Compare Occupations

	Dishwashers	Janitors and Cleaners, Except Maids and Housekeeping Cleaners	Cooks, Institution and Cafeteria	Laundry and Dry-Cleaning Workers	Food Servers, Nonrestaurant	Food Preparation Workers
SUMMARY	79% High Risk	64% High Risk	50% Moderate Risk	66% High Risk	62% High Risk	67% High Risk
JOB SCORE	2.2/10	3.2/10	3.1/10	3.2/10	2.9/10	2.2/10
POLLING	69% (High Risk, Based on 118 votes)	58% (Moderate Risk, Based on 289 votes)	66% (High Risk, Based on 28 votes)	66% (High Risk, Based on 39 votes)	72% (High Risk, Based on 61 votes)	70% (High Risk, Based on 66 votes)
GROWTH by year 2034	0.2%	2.0%	2.0%	5.4%	3.0%	-3.4%
WAGES	$33,670 or $16.19 per hour	$35,930 or $17.27 per hour	$36,450 or $17.52 per hour	$33,800 or $16.25 per hour	$34,460 or $16.57 per hour	$34,220 or $16.45 per hour
VOLUME as of 2024	471,670	2,199,900	448,260	195,360	271,780	888,770
SNOWFLAKE [?] The Snowflake is a visual summary of the five badges: Automation Risk (calculated), Risk (polled), Growth, Wages and Volume. It gives you an instant snapshot of an occupations profile. The colour of the Snowflake relates to its size. The better the occupation scores in relation to others, the larger and greener the Snowflake becomes.
DESCRIPTION	Clean dishes, kitchen, food preparation equipment, or utensils.	Keep buildings in clean and orderly condition. Perform heavy cleaning duties, such as cleaning floors, shampooing rugs, washing walls and glass, and removing rubbish. Duties may include tending furnace and boiler, performing routine maintenance activities, notifying management of need for repairs, and cleaning snow or debris from sidewalk.	Prepare and cook large quantities of food for institutions, such as schools, hospitals, or cafeterias.	Operate or tend washing or dry-cleaning machines to wash or dry-clean industrial or household articles, such as cloth garments, suede, leather, furs, blankets, draperies, linens, rugs, and carpets. Includes spotters and dyers of these articles.	Serve food to individuals outside of a restaurant environment, such as in hotel rooms, hospital rooms, residential care facilities, or cars.	Perform a variety of food preparation duties other than cooking, such as preparing cold foods and shellfish, slicing meat, and brewing coffee or tea.

Compare Occupations Side by Side

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.

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.

Job Score

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.

Polling Data

Thousands of visitors cast their votes on how “automatable” each job feels. These community insights are shown alongside the calculated probabilities.

Growth & Wages

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.

Volume of Workers

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.

The Snowflake Diagram

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.