Uncovering the Generative AI (GenAI) to Agentic AI (AgAI) Shift for Business School Education

Uncovering the Generative AI (GenAI) to Agentic AI (AgAI) Shift for Business School Education

Marios Kremantzis (University of Bristol, UK), Aniekan Essien (University of Bristol, UK), Eleonora Pantano (University of Bristol, UK), and Sophie Lythreatis (University of Bristol, UK)
Copyright: © 2025 |Pages: 21
DOI: 10.4018/JGIM.389920
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Abstract

This article conceptually examines the transformative potential of Agentic AI (AgAI) in redefining business education by addressing the limitations of Generative AI (GenAI) in fostering learner agency and higher-order skills. While GenAI excels at reactive tasks, its static, prompt-driven design struggles to cultivate autonomy, critical reflection, and adaptive decision-making, while challenging individual's linguistic abilities. In contrast, AgAI (characterised by autonomy, contextual adaptability, and proactive engagement) positions AI as a collaborative partner. Grounded in proxy agency, self-determination theory, and constructivist learning theory, AgAI empowers students to iteratively pursue goals, navigate dynamic scenarios, and reflect on learning strategies while retaining control over their educational paths. The article proposes an enhanced human-AI collaboration model where AgAI augments learning through intelligent tutoring systems, multi-agent simulations, and personalized content curation, bridging gaps in experiential learning, scalability, and ethical reasoning.
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Introduction

Advances in artificial intelligence (AI) are poised to transform business education (Nguyen et al., 2024a). In the broader economy, rapid technological change, particularly the rise of machine learning and intelligent platforms, is reshaping industries at an unprecedented pace (Kulichyova et al., 2025). Brynjolfsson and McAfee (2017) warned that we may be underestimating how quickly AI-driven changes can destabilize traditional sectors, including higher education, by concentrating advantages in the hands of those who adapt most quickly. At the same time, AI is increasingly viewed as one of the most disruptive and important new technologies in organizations (e.g., Chen & Wang, 2024; Xu et al., 2025; Ye et al., 2024; Zhang & Siau, 2024). Still, adoption remains in its early stages for many enterprises, with fewer than half of large firms having meaningful AI initiatives (Benbya et al., 2020; Davenport & Ronanki, 2018). These developments signal that business schools must proactively rethink how to prepare learners for an AI-augmented world.

Recently, generative AI (GenAI)—exemplified in systems such as ChatGPT and Gemini that produce content in response to user prompts—has emerged as a prominent educational tool (Essien et al., 2025; Huo & Siau, 2024; Nguyen et al., 2024a; Yang et al., 2024). Specifically, GenAI systems are predominantly reactive (Kumari et al., 2025; Tao et al., 2025), offering outputs only when prompted and operating within the confines of their training data. They enhance efficiency in lower-level cognitive tasks (e.g., retrieving knowledge or drafting text), and many institutions have already begun deploying GenAI for chatbot-based questions and answers, writing feedback, and content generation, including essay drafting and quiz creation (Nguyen et al., 2024b; O’Dea, 2024; Yang et al., 2024). For instance, AI text generators can assist students in drafting essays or practicing business communication (Nguyen et al., 2024b; Yang et al., 2024). Universities in many countries, including the United Kingdom, are incorporating AI detection systems into their online platforms for student assignment submissions. However, these platforms do not always provide reliable results. Still, universities in countries such as Italy are discussing the potential use of AI; however, no formal initiatives have been undertaken yet.

Thus, a core issue has surfaced: the static, on-demand nature of GenAI does not cultivate the higher-order skills and learner autonomy demanded in business education. While studies show GenAI can boost performance on basic tasks, it yields only minimal gains for advanced skills, including critical thinking, metacognition, and problem-solving (Essien et al., 2024; Larson et al., 2024). Over-reliance on AI-generated answers may even encourage passive learning, as students bypass the deep engagement needed for authentic understanding.

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