AI is shaking up business education far beyond just how students learn. From research to school operations, its impact is growing fast. In this piece, Toby Roe, co-founder of Roe Communications, speaks with three AI experts from leading business schools to explore how AI is reshaping the future of the industry.

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Much has been written about AI in business education from its transformative benefits to fears about it undermining the very essence of higher education. For a large part, the existing debate has been centred around AI’s effect on student learning, but its influence goes much deeper. It has the potential to alter many aspects of business education from research to the daily operation of business schools.

Toby Roe, Co-founder of PR consultancy, Roe Communications brought together three AI experts from different business schools to look at where we are as a sector and what AI really means for business schools over the next few years.

• Professor Pinnaree Tea-makorn is the AI Strategist at Sasin School of Management, Thailand.
• Professor Dejan Glavas is the Director of the AI for Sustainability Institute at ESSCA School of Management, France.
• Professor Oguz Acar is the Head of Generative AI at King’s Business School, UK.

Toby: Perhaps we could start with the subject of business school teaching and Artificial Intelligence. In particular, how do you think faculty can be helped to integrate AI into their teaching practice, without compromising their pedagogical autonomy?

Oguz: It’s a crucial point. We need to help faculty integrate AI through a supportive framework that respects their autonomy and expertise. AI doesn’t have to interfere with how faculty teach—when used thoughtfully, it can be a powerful tool to enhance their approach. We want to avoid a strict, top-down approach that dictates exactly how to use AI. This can feel limiting and stifle a faculty’s ability to shape their teaching. At the same time, we don’t want faculty to ignore AI altogether, from outdated assumptions, this risks depriving students of valuable learning experiences and skills.

Pinnaree: I’d agree. Its essential for business schools to be including AI training for faculty so that they understand the implications for their classes and students. It’s useful to have workshops where faculty can share with one another how they are integrating AI into teaching. While schools should have recommended AI policies, an element of faculty autonomy is vital. Every class is different, and it should be the faculty deciding how to best use AI.

Dejan: I would add that AI developments are moving incredibly quickly, and so it’s key to help faculty keep updated on AI advancements—through industry news, research, and training sessions. That way you can be informed without feeling pressure to adopt specific methods. We recently conducted an AI research barometer amongst four hundred European companies with our partner Forvis Mazars. An approach highlighted in the research is ‘test-and-learn’ where companies adapt AI to their specific needs and industry context. It is a good approach for business schools to follow.

Oguz: Yes, it is about equipping faculty with the skills and knowledge to use AI confidently. If we can help them understand what AI can (and can’t) do, they will be better positioned to make choices about where and how AI can best serve their own teaching goals.

Toby: Sticking with the topic of teaching, or rather the other side – student learning. A common concern is how AI can detract from (or contribute to) the development of critical thinking and problem-solving skills? What are your views on this?

Dejan: There are potential risks. Studies show that excessive reliance on AI can lead to reduced cognitive engagement and weaker reasoning abilities among students. We need to be careful about the way we integrate AI to avoid creating dependency that could impair students’ ability to develop analytical capabilities.

However, when implemented thoughtfully, AI can enhance critical thinking by automating routine tasks and creating new opportunities for deeper analysis. The key lies in using it as a ‘process tool’ not an ‘answer tool’.  We can realise the benefits through strategies such as using AI-generated content as material for critical evaluation.

Pinnaree: Yes, AI can do both, depending on how we use it. The technology can reduce the time it takes us to complete tasks enabling students and faculty to focus more on critical thinking and strategic decision-making. It can also be used as a tool to develop critical thinking by leveraging complex analysis through machine learning or interacting with GenAI chatbots. However, negligent use of AI can result in students circumventing critical thinking, analysis, and problem-solving, consequently detracting from the development of those skills.

Oguz: It certainly is a double-edged sword. Positive examples are assignments that ask students to identify AI confabulations, like inaccurate or inappropriate outputs. Or an assignment where students generate AI-created ads and evaluate their limitations from a brand image perspective. These can sharpen their critical thinking.

