🎯
Business Objectives
- ›Ensure right access for right person at right time
- ›Detect insider risk and stale accounts
- ›Improve onboarding speed
⚙️
Operational KPIs
- ›Active users / day
- ›MFA adoption %
- ›Failed login rate
📈
Management KPIs
- ›Onboarding time (request → access)
- ›Orphaned account count
🤝
Customer KPIs
- ›Customer portal logins / week
- ›Self-serve action rate
🗄️
Available Data
- ›User profile, role, created date, last login
- ›Action audit trail
- ›Permission matrix
- ›Login IP / device
✨
AI Use Cases
- ›Role recommendation from behavior
- ›Anomalous-access detection
- ›Onboarding copilot that auto-provisions
🔮
Predictive Analytics
- ›Account churn / inactivity risk
- ›Likely permission needed for new hire
🚨
Anomaly Detection
- ›Unusual login geo / hour
- ›Privilege escalation patterns
🎁
Recommendation Engines
- ›Suggested role downgrades for unused permissions
🤖
AI Copilot Features
- ›'Give Tomiko driver-supervisor access for 14 days'
💬
Natural-Language Reporting
- ›'Who logged in from a new device this week?'
📊
Executive Dashboard Metrics
- ›Active users, MFA %, dormant accounts
⚡
Workflow Automation
- ›Auto-deprovision after 60 days inactive
- ›Auto-rotate API keys
🛰️
Autonomous Agents
- ›Access Review Agent runs quarterly attestations
🖥️
Recommended Dashboards
- ›Security & Access
- ›Adoption
💡
Example Executive Insights
- ›27% of accounts are over-permissioned vs. observed usage
📦
Required Datasets
- ›users
- ›user_roles
- ›activity_log
- ›auth_events
📅
Historical Data Needed
6–12 months
🧠
ML Models / AI Approaches
- ›Behavioral clustering
- ›Isolation Forest for anomalies