Will AI replace Facilities Managers?
Estimated risk score: 44 out of 100
Lower replacement risk
Estimate from published task research, not reviewed by a person · how we estimate
Within about 19 points for 4 in 5 of the jobs we checked (25 to 63).
Low confidence: only 11 of its tasks are rated.
For the occupation as a whole, from ratings of its 11 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 11-3013.00 · Management
Tasks rated in 2023 as ones AI could do or speed up
Tasks a GPT-4-class model could do, or do in half the time or less: 1 of its 11 rated tasks. In O*NET’s words.
- Prepare and review operational reports and schedules to ensure accuracy and efficiency.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 4 of its 11 rated tasks. In O*NET’s words.
- Conduct classes to teach procedures to staff.
- Dispose of, or oversee the disposal of, surplus or unclaimed property.
- Monitor the facility to ensure that it remains safe, secure, and well-maintained.
- Oversee the maintenance and repair of machinery, equipment, and electrical and mechanical systems.
What the job is
Plan, direct, or coordinate operations and functionalities of facilities and buildings. May include surrounding grounds or multiple facilities of an organization's campus.
Also called: Facilities Director, Facilities Operations Manager (Facilities Ops Manager), Space Officer, Stadium Manager, Building Manager, Ops Administrator, Facilities Specialist, Facilities Coordinator.
Closest jobs we score by hand
In the same field (Management). Different jobs, each scored by a person.
Source. This site includes information from the O*NET 30.1 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not approved, endorsed, or tested these modifications. (O*NET, CC BY 4.0.) Task ratings: Eloundou, Manning, Mishkin and Rock (2023), “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models”, data used under the MIT licence (licence texts). Our change: we averaged the ratings over this occupation’s tasks and calibrated them to our 0–100 scale. It is not a prediction about any one person and not career advice. Disagree? Write to hello@yourstopwashit.com. How we estimate