Pain points: • Many pain points are only discovered when someone directly experiences a problem within a process. • Each department typically sees issues only within its own scope, while the actual bottleneck may lie in the interaction between multiple units. • As a result, systemic inefficiencies can persist for a long time without being clearly identified.

Solution: • Build an AI system that analyzes real operational data such as: o Workflow logs o Approval times o Returned or resubmitted requests o Form submissions o Service requests/tickets o Email metadata and follow-up patterns o Calendar and meeting data

• The AI can automatically identify: o Which processes take the longest to complete. o Which approval steps are most frequently delayed or stuck. o Which departments require the most follow-up or chasing. o Which forms or requests are frequently rejected or resubmitted. o Which activities consume significant time while delivering relatively low value. o Which information is repeatedly entered across multiple systems. o Which workflows involve excessive hand-offs between departments.

• The final output can be presented in a dashboard that automatically prioritizes issues based on their level of impact and recommends the processes with the greatest potential for improvement or automation.