The key is to promote responsible, effective use of AI, keeping human insight, creativity, and agency at the centre. At King’s we use the PAIR framework—Problem, AI, Interaction, and Reflection. It helps educators thoughtfully integrate GenAI into their curricula and guides students to engage critically with it. Students begin by defining the Problem to set context and scope. Next, they identify AI tools useful for analysis. In the Interaction phase, they experiment with these tools, questioning and evaluating outputs. Finally, in Reflection, they assess how AI helped or hindered their problem-solving and consider its broader implications.

Toby: In a similar vein, what are your thoughts and concerns on how AI may affect the development of uniquely human skills like empathy and leadership?

Pinnaree: Again, overreliance on AI will reduce the opportunity to hone those skills. It really is that simple and as business educators we have an incredible responsibility to find a balance in using AI.

On a positive note, some of the AI tools can be helpful in supporting us humans with the development of skills such as empathy and leadership. At Sasin, the technology enables role-play scenarios where students can interact in various situations in real-time and can provide insights from data that help us understand various factors that contribute to these skills.

Dejan: Absolutely, skills like empathy can be supported by AI tools that simulate scenarios allowing students to practice perspective-taking and ethical decision-making within controlled environments.

In leadership development, AI is going to reshape traditional approaches by requiring students to build AI literacy and ethical awareness. Future leaders need to understand human-AI systems and how they influence team dynamics, ethics, and organisational culture.

I echo the point about our responsibility. Business education needs to emphasise responsible AI use by preparing students to make principled decisions that consider biases and potential negative consequences.

Oguz: We need to strike a balance here, keeping the essential human aspect in education while leveraging AI’s capabilities. Role plays and simulations are great as you can explore tricky topics such as negotiation or conflict resolution. But, if AI replaces most of the human interactions in class, students will become detached from the interpersonal, nuanced aspects of leadership and empathy. As such, they may miss building the emotional intelligence essential to be an effective leader.

Toby: Balance is clearly the key in the classroom. Looking beyond teaching and learning into the jobs market, what are the key ways we need to help prepare students for roles in AI-driven industries.

Oguz: We need to bring AI tools directly into the classroom and let students experiment with them in their specific fields. GenAI is set to impact most knowledge work, so students need to understand not only what these tools can (and can’t) do, but also how to use them effectively in different domains.

Practically, it means embedding AI projects and tools into coursework to give students first-hand experience with real-world problem-solving. For example, developing a functional app prototype as an assignment, applying both AI skills and industry-specific knowledge.

The whole world is trying to figure out what these tools mean across a wide range of fields. By building both AI literacy and domain-specific skills, and hands-on experience in solving problems, students can be ready to contribute meaningful insights and solutions.

Dejan: A general understanding of AI and an interdisciplinary approach is important. Schools can develop core courses in AI, machine learning, and data analytics to provide a foundational understanding of these technologies. An interdisciplinary approach that combines traditional business subjects with AI applications helps students see how AI is transforming functions like marketing, finance, and operations. This integration shows the practical applications of AI across business contexts, giving students a clearer sense of its potential impact.

Pinnaree: Fundamentally, an introduction to AI should be a required class for every student, regardless of their subject. We all need to understand the concept of AI, how it works, how to effectively use it, and the social and ethical implications that may require change from current practice. It is a technology that touches most industry sectors, so entering almost any job means you will be interacting with AI. A key role for business schools is to help students with their mindset. They are entering an AI-driven world, and they need a certain level of understanding, which should breed confidence, to survive and thrive.

Dejan: I would add that an understanding of AI and ethics is vital. We need to help students understand the importance of transparent, fair, and accountable AI, equipping them to implement responsible AI practices in companies and organisations. We can also create partnerships with technology companies, bringing in guest lecturers and real-world internship opportunities to help students gain practical experience in those industries that already use AI intensively.

Toby: You all speak about the widespread adoption of AI. With that in mind, what is the potential for AI to widen and democratise access to high-quality business education?

