Automation Risk
Each occupation shows a probability of automation. A higher score means machines and algorithms are more likely to take over the role in the future.
| SUMMARY |
70%
High Risk
|
38%
Low Risk
|
53%
Moderate Risk
|
70%
High Risk
|
69%
High Risk
|
| JOB SCORE | 2.9/10 | 5.2/10 | 4.0/10 | 2.2/10 | 3.3/10 |
| POLLING |
There hasn't been enough votes on this occupation yet
|
54%
(Moderate Risk,
Based on 29 votes)
|
38%
(Low Risk,
Based on 94 votes)
|
There hasn't been enough votes on this occupation yet
|
There hasn't been enough votes on this occupation yet
|
|
GROWTH
by year 2034
|
2.0%
|
1.2%
|
-2.8%
|
-1.1%
|
3.0%
|
| WAGES |
$45,130
or $21.70 per hour
|
$71,190
or $34.22 per hour
|
$60,500
or $29.08 per hour
|
$44,980
or $21.62 per hour
|
$47,010
or $22.60 per hour
|
|
VOLUME
as of 2024
|
57,310
|
685,140
|
56,540
|
14,900
|
16,160
|
| SNOWFLAKE |
|
|
|
|
|
| DESCRIPTION | Set up, operate, or tend machines, such as glass-forming machines, plodder machines, and tuber machines, to shape and form products such as glassware, food, rubber, soap, brick, tile, clay, wax, tobacco, or cosmetics. | Directly supervise and coordinate the activities of production and operating workers, such as inspectors, precision workers, machine setters and operators, assemblers, fabricators, and plant and system operators. Excludes team or work leaders. | Lubricate machinery, change parts, or perform other routine machinery maintenance. | Set up, operate, or tend machines that extrude and form continuous filaments from synthetic materials, such as liquid polymer, rayon, and fiberglass. | Operate or tend heating equipment other than basic metal, plastic, or food processing equipment. Includes activities such as annealing glass, drying lumber, curing rubber, removing moisture from materials, or boiling soap. |
Curious how automation and AI could affect your career? Our comparison tool lets you view two or more jobs side by side, helping you quickly spot differences in risk level, pay, growth, and popularity. All of this is based on a mix of academic research, user polling, and official labour data.
Each occupation shows a probability of automation. A higher score means machines and algorithms are more likely to take over the role in the future.
A quick summary of how a job performs overall — factoring in wages, growth, volume, and automation risk. It’s a handy way to see the bigger picture at a glance.
Thousands of visitors cast their votes on how “automatable” each job feels. These community insights are shown alongside the calculated probabilities.
See how fast each occupation is projected to grow and what people earn on average. High wages don’t always mean high security — automation risk still matters.
Explore how many people currently work in each occupation and in which year the data was recorded. Popularity can affect how disruptive automation will be for the wider economy.
Each snowflake visualises the balance between automation risk, wages, growth, and job volume. Bigger and greener areas mean stronger performance in that dimension.
Use this comparison page to research careers, guide students, or simply explore the future of work. All data is regularly updated to keep the results relevant.