Distribution across 10 profiles.
Middle half of Business Intelligence Consultants score between 40% and 45%.
0%
50%
100%
p10 · 37%
47% · p90
Task breakdown by work type
On-screen work78%
Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.
In-person + screen15%
Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.
Computer + action6%
Computer input, real-world output — needs someone to act on it, not just software.
Fully in-person0%
No computer required. Furthest from automation — the strongest human advantage.
Typical tasks
3 synthetic profiles for a Business Intelligence Consultant, ordered by automation exposure.
Tab between them to see how task mix drives the score difference.
TaskTimeTypeExposure
Meeting with business stakeholders to understand their analytical needs, translate requirements into technical specs
deep expertisesocial core
22%AD
16%
Creating dashboards and visualizations in tools like Tableau, Power BI, or Looker to present metrics and trends
20%DD
56%
Debugging data quality issues, investigating discrepancies, and validating data accuracy across sources
deep expertise
19%DD
34%
Presenting findings and insights to leadership, explaining what the data means and recommending actions
deep expertisesocial core
13%DA
2%
Documenting data definitions, data lineage, and creating technical specifications for reports and models
9%DD
46%
Designing data models and ETL pipelines; optimizing queries for performance
deep expertise
7%DD
39%
Writing SQL queries and extracting data from databases and data warehouses to answer business questions
6%DD
90%
TaskTimeTypeExposure
Creating dashboards and visualizations in tools like Tableau, Power BI, or Looker to present metrics and trends
26%DD
56%
Meeting with business stakeholders to understand their analytical needs, translate requirements into technical specs
deep expertisesocial core
23%AD
4%
Writing SQL queries and extracting data from databases and data warehouses to answer business questions
20%DD
53%
Designing data models and ETL pipelines; optimizing queries for performance
14%DD
62%
Debugging data quality issues, investigating discrepancies, and validating data accuracy across sources
deep expertise
7%DD
38%
Documenting data definitions, data lineage, and creating technical specifications for reports and models
7%DD
55%
Presenting findings and insights to leadership, explaining what the data means and recommending actions
deep expertisesocial core
0%DA
9%
TaskTimeTypeExposure
Writing SQL queries and extracting data from databases and data warehouses to answer business questions
deep expertise
24%DD
38%
Debugging data quality issues, investigating discrepancies, and validating data accuracy across sources
21%DD
69%
Creating dashboards and visualizations in tools like Tableau, Power BI, or Looker to present metrics and trends
deep expertisesocial element
15%DD
29%
Documenting data definitions, data lineage, and creating technical specifications for reports and models
15%DD
74%
Designing data models and ETL pipelines; optimizing queries for performance
13%DD
62%
Meeting with business stakeholders to understand their analytical needs, translate requirements into technical specs
deep expertisesocial core
9%AD
4%
Presenting findings and insights to leadership, explaining what the data means and recommending actions
deep expertisesocial core
0%DA
7%
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AI tools for this role
Tools relevant to the most automatable tasks in this profession.
