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 software solutions. This course concludes with a discussion of the common challenges and barriers to AI adoption. The course consists of 4 chapters:
- Chapter 1 - Introduction to Artificial Intelligence (AI)
- Chapter 2 - AI Technologies in Accounting Software
- Chapter 3 - Using AI for Data Analysis and Reporting
- Chapter 4 - Considerations When Adopting AI
This chapter provides an overview of the basics of AI, including the key concepts related to AI such as machine learning, deep learning, and Natural Language Processing. This chapter also provides a discussion of how AI and automation can be used in the accounting profession.
This chapter provides an overview of how AI is reshaping accounting software, streamlining tasks, improving accuracy, and offering advanced analytics. It covers key AI-driven features like automated data entry, intelligent invoice processing, predictive analytics, fraud detection, risk assessment, and natural language processing.
This chapter provides an overview of leveraging AI for data analysis and reporting in accounting. It covers the automation of data extraction, cleansing, and normalization processes as well as how AI facilitates automated financial analysis and forecasting. This chapter also addresses how AI generates actionable insights from financial data which aids in strategic planning.
This chapter provides an overview of some of the implementation strategies and considerations when integrating AI technologies within organizations. It addresses how you can assess readiness for AI adoption as well as integrating AI into current workflows. This chapter also addresses the importance of training and upskilling staff to effectively utilize AI tools and some of the common challenges and barriers to AI adoption.
Learning Objectives
- 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 AI tools like OCR and NLP for data extraction.
- Recognize AI algorithms for data cleansing.
- Identify data normalization and AI techniques.
- 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.
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Prerequisites
No advanced preparation or prerequisites are required for this course.