The work began with OPIM 5515: Generative AI for Business, a graduate course first offered at UConn in Fall 2024. The course became the textbook Generative AI for Business: Frameworks, Techniques, and Governance (2025), which gives instructors a coherent way to teach generative AI as an information systems and management topic: the foundations of large language models, prompt engineering, retrieval-augmented generation, AI agents, evaluation, and governance.

• Textbook adoption. A free instructor copy is available through VitalSource; more than 40 faculty members have requested access.
• Shared teaching resources. Accompanying slides have been shared with more than 150 faculty across 13 countries. GenAI4All.org provides the course structure, teaching materials, and sample video clips. A second edition is in progress.
• Faculty workshops. Generative AI teaching workshops at Lehigh University, Indiana University, and the University of Kansas, and at the 2025 and 2026 IT Teaching Workshops.
• Next course. The new OPIM 5519: AI Workflow for Business (Spring 2027) extends the work from AI capabilities to workflow redesign, drawing on the T-W-O framework and the business novel The Owner.

Instructors interested in the textbook or slides can start at genai4all.org or email publishing@genai4all.org.

Visit genai4all.org

OPIM 5515: Generative AI for Business is a graduate course designed to equip students with the knowledge and skills needed to leverage generative AI (GenAI) and Large Language Models (LLMs) in business contexts. It was first offered in Fall 2024.

Course Description

This course will delve into the core mechanisms of GenAI, focusing on Large Language Models (LLMs). Participants will explore advanced techniques in prompt engineering, retrieval augmented generation (RAG), agentic systems, fine-tuning LLMs, and ensuring the safety and ethical use of GenAI. The curriculum balances theoretical knowledge with hands-on exercises, enabling participants to apply GenAI innovations to real-world business challenges effectively. By demystifying the complexities of LLMs, this course aims to empower students to leverage these powerful models for creating innovative solutions and navigating the dynamic landscape of generative AI with confidence. By the end of the course, you should be able to:

• Articulate the essentials of LLM architecture, training methodologies, and business applications.
• Implement effective prompt engineering strategies to develop robust business applications.
• Integrate RAG into LLM applications to provide coherent and contextually relevant responses.
• Design agentic systems that incorporate tools, workflows, and multi-agent architectures.
• Customize LLMs using fine-tuning, balancing model capabilities and computational demands.
• Address safety and ethics issues in LLM applications.
• Engage in thoughtful discussions on the transformative potential of GenAI.

This course does require that you have some basic knowledge of machine learning and programming. But in general, this is not a coding heavy class. Instead, the focus is on creating business applications utilizing the rich ecosystem that has been built on top of LLMs.

OPIM 5519: AI Workflow for Business is a new graduate course, first offered in Spring 2027. It examines how organizations redesign business processes when AI can perform meaningful portions of analysis, drafting, coordination, and execution.

Course Description

The course treats AI tools as an essential part of workflow design, with particular attention to no-code workflow systems and coding agents as the main infrastructure for building and running AI-enabled processes. It is organized around the T-W-O framework (Task, Workflow, Organization) and a progression from workflow execution to critical evaluation to strategic oversight. Business cases, workflow simulations, redesign workshops, hands-on exercises, and a team project help students analyze and redesign workflows in accounting, finance, operations, marketing, and analytics. By the end of the course, you should be able to:

• Build and test AI workflows using no-code tools and coding agents.
• Analyze a business workflow and redesign it for effective human-AI collaboration.
• Determine which steps should be handled by humans, by AI, or jointly.
• Define the standards, review points, and context needed for reliable execution.
• Monitor workflow performance and evaluate results over time.
• Explain why AI improves some processes but creates problems in others.
• Assess governance, accountability, and measurement choices for AI workflows.
• Develop and present a workflow redesign for a real business use case.

Course readings include The Owner: A Business Novel about Work in the GenAI Era and Generative AI for Business.

As part of our effort at the UConn Digital Frontiers Initiative, we offer an intensive one-day Executive Workshop on Generative AI for business leaders, managers and data scientists. Using tools provided in class, we cover the following course content. You do not need to know programming to benefit from this workshop.

1. GenAI Introduction and Prompt Engineering
   Get started with the foundational concepts of generative AI and learn how to craft prompts that produce consistent, useful outputs.
   • Fundamentals of GenAI & Large Language Models (LLMs).
   • How to customize LLMs for your business applications.
   • Prompting engineering (e.g., few-shot, chain-of-thought) and hands-on exercise.
2. Retrieval Augmented Generation (RAG)
   Build scalable, knowledge-grounded chatbot with your organization’s private knowledge.
   • The RAG pipeline and business cases.
   • Embeddings, vector databases, and semantic search explained.
   • Hands-on exercise to create a RAG-based chatbot.
3. AI Agents and Workflows
   Explore agentic systems that reason, plan, and act with tools.
   • What makes an AI agent?
   • Business cases: AI for BI, code generation, deep research, and more.
   • Hands-on exercise to create an AI agent and workflow.
4. Evaluations and Team Integrations
   Explore how to structure AI initiatives with robust governance and long-term adaptability.
   • Transparency, hallucination, and evaluation frameworks.
   • Structuring teams for experimentation, deployment, and governance.
   • Business transformation using GenAI.

The workshop is based on the key learnings from my semester-long master class for the MS BAPM and FinTech programs (more info above). It typically takes the format of one-day training of 6 hours, but can be customized to the length and format most suited for your needs (e.g., 2-3 days). For workshop related inquiries, contact us here, or email me directly at weichen@uconn.edu.

University of Connecticut, 2023 - present

• OPIM 5519: AI Workflow for Business
  • New course, first offered Spring 2027
• OPIM 5515 (formerly 5894): Generative AI for Business
  • Fall 2024: 46 MS students, rating 5/5
  • Fall 2025: 14 MS students, rating 5/5
  • Fall 2026: 24 MS and MBA students
• OPIM 3505: Business Database Management
  • Fall 2023: 18 undergraduate students, rating 5/5
  • Fall 2024: 16 undergraduate students, rating 5/5
  • Fall 2025: 10 undergraduate students, rating 5/5
  • Fall 2026: 19 undergraduate students
• OPIM 5272: Data Management and Business Process Modeling
  • Fall 2023: 22 MS students, rating 5/5

University of Arizona, 2015 - 2023 (1,034 students)

• MIS 611C: Economics of Information Systems
  • Fall 2020 & 2022: 21 PhD students
  • Avg. rating: 4.96/5
• MIS 543 Online: Business Data Communications & Networking
  • Fall 2019 - Spring 2023: 263 MS students (online, Cybersecurity and MIS)
  • Avg. rating: 4.7/5
• MIS 543: Business Data Communications & Networking
  • Fall 2016 - Fall 2022: 464 MS students
  • Avg. rating: 4.6/5
• MIS 307: Business Data Communications
  • Fall 2015 - Fall 2018: 286 undergraduate students
  • Avg. rating: 4.5/5

UC San Diego, 2013 (32 students)

• MGT 103: Product Marketing and Management
  • Summer 2013: 32 undergraduate students
  • Avg. rating: 4.2/5