This course provides an overview of Artificial Intelligence(AI) in accounting. This course includes a detailed discussion of key AI concepts as well as its use in data analysis and reporting. This course also provides an overview of how organizations can implement AI solutions as well as the factors to consider when implementing these softwaresolutions. This course concludes with a discussion of the common challengesand barriersto AI adoption.
Learning Objectives
Upon successful completion of this course, participants will be able to:
Identify key concepts related to AI
Recognize subsets of machine learning
Identify key characteristics of deep learning
Recognize how AI can be used in the accounting profession
Identify key differences in traditional vs. AI-driven accounting software
Recognize examples of various types of AI accounting software
Identify AItools like OCR and NLP for data extraction
Recognize AIalgorithmsfor data cleansing
Identify data normalizationand AItechniques
Identify AI-driven forecasting techniques for accurate predictions
Recognize readiness factors for AI adoption in organizations
Identify steps for integrating AI into existing processes and workflows
Recognize the importance of training and upskilling employees
Identify common challenges and strategies for AI adoption in organizations
Major Topics
AI Key Concepts
Machine Learning
Deep Learning
Algorithms
Significance of AI in the Accounting Profession
AI Technologies in Accounting Software
Tax Preparation Software
Robotic Process Automation
Ethical Implications of Adopting AI Technologies
Using AI for Data Analysis and Reporting
Using AI for Data Extraction, Cleansing and Normalization
Considerations When Adopting AI
Integrating AI into Existing Workflows
