Tools or Fools: Are We Educating Managers or Creating Tool-Dependent Robots?

Abstract

This essay examines strategies for thoughtfully integrating generative AI (Gen-AI) into management curricula to enhance student learning while mitigating risks like overreliance. We make the case that outright resistance is counterproductive; instead, management educators should embrace Gen-AI’s potential to create more engaging, experiential learning aligned with andragogical principles. We provide a conceptual framework mapping nine Gen-AI objectives to the principles of andragogy. A semester-long course example illustrates this framework in action through AI activities fostering autonomy, competence, and real-world application. Student surveys revealed overwhelmingly positive perceptions of Gen-AI integration and improved exam scores. However, dependence risks remain. The essay discusses strategies to enhance critical thinking, personal growth, and academic integrity. Overall, we propose that prudent Gen-AI adoption can enrich management education, but long-term vigilance regarding overreliance is vital.

Keywords

Gen-AI Chat-GPT AI andragogy artificial intelligence

“There will be a further increase of useful things for useless people”—Illich (1973, p. 34)

Introduction

Artificial intelligence (AI), especially generative AI (Gen-AI) platforms like ChatGPT, Stable Diffusion, and Bard, has caused significant disruption within the educational landscape. Educators have broadly met this technology with resistance, perceiving it as a potential threat to their profession and detrimental to student learning outcomes (Mitchell, 2022; Mollick, 2022). This reaction is understandable, considering the seemingly boundless potential of such technologies. Yet, we posit that the advent of ChatGPT has ignited a paradigm shift for educators, indicating that containment strategies—such as bans and detection—will increasingly be predicated on the premise that educational institutions will maintain technological superiority, and educators will sustain their advantage in technological proficiency over students. However, we believe this is unlikely.

In our perspective, the business model pursued by ChatGPT—a high-quality product offered freely—parallels the strategies typical of disruptive innovations (Brynjolfsson & McAfee, 2012; Christensen et al., 2015). Consequently, the accelerated pace at which ChatGPT has enabled the diffusion of generative AI technology suggests a future where new products and services will be developed with an integration of these technologies. In fact, by January 2023, ChatGPT gained over 100 million users which made it the fastest growing consumer software application of all time (Smith-Goodson, 2023). As a result of the rapid adoption of ChatGPT, we are witnessing organizations developing AI strategies (Kemp, 2023) which, according to a recent McKinsey & Company Report, will have a significant impact across all industry sectors (Chui et al., 2023). Indeed, this accelerates what D. B. Allen et al. (2021, p. 182) noted prior to ChatGPT that, “technological advancement is rapidly becoming a part of business and the way work is conducted.” Given the current trajectory of Gen-AI, outright resistance may prove to be a suboptimal approach, as it risks overlooking the potential advantages that Gen-AI can offer to management education as we begin to embrace a digital mindset and aim to foster tech literacy in our students (S. J. Allen, 2020).

Despite the many exciting benefits AI can offer to the classroom experience, many professors harbor reservations about AI use in the classroom (McMurtie & Supiano, 2023). The crux of this fear is not merely about students using AI to cheat, but rather a deeper, more existential dread that students may become overly reliant on these technologies, thereby compromising their ability to think independently and critically (Illich, 1973). In other words, professors worry that students may not use these tools to augment their learning and enhance their competencies but, instead, become dependent on the tools themselves. As a result, students may potentially stunt their intellectual growth and critical thinking skills (Fornaciari & Loffredo Roca, 1999; Fügener et al., 2022). This concern is particularly pertinent in management education, where the development of critical thinking and problem-solving skills is of paramount importance (Smith, 2003).

The impact of Gen-AI largely hinges on its usage (Illich, 1973). As such, the challenge for educators is not to resist or fear these technological advancements, but to strategically integrate them into the curriculum in a way that enhances student learning and fosters critical thinking (S. J. Allen, 2020; Brynjolfsson & McAfee, 2012; Smith, 2003). In this light, the arrival of Gen-AI emerges not as a threat, but as an opportunity for educators to revamp pedagogical strategies, utilize these tools to enhance student learning experiences, and craft modern curricula or learning opportunities that ready students for a future with Gen-AI at the forefront (S. J. Allen, 2020). With the growing adoption of Gen-AI technology (Friedersdorf, 2022), it falls to management educators to consider adaptation and navigate a path forward in this evolving landscape. Hence, this essay aims to offer a roadmap for integrating generative AI in a manner that augments competence and autonomy in learners, instead of creating a generation overly reliant on machines. By using Gen-AI and other AI tools thoughtfully and ethically, management educators can unlock their full potential and create a more effective and engaging learning experience for their students.

