Scenario 2 – Clear Expectations
An agency launched an AI PoC to automate the classification of incoming correspondence. Before development began, the team worked closely with business leaders to define clear success criteria, including measurable improvements in processing time, accuracy, and staff workload reduction.
A shared understanding of the project’s goals, benefits, and limitations was established early. The PoC was framed as a technical experiment and a strategic initiative aligned with the agency’s broader digital transformation agenda.
The PoC delivered strong results, exceeding performance benchmarks and demonstrating clear return on investment. Because expectations were well-managed and outcomes were communicated in business terms, the leadership team quickly approved the transition to pilot. The transition to pilot included further development of the technology, rigorous validation, integration with existing enterprise systems, and the development of operational processes for ongoing monitoring and improvement.
Meeting sponsor expectations including results achieved, risk controls and governance requirements, the solution was approved for production. The solution is now being scaled across multiple departments, with strong executive sponsorship and a roadmap for continuous improvement.
What Worked Well
- Success criteria were clearly defined upfront – processing time, accuracy, and workload reduction – providing a shared baseline
- The PoC was positioned not just as a technical experiment but as a key enabler of broader digital transformation goals
- Strong results were effectively communicated in business language, supporting fast sponsor approval to move to pilot
- Rigorous pilot‑stage validation included integration with enterprise systems, operational readiness processes, and ongoing monitoring
- Meeting risk, governance and quality expectations gave confidence in decision-making and cleared the path to production
Lessons Learned
- Without early and explicit framing of limitations (e.g., edge cases, data quality constraints), expectations could easily inflate
- Business owners required sustained engagement to avoid misalignment between early technical promise and real‑world operational complexity