Designing Governance for an AI Agent Workforce
ICD designed workflows and UI/UX for an AI governance product that could be pitched to enterprise and government clients. The product was imagined as a control layer for organisations deploying multiple AI agents across departments, functions and geographies. It helps teams register agents, monitor performance, evaluate accuracy, track cost and time saved, review policy breaches and decide when an agent should be updated, paused, archived or removed. The design challenge was to make AI governance feel operational and usable, not abstract or compliance-heavy.
Making agent performance visible
ICD’s thinking focused on giving leaders one place to understand their agent workforce. The screens show live agents, cost per month, hours saved, average ratings, department-wise distribution, leaderboards and agent-level performance. This helps managers see which agents are creating value, which teams are using them well and where performance needs closer review.
Designing for trust at scale
ICD treated AI governance as a new enterprise operating system, where every agent needs ownership, visibility, accountability and measurable impact. The interface balances strategic oversight with operational detail, making it useful for CIOs, compliance teams, business heads and government administrators. This reflects ICD’s ability to think beyond standard dashboards and design for the next layer of enterprise AI: managing the behaviour, value and risk of autonomous systems at scale.
Turning governance into action
The product was designed to connect monitoring with decisions. Agents are evaluated against internal policies, ethics checks, fairness rules, transparency standards and government-mandated frameworks. When a risk, breach or poor score appears, the system does not stop at reporting it. It gives managers clear actions such as update, pause, archive or kill the agent.
Making the Agent Workforce Measurable
The workforce and leaderboard views help organisations see how AI agents are distributed, who is creating them, and where they are delivering value. By combining usage, cost, time saved, ROI and rankings, the product turns agent adoption into something leaders can monitor, compare and improve across departments.
share
