Innovative Data Sources and Tools: Generative AI

In this class, students will explore the role of Generative AI, particularly Large Language Models (LLMs) like GPT, in data analytics. The session will begin with an introduction to the practical applications of GPTs in automating initial analyses and improving workflow efficiency. Using a case-based approach, students will interact with GPT models to generate a first-pass analysis of the case requirements, saving the output for refinement. The class will emphasize how GPTs can assist in building Python code that meets specific analytical needs, while also showcasing how iterative dialogue with LLMs can improve the quality of the solution.

Why is this important?

As generative AI continues to transform various industries, understanding how to effectively leverage these tools is essential for accounting and data professionals. By learning how to use GPTs and other LLMs, students will gain a competitive advantage in automating routine tasks, accelerating problem-solving, and enhancing data-driven decision-making processes. This class equips students with the ability to integrate cutting-edge AI technologies into their analytical workflows, which is increasingly valuable in fields such as forensic accounting, audit, and advisory services. The hands-on experience also prepares students to navigate the ethical and practical challenges posed by these powerful tools.

Materials:

Case: Prompt Engineering Examples Background Case
Case: GPT Forensics Case
Slides: will be available for download by the beginning of class in either powerpoint or pdf formats.
Data: A data update may be required for this class. To ensure your files are the most up-to-date, navigate to ACCTG522_Labs folder and run the command git pull.
Analytics Tools: Chat GPT or another Large Language Model (LLM), Python and Alteryx

Review and Extension:

This class builds on the foundation of previous sessions by expanding the toolkit available for data extraction and analysis. While earlier classes focused on more traditional ETL processes and textual analysis methods, this session introduces an innovative approach by integrating GPTs into the analytical process. Students will apply their knowledge of Python and Alteryx in combination with AI-driven solutions, pushing the boundaries of conventional data analysis techniques. This session's case studies and exercises will further develop their skills in leveraging advanced technologies to automate and streamline complex data workflows.

Preparation:

1. The background reading and case can either be read in advance, or used as a reference.
2. Pre-reading the Forensics Case isn't strictly necessary, but will make the work we do easier.

Class Plan:

Teams: during this class, please sit in your discussion teams.

1. We will start with a short discussion of GPTs and a practical way of using them in data analytics.
2. We will first ask the GPT to provide a first pass at the requirements for the case. The output will be saved as the first attempt.
3. We will then refine our approach to the case by interacting with the GPT in building python code to execute the requirements.