Cover
Half Title
Series Page
Title Page
Copyright Page
Contents
List of Illustrations
Foreword
Preface
Acknowledgments
1. What Accountants Need to Know
Introduction
History of AI
History of Accountants Using Technology
Overview of How Accountants Are Using AI
Human Intelligence versus Artificial Intelligence
What Accountants Need to Know About AI
Artificial Intelligence
Artificial Narrow Intelligence (ANI)
Artificial General Intelligence (AGI)
Machine Reasoning
Expert Systems
Machine Learning
Supervised Learning
Unsupervised Learning
Semi-supervised Learning
Reinforcement Learning
Deep Learning
Natural Language Processing
Data Mining
Text Mining
Robotic Process Automation (RPA) and AI
Application Programming Interfaces (API) and AI
Best Programming Languages Accountants Should Learn for Artificial Intelligence Applications
Notes
References
2. Applications of AI in Accounting
Financial Accounting Applications
Cash and Account Reconciliations
Receivables and Sales
Inventory
Accounts Payable
Management Accounting Applications
Audit Applications
Tax Applications
Advisory Applications
Conclusion
Note
References
3. Robotic Process Automation (RPA) and AI
Overview of RPA
RPA Vendors
When to Use RPA?
Advantages and Challenges of RPA
Challenges of RPA
Applications of RPA in Public Accounting
RPA in Audits
RPA in Tax
Applications of RPA in Corporate Accounting
Implementation of RPA
Why RPA Fails
Integrating RPA with AI/ML Applications
References
4. Text Mining
What is text mining?
The role of natural language processing in text mining
Overview of Text Mining Research
Methods and Technologies Used in Text Mining
Document Preprocessing
Data Selection and Filtering
Data Cleaning
Document Representation
Morphological Normalization and Parsing
Semantic Analysis
Mining
Clustering
Classification
Entity and Relation Extraction
Visualization
Visualization Techniques for Multidimensional Data
Text Summarization
Advantages and Disadvantages of Text Mining
Current and Potential Applications of Text Mining in Accounting
Audit Automation
Accounting Automation
Tax Automation
Business Advisory Automation
References
5. Contemporary Case Studies
Case Study #1: Use of NLP for Risk Analysis (KPMG)
Background
Results
Lessons Learned
Case Study #2: Use of AI for Tax Transfer Pricing Services (KPMG)
Background
Results
Lessons Learned
Case Study #3: Autonomous Audit Drones for Inventory Management (EY)
Background
Results
Lessons Learned
Case Study #4: Use of AI to Augment Auditor Judgment (Deloitte)
Background
Results
Lessons Learned
Case Study #5: Use of Data Automation and RPA for Tax Functions (Grant Thornton)
Background
Results
Lessons Learned
Conclusion
Notes
Reference
6. Challenges and Ethical Considerations of AI
Algorithmic Bias
Definition of Algorithmic Bias
Guidance for Algorithmic Bias Considerations
Security, Privacy and Change Management Risks
Security and Privacy Risks
Change Management Risks
Regulations Related to AI
Ethical Considerations
Accountability and Professional Responsibility
Fairness and Non-Discrimination
Human Control of Technology
Privacy and Security
Transparency and Explainability
Promotion of Human Values
Note
References
7. Future Outlook
Future of the Accounting Profession
Technology Changing the Landscape of the Accounting Profession
Firm Hiring Trends of Accounting Graduates
Skillsets Needed in the Next Ten Years
Accounting Educators
Strategies for Incorporating AI into the Classroom
AI Training for Faculty
Conclusion
References
Glossary of Terms
Index