Collectively, this essay seeks to add to the ongoing dialogue in management education, as underscored in the Call for Papers for this Special Issue, regarding strategies to cultivate a digital mindset among management educators, advance technology literacy in our students, and contribute to preparing and molding the future of work (S. J. Allen, 2020; D. B. Allen et al., 2021). To address the opportunities and challenges associated with integrating generative AI into management education, this essay will proceed as follows: First, we provide background on what generative AI is and explain its capabilities using ChatGPT as an illustrative example. Next, we make the case for why management educators may want to embrace rather than resist the integration of generative AI into their courses. We then present a semester-long example course that incorporated generative AI through a series of experiential learning activities. In doing so, we illustrate how generative AI can be developed with andragogical methodology and principles in mind that enrich the learning process (Fornaciari & Lund Dean, 2014). Subsequently, we share survey and test results that reveal students’ overwhelmingly positive perceptions of our generative AI integration and improved performance on a standardized test. Following this, we engage in a discussion of the salient concerns associated with potential overreliance on generative AI, namely diminished critical thinking, lack of personal growth, and academic dishonesty. For each concern, we provide recommendations for mitigation strategies. Finally, we conclude by proposing avenues for future research related to long-term impact assessments, human-AI interaction, personalized learning, student wellbeing, best practices, and ongoing critical inquiry.

What Is Generative Artificial Intelligence (Gen-AI)

ChatGPT is built on the foundation of the Generative Pre-Trained Transformer 3 (GPT-3), a natural language processing (NLP) model employing deep learning techniques to predict subsequent words and sentences, thus generating text from scratch. Unlike simplistic models that might generate predictable responses, GPT-3 transcends this by crafting any probable response derived from its training data. It takes an input and generates a prediction based on the language patterns it has learned from its training set of 170 trillion parameters, which includes a diverse range of text sources from the internet. The model’s use of transformer architecture (Floridi & Chiriatti, 2020) enables it to adapt to various writing styles, from a Shakespearean sonnet to a technical report.

The unique aspect of Gen-AI, like ChatGPT, is that it allows students to interact directly with the AI, asking questions, seeking explanations, and even generating content. This direct interaction enables a more personalized and engaging learning experience. Students can guide their learning process, explore topics at their own pace, and receive immediate, tailored feedback. This is akin to having a personal tutor available at all times, ready to adapt to each student’s unique learning style and pace. By placing the power of AI directly into the hands of the students, Gen-AI opens up new possibilities for personalized and interactive learning experiences, fostering a more student-centered approach to education. Notably, while management education has seen the use of chatbots before (see S. J. Allen, 2020), the technological advancement in ChatGPT transcends previous technology by offering superior quality interactions at a lower cost, posing an immediate potential disruption to management education.

Drawing a parallel, the calculator’s advent marked a watershed moment in math education; similarly, Gen-AI (e.g., ChatGPT) signifies a substantial pivot in educational technology. Gen-AI, metaphorically termed a “language calculator,” is redefining management education. However, while calculators perform mathematical calculations, users still need foundational math knowledge to logically evaluate results. Similarly, Gen-AI has the ability to produce text that resembles human writing. However, students need a fundamental grasp of the topic to evaluate the output’s quality and credibility critically. The goal is not necessarily for all students to become AI experts, but rather to build core literacy to thoughtfully apply these emerging technologies. In the section that follows, we further elaborate on why management students ought to receive an education that increases their tech literacy.

Why Integrate Gen-AI Into Management Courses

“In medicine, law, finance, retailing, manufacturing, and even scientific discovery, the key to winning the race is not to compete against machines but to compete with machines.” —Brynjolfsson and McAfee (2012, p. 2)

Much of the current discourse about Gen-AI in the classroom is centered on the potential negative impacts of the tools in the classroom (e.g., Huang, 2023). For example, one author at a large public university was a panelist at a University level session about implementing Gen-AI in the classroom. They noted that the primary concerns were about academic integrity. Many faculty were generally skeptical of using Gen-AI in the classroom and focused on plagiarism detection. As many universities and educators are seeking to write policies and develop detection applications/software to deter the use of Gen-AI, we believe that the challenges of AI integration can be effectively addressed through thoughtful classroom design. This opens the door to significant enhancements in the educational experience. In this context, we invite management educators to explore the advantages that Gen-AI can offer at the institutional and course levels, especially given the Advance Collegiate Schools of Business’s (AACSB) emphasis on technological agility.

In 2020, the AACSB International introduced a business accreditation standard on curriculum, known as standard 4.1:

“The school delivers content that is current, relevant, forward-looking, globally-oriented, aligned with program competency goals, and consistent with its mission, strategies, and expected outcomes. The curriculum content cultivates agility with current and emerging technologies.” (AACSB International, 2020)

In line with this standard, business schools are required to prioritize the development of their students’ technological agility. This preparation equips them to adapt to the ever-evolving landscape of emerging technologies, both now and in the future (AACSB International, 2020). While it is not expected for business students to be technology experts, it is crucial for them to possess a strong comprehension of the technologies that will significantly impact their prospective roles as employees, managers, and leaders (S. J. Allen, 2020; D. B. Allen et al., 2021; Bagranoff & Bryant, 2020; Brynjolfsson & McAfee, 2012).

