How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is less exposed to automation, and meaningful change looks likely over the next 5 to 10 years.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 24.8 to 48.8
Physical / roboticsrange 11.9 to 35.9
When the change is likely
Partial, 5 to 10 yearslocal demand stable
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Use your 5 to 10 year runway
Change here is gradual. Build resilient skills steadily and watch the signals rather than waiting for a shock.
2
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
3
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
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Which of my tasks are exposed
Coordinate or conduct internal investigations of problems such as employee theft and violations of corporate loss prevention policies.
50.0
Administer systems and programs to reduce loss, maintain inventory control, or increase safety.
50.0
Review loss prevention exception reports and cash discrepancies to ensure adherence to guidelines.
50.0
Train loss prevention staff, retail managers, or store employees on loss control and prevention measures.
50.0
Investigate or interview individuals suspected of shoplifting or internal theft.
100.0
Provide recommendations and solutions in crisis situations such as workplace violence, protests, and demonstrations.
100.0
Identify potential for loss and develop strategies to eliminate it.
50.0
Hire or supervise loss prevention staff.
100.0
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Investigate or interview individuals suspected of shoplifting or internal theft.
Task: Provide recommendations and solutions in crisis situations such as workplace violence, protests, and demonstrations.
How this score is calculated
Map Loss Prevention Managers to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 36.8, robotics 23.9.
The timeline comes from the higher axis (36.8), shifted for local demand (stable), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.