Intelligent Finance with SAP

AI-Based Automation and Custom Solutions
1. Auflage 2026
ISBN: 978-1-4932-2827-0
Verlag: Rheinwerk Verlag GmbH

Buch, Englisch, 535 Seiten, Format (B × H): 261 mm x 183 mm, Gewicht: 1106 g

You’ve seen the hype around AI—but are you ready to make the most of it? With this book, discover how standard and generative AI can elevate your finance capabilities. Take a tour of SAP’s embedded and service-based AI tools for your core processes: accounts receivable and payable, general ledger accounting, predictive accounting, and more. Go beyond the available functionality and learn how to create custom use cases tailored to your business. It’s time to unlock the future of finance!

In this book, you’ll learn about:

a.Navigating SAP’s AI Landscape

See what’s possible with SAP’s out-of-the-box standard and generative AI tools. From SAP Business AI to SAP BTP, explore how cutting-edge capabilities elevate your finance business processes.

b.Leveraging AI Tools

Set up and use AI services and embedded capabilities. Automate invoice processing with SAP Build Process Automation, use low-code/no-code tools to enable intelligent asset accounting, perform predictive forecasting with Smart Insights, and more.

c.Crafting a Custom AI Solution

Identify your organization’s unique requirements—and then design custom AI solutions. Explore use cases that demonstrate how SAP and third-party AI tools like Joule, SAP Databricks, and OpenAI can work together to solve your finance business problems.

Highlights include:

1)Standard and generative AI

2)Custom AI solutions

3)Accounts payable and receivable

4)Asset accounting

5)General ledger accounting

6)Predictive planning and accounting

7)Working with financial data

8)Content transformation

9)SAP tools (Joule, SAP Databricks, and more)

10)Third-party tools (OpenAI, Gemini, and more)

11)AI assistants

12)Agentic AI

Autoren/Hrsg.

Bikulcius, Darius

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware SAP
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen

