Five Generative AI Use Cases for Enterprise IT Leaders — Appian
Enterprises broadly face challenges bridging the gap between AI anticipation and implementation, while individual organizations struggled with labor-intensive, error-prone manual processes across claims handling, customer service, and document processing.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Claims FNOL intake
Claims are captured through a portal and a First Notice of Loss (FNOL) intake process.
Tools used
AppianAppian Connected ClaimsRPAlarge language models
Outcome
AI-powered workflows delivered measurable results across multiple organizations: Aviva France saw same-day claims processing surge from 1% to 25% and settlements increase by 530%; Leroy Merlin streamlined up to 90% of manual processes; Texas DPS made information viewable by more than 10,000 stakeholders; and Global Excel implemented a claims portal and FNOL intake process in less than 12 weeks.
What failed first
Leroy Merlin's fragmented oversight and data silos between systems caused prolonged approval processes, frequent order cancellations, a decline in customer satisfaction, and financial losses from inaccurate data. Aviva France's agents dealt with disjointed systems that slowed claims handling.