B

Below-Average Risk (35–42%)

Industry occupation-mix grade — shared by every General Industrial Machinery & Equipment employer tracked

BLS + SEC data General Industrial Machinery & Equipment Industry AI-risk grade B

Enerflex Ltd.

Workforce AI-exposure profile for Enerflex Ltd.: industry grade B (37.6/100), plus SEC headcount and BLS occupation mix.

EFXT General Industrial Machinery & Equipment SIC 3560
Industry AI Displacement Exposure
37.6/100 B

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

Workforce Size
N/A
Not reported in XBRL filings
Industry Classification
General Industrial Machinery & Equipment
SIC Code: 3560
NAICS Sector: 33
The verdict

Enerflex Ltd.'s workforce carries a grade B AI-risk profile (37.6% weighted exposure), 4.3 points below 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.

37.6%
AI exposure
B
Risk grade
33
NAICS sector the grade comes from

Where Enerflex Ltd. sits among tracked employers

Industry occupation-mix AI exposure across the 1,965 public employers tracked. The marker is General Industrial Machinery & Equipment's value, which every employer we track in that sector shares — it is not a measurement of Enerflex Ltd. specifically.

Where Enerflex Ltd.'s industry AI exposure sits

Industry occupation-mix AI exposure across tracked public employers

37.6% Lower than most lower than 60% 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 General Industrial Machinery & Equipment sit below the typical industry AI-exposure band. Most roles still need dexterity, interpersonal skill, or on-site presence that current AI systems struggle with.

A
B
C
D
F

Industry exposure standing

Signature: 37.6/100 (grade B) · industry AI-exposure score (corpus extremity among disclosed peers)

As of May 2026, Enerflex Ltd. sits near the middle on both disclosed headcount and three-year change. Industry grade B (37.6/100) is shared by every tracked employer in General Industrial Machinery & Equipment. As of May 2026, Enerflex Ltd. (EFXT) has no XBRL headcount on file. Industry grade B (37.6/100) from General Industrial Machinery & Equipment is the primary measurable signal here.

SIC 3560 · NAICS 33 · 6 estimated roles; largest share Molders, shapers, and casters, except metal and plastic · sources SEC EDGAR · O*NET 30.0 · BLS industry-occupation distributions.

Estimated Workforce Occupation Mix (Industry Average)

Enerflex Ltd. does not publish its own occupation breakdown, so this reflects the typical occupation mix for other employers in General Industrial Machinery & Equipment (BLS industry-occupation employment distributions), not company-specific data. AI exposure scores from O*NET Database 30.0.

Occupation Est. Workforce Share AI Exposure
Molders, shapers, and casters, except metal and plastic
SOC 51-9195
40%
34%
Civil engineering technologists and technicians
SOC 17-3022
18%
39%
Security and fire alarm systems installers
SOC 49-2098
15%
26%
Shipping, receiving, and inventory clerks
SOC 43-5071
10%
60%
Funeral home managers
SOC 11-9171
9%
38%
Gas compressor and gas pumping station operators
SOC 53-7071
8%
38%

Methodology and scoring detail live on our how we score AI exposure page; occupation hubs sit under Browse all occupations.

Frequently Asked Questions

What is the AI risk grade for Enerflex Ltd.'s industry?

Enerflex Ltd. (EFXT) maps to General Industrial Machinery & Equipment with a mid-pack industry AI grade B (37.6/100). That score is identical for every tracked employer in the sector. Companies in General Industrial Machinery & Equipment sit below the typical industry AI-exposure band. Most roles still need dexterity, interpersonal skill, or on-site presence that current AI systems struggle with.

How is the AI risk score calculated?

The score uses the company's primary industry (SIC 3560: General Industrial Machinery & Equipment), 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 Enerflex Ltd. face the most AI risk?

Largest estimated shares in the General Industrial Machinery & Equipment mix: Molders, shapers, and casters, except metal and plastic (34% AI exposure); Civil engineering technologists and technicians (39% AI exposure); Security and fire alarm systems installers (26% AI exposure). Treat these as industry-typical roles, not Enerflex Ltd.'s published org chart.

How many employees does Enerflex Ltd. have?

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

Has Enerflex Ltd. had layoffs?

WARN Act layoff notices for Enerflex Ltd. 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 Enerflex Ltd. in?

Enerflex Ltd. is classified under SIC 3560 (General Industrial Machinery & Equipment), mapping to NAICS sector 33. That classification selects the BLS occupation mix behind the AI exposure grade.

What to do with this

Use Enerflex Ltd.'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