Inhaltsverzeichnis

... Preface ... 17

... Target Audience ... 18

... Objectives of This Book ... 20

... How to Read This Book ... 22

... Closing Thoughts ... 23

1 ... Introduction to AI with SAP ... 25

1.1 ... Types of AI in Your SAP Landscape ... 26

1.2 ... SAP Business AI ... 41

1.3 ... Solutions in SAP BTP ... 47

1.4 ... Third-Party Solutions ... 58

1.5 ... Summary ... 63

PART I ... Leveraging Standard and Generative AI ... 65

2 ... Accounts Receivable ... 67

2.1 ... Master Data ... 68

2.2 ... Customer Invoices ... 79

2.3 ... Payment Advice and Bank Statements ... 89

2.4 ... Dispute Management ... 91

2.5 ... Cash Application ... 94

2.6 ... Cash Forecasting ... 98

2.7 ... Summary ... 99

3 ... Accounts Payable ... 101

3.1 ... Master Data ... 101

3.2 ... Supplier Invoices ... 102

3.3 ... Supplier Downpayment Requests ... 111

3.4 ... GR/IR Reconciliation ... 113

3.5 ... Invoice Automation with OpenText ... 114

3.6 ... Summary ... 118

4 ... Intelligent Asset Accounting ... 121

4.1 ... Master Data ... 122

4.2 ... Asset Acquisitions ... 127

4.3 ... Asset Transfers ... 130

4.4 ... Asset Retirements ... 136

4.5 ... Asset Scrapping ... 142

4.6 ... Summary ... 144

5 ... General Ledger Accounting ... 147

5.1 ... Journal Entries ... 148

5.2 ... AI-Assisted Journal Upload ... 154

5.3 ... Accruals ... 160

5.4 ... Reclassification ... 164

5.5 ... Exchange Rates ... 167

5.6 ... Intelligent Intercompany Matching and Reporting ... 171

5.7 ... Summary ... 177

6 ... Predictive Accounting ... 179

6.1 ... Prediction Ledger ... 179

6.2 ... Sales Order ... 181

6.3 ... Data Quality Management ... 183

6.4 ... Profit Center Reorganization ... 186

6.5 ... Travel and Expense Management ... 193

6.6 ... Summary ... 198

7 ... Predictive Planning and Analytics ... 201

7.1 ... Just Ask ... 202

7.2 ... Smart Insights ... 210

7.3 ... Time Series Forecasting ... 217

7.4 ... Smart Grouping ... 225

7.5 ... Predictive Planning ... 232

7.6 ... Regression and Classification via Smart Predict ... 238

7.7 ... Summary ... 244

PART II ... Developing Custom AI Solutions ... 247

8 ... Designing, Deploying, and Scaling Custom AI Solutions for Finance ... 249

8.1 ... Identify Information Need and Finance Stakeholders ... 250

8.2 ... Assess Out-of-the-Box Functionality ... 256

8.3 ... Define Use Cases ... 259

8.4 ... Prioritize for Impact ... 263

8.5 ... Review Available Tools ... 266

8.6 ... Assess Development Cost ... 278

8.7 ... Define Implementation Steps ... 281

8.8 ... Understand Audit and Compliance Concerns ... 284

8.9 ... Summary ... 288

9 ... Summarizing and Synthesizing Financial Data ... 291

9.1 ... Automated Variance Commentary ... 292

9.2 ... Executive-Ready Flash Reporting ... 300

9.3 ... Earnings Call Preparation ... 307

9.4 ... Cross-LOB Performance Synthesis ... 317

9.5 ... Summary ... 323

10 ... Retrieving Financial Data ... 325

10.1 ... Natural Language Assistants ... 325

10.2 ... Automated KPI Lookups ... 331

10.3 ... Contract and Transaction Data Retrieval ... 341

10.4 ... Dynamic Drilldowns into Reports ... 349

10.5 ... Summary ... 358

11 ... Transforming Content ... 359

11.1 ... Raw Transaction Logs ... 360

11.2 ... Regulatory Filings ... 368

11.3 ... Multientity Reports ... 378

11.4 ... Historical Data ... 388

11.5 ... Summary ... 396

12 ... Turning Static Outputs into Dynamic Stakeholder Narratives ... 399

12.1 ... Additional Context ... 401

12.2 ... Market Intelligence ... 407

12.3 ... Real-Time KPIs ... 412

12.4 ... Sentiment and Peer Analysis ... 418

12.5 ... Summary ... 424

13 ... Leveraging Assistants ... 427

13.1 ... Financial Analyst Copilots ... 428

13.2 ... Investor Relations Assistants ... 439

13.3 ... Procurement Bots ... 448

13.4 ... Controllership Agents ... 458

13.5 ... Summary ... 467

14 ... Creating Content ... 469

14.1 ... Commentary ... 470

14.2 ... Investor Relations Scripts ... 476

14.3 ... Financial Summaries ... 480

14.4 ... Policies ... 485

14.5 ... Summary ... 489

PART III ... Looking Ahead for AI ... 491

15 ... Nine Elements of Future ERP AI Automation ... 493

15.1 ... The Four Pillars of the Intelligent Enterprise ... 494

15.2 ... The Nine Elements ... 495

15.3 ... Implications for Finance Leaders ... 508

15.4 ... Technology Impacts and Operating Model Shifts ... 510

15.5 ... Common Misconceptions and Failure Patterns ... 512

15.6 ... Putting the Nine Elements into Motion ... 513

15.7 ... From Principles to Roadmap: Building the Automation Portfolio ... 518

15.8 ... Measured Outcomes and Value Realization ... 520

15.9 ... Summary ... 522

... The Author ... 525

... The Contributors ... 525

... Index ... 527

Über Autor(innen)

Bikulcius, Darius
Darius Bikulcius is a director with PwC’s SAP financials practice. He has more than 23 years of experience with SAP financials design and implementation. During this time, he has specialized in the areas of automation in finance from invoice management, journal entry automation, and month-end close automation. Darius is SAP S/4HANA-certified in the finance and Central Finance solutions.