Presently, individual businesses and entire industries are undergoing a rapid surge in the practicality and applicability of Gen-AI, leading to its widespread adoption as an aid to streamlining business processes (Berg et al., 2023; King, 2022). Kemp (2023) argues that by integrating AI in the firm’s experiential, relational, and strategic systems (i.e., situating AI), firms can cultivate AI-driven capabilities, laying the groundwork for AI-driven competitive advantages. Furthermore, Berg et al. (2023) highlight that the introduction of Gen AI, as opposed to discriminative AI (e.g., classification and prediction tasks), has broadened the scope of uses for AI within organizations. They further note that, “For generative AI, because the potential uses are virtually limitless and open-ended, there may be more of a premium for creativity and the ability to identify how to use these tools well” (p. 7). Thus, management researchers at the frontier of AI have indicated that students will be tasked with the challenge of aiding or leading organizational efforts to continuously update and adapt their AI capabilities in creative ways in order to remain competitive and valuable in the future.

With the integration of Gen-AI into management courses, students will have the opportunity to develop the necessary technological agility, critical thinking, and problem-solving skills to navigate the complexities of integrating Gen-AI into business processes. Management courses that prioritize Gen-AI education can empower students to become forward-thinking professionals capable of using Gen-AI to drive organizational success. Thus, at the institutional level, the integration of Gen-AI is consistent with the espoused mandates from AACSB (AACSB International, 2020).

Course Level Considerations: Andragogy and Gen-AI

At the course level, integrating Gen-AI into management courses is consistent with the call for management educators to move from pedagogy to andragogy (e.g., Fornaciari & Lund Dean, 2014; Forrest & Peterson, 2006). Andragogy acknowledges that adult learners have their own unique set of experiences, assumptions, and views toward their learning (Knowles, 1968). Andragogy proposes six learning assumptions of adult learners (Forrest & Peterson, 2006, p. 116):

Adults have a self-concept of a self-reciting personality;

Adults bring a wealth of experience to the learning process;

Adults come to the learning process ready to learn;

Adults are oriented toward the immediate application of learned knowledge;

Adults need to know the reasons for learning something; and

Adults are driven by intrinsic motivation to learn.

Implementing Gen-AI into the classroom aligns with andragogy by empowering learners to take ownership of their learning, engage in problem-solving, receive personalized instruction, and pursue lifelong learning consistent with changes in technology. The integration of Gen-AI can enhance the learning experience by providing adaptive, interactive, and relevant learning opportunities. Gen-AI is truly a democratized technology.

In addition integrating Gen-AI into management education can also foster an inclusive classroom. Particularly since students in management education come from a diverse range of backgrounds, language abilities, and socio-economic statuses. However, AI can provide opportunities to increase inclusion and provide tools for students needing accommodations (Harklau et al., 1999; Schleppegrell & O’Hallaron, 2011). For instance, students with language disabilities, non-native English speakers, or those who received less comprehensive English education, due to socio-economic constraints, may underperform on writing tasks, despite the quality of their ideas (Connelly et al., 2006; Lam & Tong, 2021). This is particularly problematic in management education, where the quality of students’ ideas, such as strategic and critical thinking and decision-making, is often the primary focus.

Gen-AI technology, like ChatGPT, can serve as a valuable supplement to traditional teaching methods by equalizing language proficiency barriers. This allows educators to devote more attention to the nuances of students’ ideas, rather than being preoccupied with language limitations. While the primary role of breaking down complex ideas for better understanding remains with the educator, Gen-AI can offer additional support by making these concepts more accessible. This is particularly beneficial for students who may need extra help outside of classroom hours. Moreover, Gen-AI’s ability to translate content into various languages can further foster an inclusive environment for non-native speakers.

Taken together, the integration of Gen-AI into management education not only aligns with the mandates from AACSB and the shift from pedagogy to andragogy (Forrest & Peterson, 2006), but also promotes an inclusive classroom. However, the use of these tools without the proper guidance and curriculum design may promote passive and ineffective use of the tools which potentially leads to the proliferation of a generation of management students who know about Gen-AI but are unfamiliar with how to use it to augment their abilities rather than substitute for them. Our purpose, therefore, is to explain how management educators can utilize this transformative tool to enhance learning outcomes and foster an inclusive learning environment. In the section that follows, we provide an example of a semester-long management course that integrated Gen-AI by aligning Gen-AI specific objectives with andragogical instructional strategies.

