Speaker
Description
The accelerated integration of generative artificial intelligence (GenAI) into accounting practice is reshaping professional roles, task structures and required competencies. Automation of routine procedures has shifted the emphasis of accounting work toward analytical reasoning, ethical judgment and the supervision of AI‑generated outputs. However, many accounting programmes continue to rely on traditional, rule‑based teaching methods that offer limited opportunities for experiential learning and decision‑making in realistic professional contexts.
The aim of this paper is to explore how GenAI‑powered simulations can be employed in accounting education to support experiential learning, ethical reasoning and the development of higher‑order professional skills. Rather than focusing on technical automation, the study examines the pedagogical potential of GenAI to create dynamic, interactive learning scenarios that mirror contemporary accounting challenges, such as financial analysis under uncertainty, ethical dilemmas in reporting, fraud detection, and audit planning.
The paper adopts a qualitative, conceptually driven methodology based on three elements. First, a structured review of recent academic literature on experiential learning, simulation‑based education and GenAI applications in business and accounting education is conducted. Second, common accounting decision contexts are identified and structured as simulation‑based learning scenarios generated or mediated by GenAI systems. Third, a comparative pedagogical analysis of selected GenAI platforms used for adaptive tutoring, role‑playing and scenario generation is undertaken, focusing on criteria relevant to higher education, such as feedback quality, scalability, accessibility and alignment with accounting learning objectives.
The preliminary results indicate that GenAI‑powered simulations offer significant pedagogical advantages over traditional case‑based approaches. They enable continuous interaction, personalised feedback and the exploration of multiple decision pathways, thereby strengthening reflective learning and professional judgment. The analysis further suggests that GenAI‑mediated role‑play is particularly effective in addressing ethical reasoning and professional scepticism, competencies that are frequently identified as underdeveloped in accounting graduates. Additionally, the use of adaptive AI tools allows instructors to shift their focus from content delivery toward learning design and guided reflection.
The paper contributes to current debates on digital transformation in economic and business education by demonstrating how generative AI can be leveraged as a pedagogical resource rather than a threat to academic integrity. It offers practical insights for accounting educators seeking innovative, experience‑based teaching approaches that respond to the evolving demands of the profession, without relying on quantitative data analysis or primary empirical testing.
