Executive · Governance & ROI Board
One board view of AI-agent governance — posture, spend, and what's at risk.
The single surface to take to a board or leadership review: are we governing our AI agents, is it improving, and how much spend is exposed? Packages signals scattered across the operator views into one trended, exportable read.
Bottom line
Governance index 76/100 (target 80), up 18 over 6 weeks while spend rose 62% — control improving despite growth. 42% of spend ($290.50) is at risk, but top 3 agents carry 100% of it — govern support-copilot, Codex CLI, marketing-gpt and most exposure clears.
Reporting period
The headline
Posture up 18 pts while spend rose 62% — control is improving despite growth.
Governance index 58 → 76 (target 80); daily spend $88.20 → $142.60. Faster fleet, more accountability per dollar.
Governance index
76
of 100 · target ≥ 80 · ▲ 2 vs last period
80 = industry target for governed agent fleets — illustrative
Governed agents
63%
5 of 8 agents policy-bound
Spend at risk
$290.50
42% of $684.50 flows through risky / ungoverned agents
2
open high findings
clearing in ~3w
1
critical agents
posture < 50
88%
instrumentation coverage
1 shadow agent
$684.50
total AI spend
54% from cache
Governance index — 6-week trend
posture history (projected)Up 2 pts this period. At the recent pace, the fleet reaches the 80 target in ~2 weeks.
Spend — daily
$684.50 totalUp 62% across the window ($88.20 → $142.60/day).
Are the agents earning their keep?
effectiveness detail →Governance answers "is it safe"; this answers "is it working." Fleet success 89% across 1,212 tasks — about $0.64 per successful task — but only 63% of agents emit a measured outcome signal (projected where signal ≠ measured).
89%
fleet success rate
8%
needed a human
$0.64
spend / successful task
63%
measured coverage
What's driving the risk & spend
agents below the posture target, ranked by spendConcentrated, not diffuse: top 3 agents = 100% of the $290.50 at-risk spend (support-copilot, Codex CLI, marketing-gpt). Govern these and most of the exposure goes away.
Open high & medium findings
all findings →Backlog trend: closing ~4/wk vs opening ~2/wk — net shrinking by 2/wk. At this pace the 5 open findings clear in ~3 weeks (projected — qcontrol stores current state only).
Fields: postureIndexTrend · weeksToTarget · governanceTaggedSpend · costs.series · findings(severity) — from app/data/c16-fleet.ts. Posture history, spend slope comparison, and findings flow are projected (qcontrol stores current state only).