Accounting and Financial Management Research Seminar – Dr David Grundy

Title: The LOV AI Co-Creation Approach: Creating Business Teaching Cases with Deep Research AI

Date: 29 October 2025

Time: 14:00-15:00

Venue: NUBS.2.03

If you would like to attend, please register using the following link

The LOV AI Co-Creation Approach: Creating Business Teaching Cases with Deep Research AI

Speaker:   Dr David Grundy

https://www.ncl.ac.uk/business/people/profile/davidgrundy.html

Abstract:

This paper examines the use of generative artificial intelligence in the development of teaching cases for MBA programs. The study introduces the Lecturer Oversight and Verification of AI (LOV AI) Co-Creation Approach, which integrates the ChatGPT o3 Deep Research model with structured subject expert supervision to produce teaching extended case studies and related teaching materials. The model is implemented through a multi-step process. First, specific prompts are used to identify and select potential case topics that align with required syllabus objectives. Next, the AI model generates extensive drafts that include narratives, background information, and supporting data for each case. These outputs are then reviewed in detail by subject expert who verified the accuracy of the information, correct any inconsistencies, and adjust the content to meet pedagogical standards. This process involves constant iterative improvements and co-creation actions by the lecturer to ensure that the final materials reflect both current business developments and academic rigor. Preliminary findings indicate that the integration of AI reduces the time required to produce high-quality teaching cases while maintaining the depth and complexity necessary for graduate-level education. However, the study also highlights the importance of continuous human intervention of subject experts to address potential factual errors and to ensure the educational integrity of the cases. The paper contributes a practical framework for AI-assisted case study development, offering insights into the benefits and limitations of merging automated tools with expert oversight in the context of business education. Further research is recommended to evaluate the model’s long-term impact on teaching effectiveness and student learning outcomes.