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

Agile coach

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
Boards, metrics and the cadence design.
Estimate

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

16%40%+6.4
The real retro and the elephant in the room.
Estimate

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

18%14%+2.5
Train, unblock and the manager who will not let go.
Estimate

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

16%32%+5.1
Scale, dependencies and fake agile.
Estimate

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

16%28%+4.5
Conflict, power and not selling extra frameworks.
Estimate

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

18%18%+3.2
That they stop faking it, and not inflating velocity.
Estimate

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

16%14%+2.2
Total100%24%

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

Skills and activities

  • retros
  • agile cadence
  • unblock teams
  • flow metrics
  • fake agile
  • agile training
  • dependencies
  • velocity

Sources for this job· O*NET 13-1111.00· ESCO/ISCO 2421

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