An Example of a Semester Long Course Using Gen-AI

“I loved the experience and would recommend other professors incorporate AI in their lessons. I think AI is the future and we shouldn’t be in the dark when it starts to take white collar jobs. Instead, the industry will be made of those who can manipulate and use AI to manage the rest of everyone.”—Student

In the semester following ChatGPT’s release, one of the authors incorporated Gen-AI into weekly class activities to investigate the influence of artificial intelligence on management education. OpenAI’s GPT-3 served as the primary Gen-AI tool due to its centrality in the rapid adoption of Gen-AI (Berg et al., 2023). However, other Gen-AI tools were used (e.g., Poe) to complete various class activities. These AI-facilitated activities spanned a diverse range of topics, including interactive analyses such as the PESTLE analysis and AI generated cases. A few examples of these activities can be seen below (Figures 1 –3):

Figure 1.

Pestle analysis guide.

Figure 2.

Porter’s five forces analysis guide.

Figure 3.

Ethical dilemma case.

The primary purpose of the integration of Gen-AI in the class was to assess the full implementation of Gen-AI as a teaching tool for management educators. We also wanted to illustrate that the implementation of Gen-AI in management education is consistent with our increasing recognition of adopting andragogical approaches to course and activity designs (Dachner & Polin, 2016; Fornaciari & Lund Dean, 2014; Forrest & Peterson, 2006). Thus, Table 1 illustrates our objectives for developing and applying Gen-AI activities to focus areas of andragogy, guidance for implementation, and examples of student feedback related to the focus area. Below is a brief description of the Gen-AI specific objectives we developed to help guide our curriculum development for the use of Gen-AI in management courses (Table 2).

Table 1.

Instructional Strategy, Objectives, Guidance, and Student Feedback.

Instructional strategy of andragogy (Dachner & Polin, 2016)	Gen-AI objectives	Guidance for implementing Gen-AI	Student feedback
Self-Concept: Many students are still working on their self-concept. These include concepts such as goals, values, strengths, weaknesses, and readiness to be self-directed in their learning.	Clarification of AI’s Role in Augmenting Student’s Knowledge, Skills, and Abilities Academic Integrity Expectations Instant Feedback Promotion of Collaborative Learning	Here we focused on clarifying that the use of Gen-AI in the classroom is to augment their knowledge, skills, and abilities rather than to simply substitute. Additionally, we recommend clarifying academic integrity expectations. Our goal was to present learners with the opportunity to recognize that their goal is to become effective users of an effective tool and to use the tools with integrity.	“It showed me how I can use it to advance my learning and help in situations where I didn’t understand things taught in class fully.” “For the most part, it was pretty accurate, and as long as the user verifies the information given, it’s extremely helpful.” “I really would’ve loved to use AI more than we did. I think learning intricate details of using AI will help set students apart from others.”
Work Experience: Work experience varies. However, activities can be designed to leverage current work experience and provide work experience in the classroom.	Integration of Real-World Scenarios	Instructors will want to move beyond the overall acknowledgement that using Gen-AI itself simulates work experience (although, that should always be reinforced). When developing activities, make sure that students are becoming familiar with the variety of ways Gen-AI can be used to accomplish tasks related to the course content and practice. For example, ChatGPT isn’t simply an autocomplete writing tool.	“Very positive due to the fact that we will all be using it very soon, if you are not familiar with it you will fall behind.” “In my job I use AI to code certain things for me but I don’t rely too heavily on it.” “AI is such a new technology and as we are now moving into the workforce it is important to know how to use AI.”
Readiness to learn: Learners will be particularly engaged and ready to learn when they recognize the relevance/applicability of their content to their current non-student roles and responsibilities.	Effective Tool Use	When doing the initial demonstration, focus on the application of Gen-AI to everyday life outside of academics. Here, instructors want to move even beyond the usefulness in the workplace which is part of our framing above. Instructors want to also be mindful to include the usefulness for other tasks and decision-making such as recipes with current ingredients, date nights, drafting e-mails, etc.	“Find any information that you may want to learn about.” “I use it at work to create outlines or to help with my Spanish.” “It will be a huge part of our future so getting a head start on how to use it and different sources of AI was extremely helpful.”
Orientation to learning: Adult learners are problem-focused and want to be able to immediately apply what they’ve learned.	Experiential Application of Content Stimulating Creative Problem Solving	Activities using Gen-AI will inherently be immediately applicable. However, it is important for educators to make sure the activity is problem-focused. Dachner and Polin (2016) recommend using semester-long projects but a course designed with a series of experiential Gen-AI activities can have the same effect (e.g., real-world scenarios). That is, students are immediately applying Gen-AI to a variety of scenarios.	“It was great to run simulations and see the different variations.” “Very effective for learning. I had never heard of this before this class.”
Need to Know: Adult learners need to know what they will learn in the course/activity, how they learn it, why.	Exploration of Emerging Technologies	At the time when instructors explain the course overview, instructors should further explain how Gen-AI will be implemented in the course to facilitate the learning of the content (the what), and why Gen-AI will be implemented (e.g., AACSB and Workforce KSAs). This helps learners understand “the why” they need to know both the course content and Gen-AI.	“AI is now going to be such a relevant part of our life and learning in this class helped me understand its uses and benefits.” “I think learning intricate details of using AI will help set students apart from others. Not because of cheating, but because of using resources that everyone will soon be incorporating in their businesses.”
Motivation to Learn: Adult learners are intrinsically motivated by understanding the relevance and applicability of their learning to their personal development, and career advancement.	Fostering Student Autonomy	Instructors would benefit from using Gen-AI in both low-stakes and high-stakes assignments. However, low-stake assignments/activities allow students to focus more on utilizing Gen-AI and learning (intrinsic motivation) rather than focusing on completing the task to perform well in the class (extrinsic). Creating an autonomy-supportive classroom is important and can include providing student-choice within the activities/assignments used (see the examples provided in this article).	“I have used AI to start coding and to structure presentations. I think it has been extremely useful and exciting to play with the new features.” “I think it was easier to find information with.” “I believe it was effective because these tools will be helpful in the future as the world moves into AI-integrated systems.”

