Agentic enterprise control layer
A mock executive operating layer for agentic AI adoption: identity, ownership, permissions, value, cost, risk, human oversight, audit signals, and launch readiness in one view.
Classifies new requests, flags duplicate demand, drafts scoring rationale, and routes exceptions to PMO review.
Collects release gate evidence, checks missing owners, and prepares audit-ready readiness summaries.
Converts portfolio signals into weekly decision briefs with recommended tradeoffs and escalation paths.
Agent registry
This view shows how leaders could govern agent sprawl before it becomes operational, security, compliance, or cost exposure.
Runtime controls
Example controls translate AI governance into daily operating mechanisms: thresholds, audit events, review gates, monitoring, and incident escalation.
Four agents request write access to planning data. Recommendation: keep write actions behind workflow approval until owner confidence exceeds 90%.
Run-rate is trending 18% above forecast due to repeated executive brief generation. Recommendation: cache repeated summaries and cap ad hoc runs.
Read-only analysis agents are approved for scale. Agents that draft decisions, route work, or change status require explicit human confirmation.
Executive decision intelligence
The control tower does not just report risk. It frames decisions, names tradeoffs, and gives leaders a clean path to action.
Benefit: reduces manual PMO reporting load by 18-22 hours per week.
Decision needed before Legal and Security signoff for broader rollout.
Tradeoff: delay one roadmap analytics enhancement or add one engineering pod.