Summary: This session focuses on practical finance applications: turning messy data into AI-ready formats, building analysis tools for problems previously 'too expensive to explore,' and automating the manual work that finance teams have normalized.

Outcome: Identification of high-ROI AI opportunities in back-office operations

Takeaway: Two or three specific back-office AI applications to evaluate for your organization

Key Discussion Points:

• Why back-office AI delivers better ROI than front-office investments
• The hidden cost of manual work finance teams have normalized
• Data readiness: turning messy data into AI-ready formats
• Use case: automating data extraction and categorization
• Use case: exception-based processing and anomaly detection
• Use case: analysis tools for previously unexplored problems
• Building vs. buying: when to use off-the-shelf vs. custom solutions
• Change management: helping teams adopt AI-assisted workflows
• Measuring success: KPIs for back-office AI initiatives
• Case study: real-world back-office transformation results