Table 2.

Survey Results.

Item	Finding
On a scale of 1 to 5, how helpful did you find the AI-related activities in supporting your learning during the semester? (1 = Not helpful at all, 5 = Extremely helpful)	M = 4.59, SD = 0.53, Helpful or Extremely Helpful = 98.3%
On a scale of 1-5, how likely are you to recommend incorporating AI-related activities, such as ChatGPT, in other classes or academic settings? (1 = Not helpful at all, 5 = Extremely helpful).	M = 4.55, SD = 0.70, Likely or Extremely Likely = 96.5%
In your opinion, was ChatGPT an effective teaching aid or more of a distraction? Please explain your answer.	Effective = 50, Distraction = 0, Both = 3
Are you using AI in other aspects of your life outside the classroom? If so, please provide examples.	AI Outside Class = 37, Not Using = 13, Plan To = 2
Overall, do you believe the AI-related activities had a positive or negative impact on your learning experience this semester? Please explain your answer.	Positive = 50, Not Sure = 1 Neutral = 1, Negative = 1

1. Fostering Student Autonomy: Utilize generative AI as a facilitator, offering resources and pathways to encourage independent exploration of the subject matter.

2. Effective Tool Use: Provide comprehensive guidelines and exemplars to illustrate how AI can be harnessed to enrich the learning process.

3. Clarification of AI’s Role: Emphasize AI as a supplemental tool to augment students’ capabilities, not as a substitute for their critical thinking and problem-solving skills.

4. Academic Integrity Expectations: Clearly delineate the ethical boundaries of AI usage within the academic environment, ensuring transparency, and upholding scholarly standards.

5. Promotion of Collaborative Learning: Leverage AI’s capabilities to foster collaborative learning opportunities, encouraging knowledge exchange, and interpersonal interaction.

6. Integration of Real-World Scenarios: Employ AI to present current business scenarios and global trends, facilitating the practical application of theoretical knowledge.

7. Instant Feedback: Use AI to provide immediate, personalized feedback on student work, promoting a culture of continuous improvement and reflective learning.

8. Stimulating Creative Problem Solving: Harness AI to expose students to intricate business challenges, stimulating innovative thinking, and strategic solution development.

9. Exploration of Emerging Technologies: Incorporate modules that introduce nascent technologies, challenging students to devise strategic implementations within business contexts, thereby priming them for a technology-driven business landscape.

Findings From the Semester Long Using Gen-AI

Student Survey

“I think a class can become irrelevant if they don’t adapt (AI) into some college courses.”—Student

To understand student attitudes toward our AI-based teaching approach, we surveyed the students in the Spring 2023 AI-integrated sections, 58 participated. The survey didn’t target specific course learning outcomes; instead, it focused on student perceptions of AI activities. Students rated the activities’ effectiveness and their likelihood to recommend AI tools like ChatGPT for use in other classes. Ratings spanned from 1 (“Not helpful at all”) to 5 (“Extremely helpful”). Additionally, we included open-ended questions, which the table below details.

The student response to the use of Gen-AI as a teaching aid was overwhelmingly positive, with a favorable average rating of 4.59 (SD = 0.53). Insights from open-ended survey questions revealed that students found the tool effective for several reasons. They cited easy access to information, simplified complex concepts, diverse perspectives, and a better understanding of AI as key benefits. Notably, no student labeled the Gen-AI activities as unhelpful, underscoring unanimous agreement on Gen-AI’s positive impact on learning. Students further elaborated on how Gen-AI activities made the learning process both enjoyable and efficient. As one student put it, AI was both “fun to learn” and a significant convenience factor, making life and the learning process easier. Another student highlighted the efficiency boost that AI provides, appreciating how using Gen-AI “cut a lot of research time,” indicating that AI tools serve as more than mere aids, they play the role of catalysts in streamlining the learning process.

