEC data Retail-Family Clothing Stores Industry AI-risk grade C

Urban Outfitters Inc

Workforce AI-exposure profile for Urban Outfitters Inc: industry grade C (45.5/100), plus SEC headcount and BLS occupation mix.

URBN Retail-Family Clothing Stores SIC 5651
Industry AI Displacement Exposure
45.5/100 C

Weighted average O*NET AI exposure score for this industry's occupation mix

Workforce Size
N/A
Not reported in XBRL filings
Industry Classification
Retail-Family Clothing Stores
SIC Code: 5651
NAICS Sector: 44-45
The verdict

Urban Outfitters Inc's workforce carries a grade C AI-risk profile (45.5% weighted exposure), 3.6 points above the 41.9% average across 1,965 tracked employers. That is broadly typical of the industries tracked here; it describes the industry, not this company's own staffing.

45.5%
AI exposure
C
Risk grade
44-45
NAICS sector the grade comes from

Where Urban Outfitters Inc sits among tracked employers

Industry occupation-mix AI exposure across the 1,965 public employers tracked. The marker is Retail-Family Clothing Stores's value, which every employer we track in that sector shares — it is not a measurement of Urban Outfitters Inc specifically.

Where Urban Outfitters Inc's industry AI exposure sits

Industry occupation-mix AI exposure across tracked public employers

45.5% Around the middle lower than 29% of 1,965 employers

Employers, banded by industry AI-exposure mix

Each bar is a band; taller bars hold more employers. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.

Source O*NET / PlainWorkforce employer industry mix · 2026-05-15

AI Displacement Risk Analysis

Companies in Retail-Family Clothing Stores sit in a mid industry AI-exposure band. Some roles will be augmented, while core work still needs judgment, creativity, or complex problem-solving.

A
B
C
D
F

Industry exposure standing

Signature: 45.5/100 (grade C) · industry AI-exposure score (corpus extremity among disclosed peers)

As of May 2026, Urban Outfitters Inc sits near the middle on both disclosed headcount and three-year change. Industry grade C (45.5/100) is shared by every tracked employer in Retail-Family Clothing Stores. As of May 2026, Urban Outfitters Inc (URBN) has no XBRL headcount on file. Industry grade C (45.5/100) from Retail-Family Clothing Stores is the primary measurable signal here.

SIC 5651 · NAICS 44-45 · 6 estimated roles; largest share First-line supervisors of retail sales workers · sources SEC EDGAR · O*NET 30.0 · BLS industry-occupation distributions.

Estimated Workforce Occupation Mix (Industry Average)

Urban Outfitters Inc does not publish its own occupation breakdown, so this reflects the typical occupation mix for other employers in Retail-Family Clothing Stores (BLS industry-occupation employment distributions), not company-specific data. AI exposure scores from O*NET Database 30.0.

Occupation Est. Workforce Share AI Exposure
First-line supervisors of retail sales workers
SOC 41-1011
45%
45%
Shipping, receiving, and inventory clerks
SOC 43-5071
25%
60%
Food preparation and serving related workers, all other
SOC 35-9099
12%
35%
Funeral home managers
SOC 11-9171
8%
38%
Security and fire alarm systems installers
SOC 49-2098
5%
26%
Gas compressor and gas pumping station operators
SOC 53-7071
5%
38%

For task-level context on high-exposure mixes, see how AI affects different job types.

Frequently Asked Questions

What is the AI risk grade for Urban Outfitters Inc's industry?

Urban Outfitters Inc (URBN) maps to Retail-Family Clothing Stores, whose occupation mix is in the upper third of industry AI exposure here (grade C, 45.5/100). Every tracked employer in that sector shares the same grade - it describes the industry mix, not Urban Outfitters Inc's own roster. Companies in Retail-Family Clothing Stores sit in a mid industry AI-exposure band. Some roles will be augmented, while core work still needs judgment, creativity, or complex problem-solving.

How is the AI risk score calculated?

The score uses the company's primary industry (SIC 5651: Retail-Family Clothing Stores), mapped to BLS occupational employment shares. Each occupation gets an O*NET task-level AI exposure weight; the industry mix is the weighted average. 0 = no exposure; 100 = maximum.

Which occupations at Urban Outfitters Inc face the most AI risk?

Largest estimated shares in the Retail-Family Clothing Stores mix: First-line supervisors of retail sales workers (45% AI exposure); Shipping, receiving, and inventory clerks (60% AI exposure); Food preparation and serving related workers, all other (35% AI exposure). Treat these as industry-typical roles, not Urban Outfitters Inc's published org chart.

How many employees does Urban Outfitters Inc have?

Urban Outfitters Inc does not disclose employee count in recent XBRL filings. Check the latest 10-K or annual report for a current figure.

Has Urban Outfitters Inc had layoffs?

WARN Act layoff notices for Urban Outfitters Inc are published by state labor agencies and the U.S. Department of Labor when a covered mass layoff hits the 100-worker threshold. Many quieter workforce changes never appear in WARN.

What industry is Urban Outfitters Inc in?

Urban Outfitters Inc is classified under SIC 5651 (Retail-Family Clothing Stores), mapping to NAICS sector 44-45. That classification selects the BLS occupation mix behind the AI exposure grade.

What to do with this

Use Urban Outfitters Inc's risk profile above to plan next steps, not just react to the grade.

AI risk scores are estimates based on industry-level occupation distributions and may not reflect individual employer hiring practices; this is not financial advice.

AI risk scores are estimates based on industry-level occupation distributions and may not reflect individual employer hiring practices. Data sources: SEC EDGAR (company SIC codes) · O*NET Database 30.0 (AI exposure scores) · BLS Employment Projections 2024–2034. This is not financial advice.

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce