A government agency is planning to implement a new AI-driven public service system.

Within the PMI-CPMAI guidance, developing a strong business case for AI requiresevidence-based justificationthat the proposed solution will deliver measurable value, not just theoretical benefits. For a government agency whose stated goals areimproving service deliveryandreducing response times, the most convincing way to support a funding request is todemonstrate these improvements in a realistic environment. Apilot programor proof-of-concept allows the project team to implement the AI-driven public service system on a limited scale, collect operational data, and compare key performance indicators (KPIs) such as response time, throughput, user satisfaction, and error rates before and after AI adoption.

PMI-CPMAI emphasizes that pilots help validate assumptions about feasibility, scalability, and stakeholder acceptance while revealing hidden risks and integration issues early. They provide concrete, context-specific metrics that can be used directly in the business case, strengthening arguments around public value, efficiency gains, and cost-effectiveness. By contrast, case studies and workshops are indirect and qualitative, and ROI projections alone remain hypothetical without empirical evidence. Therefore,conducting a pilot programbest meets the project manager’s objective of producing robust, measurable results that support a compelling AI business case for funding approval.