When asked about the potential to expand AI-related activities into other academic settings, students responded favorably, with a mean score of 4.55 (SD = 0.7). Their recommendation, grounded in personal experience, emphasizes the effectiveness of AI in education and promotes its wider acceptance. They also recognized Gen-AI as a democratizing force in education, capable of enabling a wider community to access a wealth of information and insights. One student’s comment, “It provided a lot of great starting points to begin research,” underscores how AI tools are simplifying the research process and making learning more widely accessible.

Many students identified how the use of Gen-AI extended beyond the classroom. As one said, “Gen-AI was an effective teaching aid not only inside the classroom but outside of the classroom as well.” They found that knowledge of AI tools gave them an advantage over their peers, an insight echoed in the sentiment, “I feel like I have a leg up on my peers in knowing how to manipulate information to get what I need from an AI.” The majority, 68% of students, actively used AI in daily life and professional contexts, emphasizing the relevance of acquired AI skills in real-world scenarios.

Despite the predominant positivity toward AI-assisted learning, some students expressed more nuanced views on its application and potential misuse. They noted the possible pitfalls of such technology, particularly its potential to encourage complacency or overreliance among users. One stated, “There is the problem of it creating laziness” and another student candidly confessed to overdependence on the AI tool, admitting, “I don’t do my own work now.” This student’s admission brings a stark reminder that the line between augmentation of learning and complete dependency can blur easily, and points to the critical need for educators to ensure that AI tools are used to complement, not replace, human effort and intelligence in the learning process. In the discussion that follows, we address some of the concerns students expressed and that we have encountered implementing Gen-AI.

Standardized Exam Performance

To assess the impact of generative AI on student learning, we analyzed exam scores from a 50-question standardized test given at the end of strategic management capstone courses. We compared two sets of scores: one from students in the Fall 2021 and 2022 semesters (n = 36) without AI activities, and another from students in two sections of the same course in Spring 2023 (n = 71) with AI activities. A single professor taught all courses.

The average score for students in the traditional classroom was 33.82 (SD = 5.33), while the average score was 36.21 (SD = 6.32) for those with AI activities. The results from an independent sample t-test suggest that this difference was statistically significant, t (131) = -2.06, p = .043. This suggests that integrating generative AI activities into the strategic management capstone course positively impacted student performance on a standardized exam.

Discussion

“I think the biggest thing is the concern of students solely relying on this software and not being made aware of the trade-offs using it comes with.”—Student

With the emergence of any new technology, there are inevitably associated concerns and risks, and Gen-AI is no exception. At the outset of this essay, we posited that one of the most salient risks associated with Gen-AI is that it may be a useful tool that ultimately creates useless students (Fügener et al., 2022). Thus, the primary goal and contribution of this essay was to develop a framework to combat that potential future misuse. In doing so, we put forth nine objectives for using Gen-AI in management education. Additionally, we integrated these objectives with the six andragogical principles to provide guidance for management educators who want to adopt a digital mindset and increase tech literacy in the classroom (S. J. Allen, 2020). Finally, we illustrated the effectiveness of the framework by collecting data on a strategic management course that implemented Gen-AI into its course design.

However, based on our experience and student feedback, there remains an overarching concern for students potentially becoming overly reliant on Gen-AI. Over-reliance on Gen-AI poses significant risks that need careful consideration due to its potential negative consequences for students. As such, in this section, we will focus our discussion on the three areas related to ours and our students’ concerns regarding the overreliance of Gen-AI: (1) diminished critical thinking skills, (2) lack of personal growth and development, and (3) the potential for academic dishonesty. The concerns mentioned here are not the sole concerns associated with integrating Gen-AI technology, like ChatGPT, into management classes. Nonetheless, we have chosen to address these three concerns as we believe they are particularly significant and are often the primary sources of resistance for management educators to fully embrace Gen-AI in the classroom.

Diminished Critical Thinking Skills

Over-reliance on Gen-AI risks diminishing students’ critical thinking skills, essential for analyzing complex problems and evaluating diverse perspectives. For instance, in case assignments demanding strategic solutions, some students might solely depend on Gen-AI’s suggestions. Such dependence can result in shallow, unoriginal responses that lack broader context. During class discussions, these students may falter when peers challenge them with alternative views or conflicting evidence. This can be counterproductive since management classes aim to cultivate critical thinking skills, and students that excessively depend on Gen-AI may undermine this goal (Kooli, 2023; Powley & Taylor, 2014).

Our concern aligns with findings from Dell’Acqua et al. (2023), which identified a “jagged technological frontier” in AI capabilities. While AI significantly enhances productivity and quality in specific tasks, it falls short in others that seem equally complex. The study warns against “unengaged interaction with AI,” where users blindly adopt AI output without scrutiny. Their findings underscore the importance of sustaining cognitive effort and expert judgment when working with AI. Therefore, students who lean too heavily on Gen-AI may struggle to critically evaluate and defend their arguments. Furthermore, unengaged interactions limit students’ ability to hone their own analytical and reasoning skills (Perera & Lankathilaka, 2023b).

