IS WORK OVER?

Automation index

How much of a Data scientist’s job can AI already do?

Today an AI can already classify, reconcile, and prep a first close. The final call, and what goes to the tax office, still has a name on it.

This percentage does not predict how many people will lose their jobs.

Task comparison

Data scientist

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.

TaskShareAIPoints
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders.
Estimate

No public source provides a precise figure. This is our estimate.

14%55%+7.7
Manage timely flow of business intelligence information to users.
Estimate

No public source provides a precise figure. This is our estimate.

13%28%+3.6
Maintain or update business intelligence tools, databases, dashboards, systems, or methods.
Estimate

No public source provides a precise figure. This is our estimate.

11%48%+5.3
Provide technical support for existing reports, dashboards, or other tools.
Estimate

No public source provides a precise figure. This is our estimate.

9%55%+5
Synthesize current business intelligence or trend data to support recommendations for action.
Estimate

No public source provides a precise figure. This is our estimate.

6%28%+1.7
Create business intelligence tools or systems, including design of related databases, spreadsheets, or outputs.
Estimate

No public source provides a precise figure. This is our estimate.

6%55%+3.3
Collect business intelligence data from available industry reports, public information, field reports, or purchased sources.
Estimate

No public source provides a precise figure. This is our estimate.

6%55%+3.3
Identify or monitor current and potential customers, using business intelligence tools.
Estimate

No public source provides a precise figure. This is our estimate.

6%28%+1.7
Other less frequent tasks (weight estimated from frequency).
Estimate

No public source provides a precise figure. This is our estimate.

29%28%+8.1
Total100%40%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • analyse data
  • models
  • dashboards
  • python
  • information structure
  • data warehouse
  • database
  • web programming
  • ICT security legislation
  • business process modelling

Sources for this job· O*NET 15-2051.01· ESCO/ISCO 2521

Kitchen porter

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.

TaskShareAIPoints
Orders, mise en place and labelling.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Peel, cut, wash and restock.
Estimate

No public source provides a precise figure. This is our estimate.

24%10%+2.4
Service, passes and not getting in the way.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Hygiene, HACCP and waste.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Shifts, stoves and heat.
Estimate

No public source provides a precise figure. This is our estimate.

14%22%+3.1
Not cutting yourself or leaving a pot unwashed.
Estimate

No public source provides a precise figure. This is our estimate.

14%14%+2
Total100%17%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • cook
  • mise en place
  • dishes
  • bake
  • Orders, mise en place and labelling
  • Peel, cut, wash and restock
  • Service, passes and not getting in the way
  • Hygiene, HACCP and waste
  • Shifts, stoves and heat
  • ayudante de cocina

Sources for this job· O*NET 35-2021.00· ESCO/ISCO 9412

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