Agentic AI Use Case Library

Curated, scored use case libraries for governed agent deployment. Each use case assessed against the Sprint Factory Use Case Selection Framework.

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Industry Libraries

The Use Case Selection Framework

Every use case in the library is scored on two axes: Impact (weighted 40%) and Feasibility (weighted 60%). Feasibility is weighted more heavily because the first use case must succeed. A high-impact use case that fails damages the entire programme.

Impact Score (40%)

CriterionWeightWhat It Measures
Time Recaptured15%Hours per week of knowledge worker time consumed by the manual version
Error Reduction10%Current failure rate, rework rate, or exception rate
Cost Avoidance10%Direct savings: FTE time, vendor costs, penalty avoidance, revenue leakage
Strategic Leverage5%Does success unlock downstream use cases or create reusable components?

Feasibility Score (60%)

CriterionWeightWhat It Measures
Data Availability15%Is the required data accessible, structured, and of acceptable quality?
Process Clarity15%Is the current process well-documented with explicit decision rules?
Ease of Implementation10%Technical complexity: system integrations, API maturity, data volume
Fallback Available10%Can the organisation revert to the manual process instantly if the agent fails?
Audience (Internal/External)10%Internal use cases score higher for first deployments

Execution Pattern Categories

Selection Principles

The first use case should be non-controversial. It should be something everyone agrees is tedious, error-prone, and low-value for the humans currently doing it. Nobody should feel threatened by its automation; they should feel relieved.

Find Your First Use Case

The Sprint Factory takes you from use case selection to a governed, production agent in 6 weeks.

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