Reviewing the Use Cases of SAP Business AI in Finance

In this chapter, we will explore how AI is transforming finance-related processes within SAP S/4HANA. As businesses increasingly adopt AI technologies, it is crucial to understand how these powerful tools can enhance efficiency, accuracy, and decision-making in financial operations.

Throughout this chapter, we will delve into specific use cases that demonstrate the integration of AI along the finance process landscape. By examining real-life examples, you will gain insights into how AI can streamline tasks, automate workflows, and provide valuable data-driven insights.

Lead to Cash

The Lead-to-Cash process involves multiple stages, including lead generation, opportunity management, quotation, order processing, invoicing, and payment collection.

As businesses strive to optimize their financial operations, AI-powered solutions within SAP S/4HANA are revolutionizing the Lead-to-Cash process. By leveraging advanced analytics, machine learning, and intelligent automation, organizations can streamline their Lead-to-Cash workflows, improve customer experiences, and accelerate revenue growth.

The graph below provides an overview of the process steps along the Lead to Cash flow, highlighting the different aspects and approaches to AI integration.

The image depicts a flowchart showing various business processes within the Lead to Cash process and how they are connected. The processes include Create Sales Order, Manage Credit Risk, Collection Management, Post Goods Issue, Dispute Management, Manage Payments and Bank Communication, and Manage Cash and Working Capital.The connections between these processes are represented by arrows, indicating the flow and relationships. At the bottom of the image, there are three key technologies and approaches mentioned: Machine Learning, Situation Handling, and Intelligent Robotic Process Automation. These represent the underlying methods or tools used to optimize and automate the connected business processes shown in the flowchart.

The table below lists the capabilities in the Lead to Cash process where SAP Business AI is already integrated or planned for future integration.

Intelligent Process Automation Capabilities for Lead to Cash

Process Step	Process Automation Capabilities
Create Sales order	Delivery Performance/Delivery in Time Create Sales Order from unstructured data Automatic Sales Orders Creation from Excel Delivery Schedule Creation from Excel Delivery Insights for Sales Orders Data Not Extracted for Order Creation Data Incomplete for Order Creation Sales Item Delivery Date Changed Sales Item Delivery Date Reached Planned Execution Date Changed Planned Execution Date Reached Mass Change of Sales Docs
Manage credit risk	Confirmation is Overdue for PR Item Approve Documented Credit Decisions
Post Goods Issue	Automatic Return Creation from Excel
Collection Management	Collections Invoice Information
Dispute Management	Email Notification to Customer Manage Customer Email Response Process Collection Forms for Dispute Cases Dispute Case Processing
Manage Payments and Bank Communication	Cash App Receivables Line-Item Matching Cash App Payment Advice Extraction Advanced Bank Statement Automation Automated Upload of Bank Statements Invoice Skipped in Payment Advice Bank Message Still in Status Created Bank Message Entering Error Status Bank Message Requires Manual Processing No MBC Status Received for Bank Message Bank Message Still in Status Received
Manage Cash and Working Capital	Predictive Cash and Liquidity Management

In the following examples, we will showcase how SAP Business AI enhances various tasks throughout the Lead to Cash process, demonstrating concrete improvements in efficiency and productivity.

Streamlining Customer Dispute Resolution with SAP Business AI

SAP's Dispute Management solution, powered by AI, streamlines the dispute resolution process, enabling customer service representatives to quickly and effectively address customer concerns. In this video, we'll follow James, a customer relations specialist, as he navigates through a typical day, showcasing how AI-driven tools within SAP's Dispute Management system help him resolve customer issues with ease and professionalism.

Managing Payments and Bank Communication

Discover how SAP Business AI streamlines payment processing for accountants. In this video, we'll demonstrate how AI-powered tools extract data from payment advices, simplify the review process, and automate the clearing of open items, enabling faster and more accurate financial operations.

Getting Financial Business Insights with SAP Business AI

Explore how AI empowers project controllers to gain valuable insights and optimize their Lead to Cash cycle. In this video, we'll follow Ella as she leverages AI-powered tools to analyze KPIs, review project profitability, and collaborate with her digital assistant Joule to identify areas for improvement and share insights with her team.

Source to Pay

The Source-to-Pay process encompasses various stages, from sourcing and procurement to invoice processing and payment.

As companies aim to streamline their financial operations, AI-powered solutions within SAP S/4HANA are transforming the Source-to-Pay process. By harnessing advanced analytics, machine learning, and intelligent automation, organizations can optimize their Source-to-Pay workflows, enhance supplier relationships, and improve cost savings.

The graph below provides an overview of the process steps along the Source to Pay flow, highlighting the different aspects and approaches to AI integration.

The image depicts a flowchart showing various business processes within the Source to Pay process and how they are connected. The processes include Create/Manage Purchase Requisition, Create/Manage Purchase Order, Create/Manage Supplier Invoice, Process Accounts Payable, Process Payments, Manage Payments and Bank Communication, and Manage Cash and Working Capital.The connections between these processes are represented by arrows, indicating the flow and relationships. At the bottom of the image, there are three key technologies and approaches mentioned: Machine Learning, Situation Handling, and Intelligent Robotic Process Automation. These represent the underlying methods or tools used to optimize and automate the connected business processes shown in the flowchart.

The table below lists the capabilities in the Source to Pay process where SAP Business AI is already integrated or planned for future integration.

Intelligent Process Automation Capabilities for Source to Pay

Process Step	Process Automation Capabilities
Create / Manage Purchase Requisition	Create Purchase Requisitions from Excel Confirmation is Overdue for PR Item
Create / Manage Purchase Order	Predict Delivery Date Pending Supplier Confirmation Purchase Order Confirmation
Process Accounts Payable	GR/IR reconciliation Delivery Quantity Deficit GR/IR Clearing processor changed GR/IR deviation exceeds threshold
Process Payments	Payment Advice Processing Automated Release of Blocked Supplier Invoices Manage Payment Advice Cash Discount at Risk Blocked or Due Date Approaching Invoice Skipped in Payment Advice Payment Reject, Requires Manual Repair Batch Partially Rejected, Rejected, Status Check
Manage Payments and Bank Communication	Cash App Payables Line-Item Matching Advanced Bank Statement Automation Automated Upload of Bank Statements Bank Message Still in Status Created Bank Message Entering Error Status Bank Message Requires Manual Processing No MBC Status Received for Bank Message Bank Message Still in Status Received
Manage Cash and Working Capital	Vendor Inquiry Automation