Case Study: SoftBank scales an AI agent-powered sales model, projecting 250K hours saved a year with Dataiku
Key results
The challenge
SoftBank Corp.'s sales organization needed to share customer intelligence across representatives and internal teams, but records of conversations and insights were fragmented across minutes, memos, and other formats and could not be centrally consolidated. Information gathered in the field was too vast to be reliably aggregated in CRM, and an internal survey found sellers spent only about 20% of their time with customers.
The solution
Using Dataiku, SoftBank built a suite of AI agents that automated insight capture, analysis, and communication across the sales cycle. An insight-extraction agent structured meeting data using the team's sales metrics, a standardization agent unified opportunity stages for consistent forecasting, and research and chat agents generated account-plan materials and let sellers query deal status. A working prototype launched within one month and adoption scaled across regions.
“We are working to automatically capture every conversation, without requiring sales input as a trigger, and have an AI agent deliver the right outputs to the sales team at the right time.”
SIShintaroh ImanoSoftBank
The results, in context
SoftBank reports that 90% of sellers see higher quality and efficiency in data-driven selling and that 80% of customer conversations now link directly to CRM opportunities. The company estimates roughly 20 hours saved per seller per month, projected to 250,000+ hours saved annually at scale.