Dashboard deep dive
This simulated Workforce AI Security dashboard shows 30 days of data from a 2,000-employee enterprise. Explore the metrics and answer: what's the story this data tells?
47200
Total Interactions
41%
Employee Adoption
1340
Sensitive Data Events
7
Shadow AI Apps
Daily AI interactions (30 days)
Traffic by application
Sensitive data by type
Managed vs Unmanaged
■ Managed (62%)
■ Unmanaged (38%)
Policy enforcement breakdown
487
PII Redacted
218
Code Uploads Blocked
635
Warnings (User Continued)
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Think Deeper
Try this:
The dashboard shows 31% after-hours AI usage. Is this a risk indicator or normal? How would you investigate?
It depends on context. Check: 1. Which departments? Engineering working late is normal; HR at 2am is suspicious. 2. What data types? After-hours + sensitive data = higher risk. 3. Trend — is it growing? A sudden spike may indicate a departing employee exfiltrating data. Context turns a metric into an insight.
Cybersecurity tie-in: A dashboard is only as good as the questions you ask it.
The same data can tell different stories to a CISO ("we have exposure"), a compliance officer
("we need audit trails"), and an IT manager ("we need to approve more tools").
Learn to read dashboards like a SOC analyst reads a SIEM.