To mitigate this concern, educators can implement strategies that encourage critical thinking and independent analysis. One such strategy is to incorporate assignments that require students to not only present their solutions but also explain the reasoning behind their decisions. This could involve asking students to provide a critique of the Gen-AI’s suggestions, identifying its strengths and weaknesses, and explaining why they chose to follow or deviate from its recommendations.

In one of the author’s class activities, students were divided into teams and were asked to debate against each other—forcing students to defend their perspectives against alternative viewpoints (including arguments from the AI). This required students to think critically about their arguments and the counter arguments presented, promoting a deeper understanding of the subject matter. The use of Gen-AI in this way can also be helpful when approaching teaching controversial topics (see S. Allen, 2022).

Lack of Personal Growth and Development

A college education is widely recognized as a transformative experience that goes beyond the mere acquisition of knowledge (Paul & Quiggin, 2020). While learning specific subject matter is certainly an important aspect of college, the value of higher education lies in its ability to foster personal growth and development in students (Wilcox, 1996). Higher education provides a unique environment for individuals to explore their own ideas, challenge established knowledge, and develop their own perspectives on various topics. Through critical thinking, discussions, debates, and interactions with professors and peers, students learn to articulate their thoughts, defend their positions, and engage in constructive intellectual discourse (Cotton et al., 2023; Dwivedi et al., 2023). When students rely heavily on Gen-AI for solutions to thought-provoking questions, they may inadvertently hinder their own personal growth and development. Hence, by constantly relying on Gen-AI for solutions, students may miss out on the opportunity to grapple with complex problems, engage in independent research, and form their own unique insights.

To address this concern, educators can adopt a guided approach to the use of Gen-AI in the classroom, ensuring that it complements rather than replaces the learning process. Gen-AI can be used as a tool for exploration and discovery, rather than a source of definitive answers. For instance, students can be encouraged to use Gen-AI to gather information, generate ideas, or explore different perspectives on a topic. However, the critical analysis, synthesis of information, and formation of unique insights should be tasks that students undertake independently.

Additionally, fostering a strong self-concept in students is crucial (Clapp-Smith et al., 2019). As we noted in Table 1, educators can encourage students to view themselves as active participants in their own learning journey, emphasizing the value of their unique insights and perspectives. This can be achieved by creating a learning environment that values and rewards original thinking and problem-solving, thereby discouraging over-reliance on Gen-AI (Alqahtani et al., 2023). It is important, then, to shift the students from using Gen-AI to get a grade to using Gen-AI to acquire knowledge, skills, and abilities that will serve them in the future.

Academic Dishonesty

While Gen-AI can be a valuable tool, it also carries the risk of abuse. Its accessibility and convenience may entice certain students to engage in academic dishonesty (Sullivan et al., 2023). For instance, they might exploit Gen-AI to plagiarize content by rewording or paraphrasing someone else’s work and claiming it as their own original written words. Moreover, students could use Gen-AI to effortlessly produce well-crafted responses to exam questions or even compose entire essays. In a survey given to over 1,000 students, it was found that one-third of those students used ChatGPT on an assessment task (75% of those students knew it was considered cheating and still chose to do so; Cassidy, 2023). Such widespread academic misconduct can have severe consequences for both the students involved and the educational institution they attend (Perry, 2010). Not only is it ethically questionable, but it can also undermine students’ grasp of the course material, resulting in a diminished quality of education. Gen-AI may presently alleviate some of the academic stressors in students’ lives, however, an excessive dependence on this technology has the potential to adversely impact them in the future (Amzalag et al., 2021). Specifically, academic dishonesty hinders the cultivation of positive virtues such as honesty and fairness, while also being linked to additional detrimental behaviors that extend beyond the confines of academia (Krou et al., 2021).

To prevent misconduct, educators can create an environment focused on learning rather than grades (Cressey, 1953). This involves creating an academic environment that emphasizes learning and understanding over grades and performance. This may include emphasizing low stakes assessments and implementing formative feedback strategies/assessments. For example, giving students opportunities to revise their work based on feedback from the instructor provides them an opportunity to focus on the learning process rather than the pressure of high stakes summative assessments. By shifting the focus from grades to the learning process, educators can reduce the pressure students may feel to resort to dishonest practices (McCabe et al., 2001). Finally, clearly communicating rules about AI use and misuse is critical for student success. Hence it is imperative to this information within the course syllabus. For example:

In this course, we will have sanctioned Gen-AI activities as well as activities that require individual thought and consideration. Using Gen-AI during non-AI activities is considered cheating and will result in __________ (insert punishment here).

