Generative AI is rapidly influencing tax workflows, yet its capabilities and limitations are often misunderstood. This session examines how Gen AI performs across different categories of tax tasks, with a specific focus on the K-1 lifecycle. Participants will learn how to distinguish between tasks that are well-suited for AI assistance (such as summarization, classification, or drafting) and tasks that require structured data, established workflows, domain expertise, or human professional judgment.
Using real examples from partnership reporting, we will highlight where AI can enhance efficiency and where accuracy, compliance considerations, and context-specific decision making still require human involvement or alternative AI approaches. The goal of the session is to equip practitioners with a practical framework for determining the appropriate solution for the task at hand, rather than relying on Gen AI as a universal answer.
By the end of this session, participants will be able to:
- Differentiate between drafting tasks and judgment-based tasks within tax workflows and explain why this distinction matters when applying Gen AI.
- Describe the types of tax tasks Gen AI performs effectively, including summarization, explanation, pattern recognition, and assisted review.
- Identify limitations of Gen AI in areas requiring structured data integrity, state sourcing logic, basis tracking, or compliance-driven calculations.
- Evaluate when a human-in-the-loop approach is required to ensure accuracy, defensibility, and adherence to ethical and regulatory standards.
- Apply a practical decision framework to determine whether Gen AI, traditional software, or human expertise is the optimal method for a given step in the K-1 process.
- Integrate AI tools responsibly within busy-season workflows while maintaining data privacy and professional oversight.
CPE Credit Information
Subject Area: Tax
Course Level: Overview
Instructional Method: Group Internet Based
Prerequisites: None
Advanced Preparation: None
