Evaluate the quality or accuracy of data
Work activity · O*NET
Evaluate the quality or accuracy of data is an intermediate work activity in the O*NET database — a concrete task that recurs across many occupations , grouped under Processing Information. 86 occupations report doing it as part of their work.
What it involves
The most common detailed activities O*NET records under this category, ranked by how many occupation tasks map to each.
- Verify accuracy of financial or transactional data
- Verify information or specifications
- Verify accuracy of records
- Verify accuracy of data
- Evaluate data quality
- Check data for recording errors
- Verify accuracy of financial information
- Verify mathematical calculations
How AI is applied to this activity
Microsoft's "Working with AI" study mapped real Bing Copilot conversations to O*NET work activities. The figures below are their measurements for this activity — they describe how AI is used today in one assistant's data, not a forecast that the activity will be automated.
| AI completes it successfully | 82.2% | When Copilot attempts this activity, how often it finishes the task |
| Scope AI handles | 28.0% | How much of the activity AI carries within a conversation |
| Positive user feedback | 59.1% | Share of interactions users rated positively |
| How often AI is applied here | 84th pct | Percentile across all measured activities by how often AI performs them |
Source: Microsoft "Working with AI" (working-with-ai). A high completion rate means AI can assist the activity in isolation — it does not mean an occupation that performs it is being automated, since every job blends many activities.
Detailed work activities
The more granular units of work O*NET groups under this activity, ordered by how many occupations perform them.
- Verify information or specifications. · 18 occupations · 18 tasks · 67% AI-exposed
- Verify accuracy of financial or transactional data. · 17 occupations · 30 tasks · 93% AI-exposed
- Verify accuracy of records. · 13 occupations · 16 tasks · 100% AI-exposed
- Check data for recording errors. · 9 occupations · 10 tasks · 100% AI-exposed
- Verify accuracy of data. · 9 occupations · 12 tasks · 100% AI-exposed
- Evaluate data quality. · 8 occupations · 11 tasks · 100% AI-exposed
- Verify accuracy of financial information. · 5 occupations · 6 tasks · 100% AI-exposed
- Verify mathematical calculations. · 5 occupations · 6 tasks · 100% AI-exposed
- Review accuracy of sales or other transactions. · 4 occupations · 5 tasks · 80% AI-exposed
- Verify customer credit information. · 4 occupations · 4 tasks · 100% AI-exposed
- Check quality of diagnostic images. · 3 occupations · 4 tasks · 100% AI-exposed
Occupations that perform this activity
Ranked by how many of the occupation's tasks map to this activity.
Showing 40 of 86 occupations.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- Microsoft “Working with AI” working-with-ai Microsoft Research
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Singulariki. "Evaluate the quality or accuracy of data." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; Microsoft “Working with AI” working-with-ai. Accessed June 7, 2026. https://singulariki.com/activities/evaluate-the-quality-or-accuracy-of-data
Singulariki. (2026). Evaluate the quality or accuracy of data. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/activities/evaluate-the-quality-or-accuracy-of-data
@misc{singulariki-evaluate-the-quality-or-accuracy-of-data,
title = {Evaluate the quality or accuracy of data},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; Microsoft “Working with AI” working-with-ai. Accessed June 7, 2026},
url = {https://singulariki.com/activities/evaluate-the-quality-or-accuracy-of-data}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.