Future Research and Direction

Long-Term Impact Assessment

The prevalence of Gen-AI in management education necessitates longitudinal studies to evaluate its long-term impact on student learning outcomes and career development. This assessment allows for an examination of its effectiveness in improving knowledge retention, critical thinking, problem-solving skills, and on-the-job productivity and performance (Rowland, 2023). By identifying trends and patterns over time, researchers can provide a more accurate assessment of the overall effectiveness and potential limitations of Gen-AI integration. Furthermore, long-term impact assessment can explore the influence of Gen-AI exposure on students’ career advancement, employability, and ability to adapt to emerging trends in the management field. This evaluation is crucial for uncovering the sustained effects of Gen-AI, informing management departments about its benefits, and guiding the responsible adoption of Gen-AI technologies in education.

Personalized Learning Experiences

Generative AI presents a notable opportunity for crafting personalized learning experiences in management education. To unlock this capability, further research is needed to determine the most effective strategies for leveraging AI to tailor educational content to individual learning styles, preferences, and abilities. By doing so, Gen-AI can create customized and dynamic learning environments that optimize engagement and knowledge acquisition (Burney et al., 2023). Additionally, research can delve into the ramifications of personalized learning experiences enabled by Gen-AI, including how students interact with AI-generated content and how these experiences impact overall learning outcomes, even in collaborative environments (Stahl et al., 2006). Such research can markedly bolster student motivation, engagement, and learning outcomes in management education. By employing AI technology to adapt educational content, management professors can establish dynamic, customized learning environments that propel optimal student development and success.

Student Well-Being and Dependency

As AI continues to permeate educational settings, it is crucial to understand and assess its potential impact on student well-being and the risk of over-reliance. Future research could explore the psychological and social repercussions of excessive AI-dependence, examining its effect on student motivation, critical thinking, and self-directed learning. This inquiry can highlight the pitfalls of AI over-reliance and inform strategies promoting balanced AI usage in educational settings. Research can examine the potential consequences of students relying heavily on AI technologies, like diminished self-confidence, creativity, engagement, initiative, or problem-solving skills (Kooli, 2023). Investigating the psychological factors affecting student engagement and learning outcomes amid AI integration can help devise interventions to curb potential adverse effects. Additionally, exploring the social implications of AI dependence, such as its impact on collaboration, teamwork, and interpersonal communication skills, can contribute to a holistic understanding of the consequences of excessive reliance on AI in management education. By doing so, management education can be a fertile ground for preparing business students for a future integrated with Gen-AI (Perera & Lankathilaka, 2023a).

Best Practices

Supporting educators in integrating AI-powered tools into teaching practices is essential as AI technology evolves. This is particularly the case since management educators may be both unfamiliar with technologies, such as ChatGPT, and grossly underprepared to integrate such technologies into their classrooms (S. J. Allen, 2020; Zhao & Frank, 2003). Providing robust support could alleviate some of the concerns educators have about the potential adverse impact Gen-AI may have on various assessments (Eke, 2023). This essay serves as a starting point for the conversation about best practices for introducing Gen-AI in management education. Future research can play a pivotal role in designing and implementing effective professional development programs that equip teachers with the necessary knowledge, skills, and andragogy strategies to leverage AI technologies in their classrooms. These programs can be tailored to educators’ unique needs, providing a comprehensive understanding of AI concepts and applications relevant to management education. Research can evaluate program effectiveness by collecting feedback from teachers and analyzing their experiences, informing program refinement. Additionally, studying the outcomes of these programs on student learning and engagement can provide valuable insights into the benefits and challenges of integrating AI technologies in management classrooms. By empowering educators through research-driven professional development, the effective use of AI can enhance teaching practices and promote meaningful student outcomes in management education (Burney et al., 2023).

Conclusion

“AI in the general public has negative connotations mostly because people don’t truly understand it. This class helped me develop a better understanding for AI and showed me that it could be a tool that we should adapt to and use..”—Student

The overarching goal of this essay is to foster a reflective and forward-looking dialogue on harnessing the potential of AI to enrich management education while navigating its potential pitfalls. By shedding light on the transformative capabilities of Gen-AI and providing strategies for responsible implementation, we aim to inspire educators, administrators, and policymakers to embrace AI as a valuable tool in management education. Through careful consideration and a collaborative approach, we can leverage the power of AI to enhance learning outcomes, empower students, and shape a more innovative and inclusive future for management education. Therefore, as management educators, it may prove beneficial for us not to fear the integration of Gen-AI into our classrooms, but embrace the usefulness of Gen-AI as another tool we can use to educate our business leaders of tomorrow (Fischer & Dobbins, 2023).

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

This article is part of the Special Issue, “From Taylor to Tableau: Technology as a tool, topic, and differentiator in management education.”

ORCID iDs

Steven J. Hyde

Antoine Busby

Robert L. Bonner

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