Automatable

A task performed by Bioinformatics Scientists

Analyze large molecular datasets, such as raw microarray data, genomic sequence data, or proteomics data, for clinical or basic research purposes.

Red LightAI can do it · workers don't want it

Technically, much of it, experts rate AI capability 3.5/5, but workers don't want it automated (desire 2.83/5). It's an Automation Red Light: proceed with care.

Worker desire to automate2.8/5

How much the people who do this task want AI to take it over (avg of 6 workers).

AI capability today3.5/5

How capable experts rate current AI at this task (avg of 2 experts).

How much human involvement should stay?

The Human Agency Scale (H1–H5) captures how much human direction workers think this task should keep.

H3Equal human–AI partnership

Why workers feel the way they do

  • Frees up time for higher-value work50%
  • Helps handle larger scale50%
  • It's repetitive17%
  • It's stressful17%
  • Reduces human error17%
  • It's difficult17%

How to automate this

Doable with technology, but keep a person clearly in charge.

Analyzing & processing data

Let the spreadsheet or a BI tool do the math and the charts.

  1. 1Build it once with formulas and pivot tables instead of recalculating by hand.
  2. 2Connect a free dashboard so reports refresh themselves (Looker Studio, Power BI).
  3. 3Use AI to summarise the findings, but keep the numbers in the spreadsheet.

Tools that can help

Excel / Google SheetsLooker Studio or Power BIAI assistant

Know a better way, or spot an error?

Share how you automate this in real life, or correct the data. Reviewed before publishing.

This is 1 of 7 tasks studied for Bioinformatics Scientists, where workers want 71% of tasks automated.

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