Automation index
How much of a Waiter’s job can AI already do?
Today an AI or a robot can barely cover part of a shift. Pace, the physical space, and dealing with people still are the job.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Waiter
28%
AI can already do 28% of this job.
#86 / 623
View rankingWaiter
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Collect payments from customers.EstimateNo public source provides a precise figure. This is our estimate. | 6% | 28% | +1.7 |
Check with customers to ensure that they are enjoying their meals, and take action to correct any problems.EstimateNo public source provides a precise figure. This is our estimate. | 6% | 28% | +1.7 |
Remove dishes and glasses from tables or counters, and take them to kitchen for cleaning.EstimateNo public source provides a precise figure. This is our estimate. | 5% | 28% | +1.4 |
Prepare checks that itemize and total meal costs and sales taxes.EstimateNo public source provides a precise figure. This is our estimate. | 5% | 28% | +1.4 |
Clean tables or counters after patrons have finished dining.EstimateNo public source provides a precise figure. This is our estimate. | 5% | 28% | +1.4 |
Take orders from patrons for food or beverages.EstimateNo public source provides a precise figure. This is our estimate. | 5% | 28% | +1.4 |
Write patrons' food orders on order slips, memorize orders, or enter orders into computers for transmittal to kitchen staff.EstimateNo public source provides a precise figure. This is our estimate. | 5% | 28% | +1.4 |
Inform customers of daily specials.EstimateNo public source provides a precise figure. This is our estimate. | 5% | 28% | +1.4 |
Other less frequent tasks (weight estimated from frequency).EstimateNo public source provides a precise figure. This is our estimate. | 58% | 28% | +16.2 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- wine characteristics
- sparkling wines
- select glassware for serving
- comply with food safety and hygiene
- order supplies
- organise wine cellar
- upsell products
- check wine quality
- serve wines
- assist customers
Sources for this job· O*NET 35-3031.00· ESCO/ISCO 5131
IS WORK OVER?
Data engineer
31%
#36 / 623
View rankingData engineer
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Design pipelines, models and orchestration.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 50% | +12 |
Write SQL, Spark and data tests.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 45% | +8.1 |
Incidents, quality and lineage in production.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to analysts and negotiate data contracts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Cloud cost, permissions and PII.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 15% | +2.1 |
Decide architecture and technical debt.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 20% | +2.4 |
| Total | 100% | 31% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design pipelines, models and orchestration
- Write SQL, Spark and data tests
- Cloud cost, permissions and PII
- Decide architecture and technical debt
- ingeniero de datos
- data engineer
- etl
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511