Tool

Agents & Automation Use Case Canvas

A guided, savable canvas teams can complete to evaluate candidate tasks for automation or agentization — capturing problem, current process, inputs/outputs, value, risks, human oversight points, monitoring and rollout plan.

Interactive Tool

Agents & Automation Use Case Canvas

This guided canvas helps teams safely evaluate tasks for automation or agentization. Use it to clarify the problem, document the current process, note required inputs and outputs, estimate value, identify risks and oversight points, and decide how you will monitor and roll back if needed. Save a copy to refer to during design, pilot, and review.

Complete the fields below with practical detail. When possible, link to sample data, logs, or process maps in your repository. Be conservative about removing human judgement — document any decision points that must remain human-in-the-loop.

Give this automation a short, descriptive name (e.g., 'Auto-triage meeting notes to action items').
Who will be accountable for the design, pilot, and ongoing monitoring?
What problem are you trying to solve, who is affected, and what improved outcome will success deliver? Be specific about the outcome you care about.
Describe the current steps, systems, roles, frequency, and where friction or cost appears. Link to process maps or SOPs if available.
List the main steps and any decision points where human judgement is applied. Mark which steps you are considering for automation.
What data, documents, APIs or sensors are required? Include formats, frequency, accessibility, and any data quality concerns.
What will the automation produce (reports, tickets, notifications, updated records, suggested decisions)? Who consumes these outputs?
Describe anticipated benefits (time saved, fewer errors, faster throughput, better customer experience). If possible, estimate metrics or ranges.
Optional numeric estimate such as hours saved, cost avoided, or revenue enabled. Use consistent units across use cases to compare later.
How will you measure success during pilot and at scale? Define baseline, target, measurement frequency, and data owner.
Help the team prioritize which opportunities to pilot first.
Identify how the automation could fail, create harm, or degrade outcomes. Consider bias, data drift, incorrect outputs, security, privacy, and operational risk.
Specify which decisions must remain human-in-the-loop or require explicit sign-off, including criteria for escalation.
Where does work pass between systems, agents, and people? Who receives outputs and what actions are expected?
How will you monitor accuracy, performance, and unexpected behavior? Define metrics, dashboards, alert thresholds, and who is notified.
Choose a sensible cadence for review during pilot and production.
Define specific measurable conditions that would require pausing or rolling back the automation. Include who can trigger rollback.
Note any personal data, regulatory constraints, required approvals, encryption, or access control needs.
Consider fairness, transparency, explainability, user consent, and how the automation affects jobs or vulnerable people.
List system accounts, API access, credentials, or datasets required to implement the automation.
Rough development + testing estimate to compare candidates.
If yes, prepare a short pilot plan and stakeholder review.
Define a bounded pilot: target users, duration, evaluation criteria, and rollback plan.
List people/roles to inform, consult, or approve (Legal, Security, Compliance, Operations, Product, etc.).
Concrete next actions (e.g., 'map API access', 'draft pilot script', 'run 2-week shadow test').
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