Dejan: In our AI barometer, education ranks among the top hoped-for advances from AI in the next 20 years, suggesting broad recognition of AI’s transformative potential in this space. It is a noble aim, and AI has significant potential to open up educational opportunities through personalised, flexible, and more affordable learning options. Through AI-powered platforms, education can be customised to fit individual learning styles and goals, while features like automated feedback, language translation, and accessibility tools can help reach diverse global audiences regardless of location or background.

Crucially though, the AI barometer revealed an issue within companies that may affect business schools – less than a third of companies feel well-prepared to manage AI-related risks and disruptions, suggesting the need for robust frameworks to address concerns around data privacy, algorithmic bias, and equitable access. The challenge for us all is thoughtfully implementing AI solutions that expand access while maintaining educational quality and addressing these challenges.

In our AI barometer, education ranks among the top hoped-for advances from AI in the next 20 years, suggesting broad recognition of AI’s transformative potential in this space.

Pinnaree: Certainly, the internet democratised access to static content and live interaction, and AI offers immense potential for scalable and automated interactive content. For example, one could create a large language model (LLM) based on a famous lecturer and replicate their experience and insights to interact with individual students, no matter when or where they are. The potential of AI to shake up business education globally is there.

Oguz: One of AI’s greatest potentials is its ability to reduce costs and massively increase scale. It should allow educators to implement effective teaching practices that are traditionally costly in terms of time and resources, meaning business schools can reach a broader audience without necessarily compromising on standards. For example, providing detailed feedback is crucial for student growth, but it becomes harder to manage as class sizes increase. GenAI can help with this by delivering personalised, high-quality feedback at scale.

In a recent study, researchers developed a web application based on foundational LLMs to generate quantitative and qualitative feedback on marketing analytics assignments. Across three empirical studies, the results showed that the app’s scores closely matched human evaluators, its feedback was factually accurate and helpful, and students rated it highly for ease of use and learning benefits.

Similarly, GenAI makes it much easier to create fresh, relevant case discussions for each class, tailored to specific learning goals. Faculty could use AI to produce video lectures or offer guidance through avatars—or even create AI replicas of themselves to support large groups of students simultaneously.

Toby: It’s exciting, and I guess time will tell how much business schools can use AI to open up learning, with much depending on the systems and structures of any given institution. Turning to this area, in what ways might AI tools improve productivity and efficiency in business school operations?

Pinnaree: In the wider economy, the value of AI driving efficiencies and delivering value is generally agreed. In its recent Sizing the Prize report, PWC estimates that AI could contribute up to $15.7 trillion to the global economy by 2030, representing a 14% increase in global GDP.

We are already seeing a positive impact across teaching, research, and administrative activities at Sasin. My observation is that while AI use in business schools started with individuals, more business schools are taking an organisational approach to AI and considering it within their strategies. Through this, the use of the technology should increase.

In teaching, AI can assist in analysing students and classes, recommending courses, generating ideas for lesson plans and class preparation, drafting and grading assignments and assessments, and creating a variety of teaching tools, such as slides, images, and games.

Research colleagues use AI platforms to help conduct literature reviews and preliminary data analysis. Of course, it can speed up the writing process by drafting papers and reports by generating initial content and suggesting edits for clarity and coherence. Administratively, GenAI helps with many activities from writing memos to summarising meeting minutes. It is used extensively in the marketing team for voice, video, and animation production.

Oguz: As a general-purpose technology, AI offers numerous applications, and we’re already seeing significant gains across different tasks, from writing and coding to analysis and problem-solving. For instance, a study in Science found that professional writers achieved about 40% efficiency gains with AI tools, and another study with Boston Consulting Group consultants showed 25% efficiency gains. Both studies also highlighted notable quality improvements.

Dejan: I think the great thing about AI is how it handles repetitive tasks such as ticket categorisation and predictive analytics. By using natural language processing, schools can automate the categorisation and prioritisation of support tickets, enhancing response times and optimising resource allocation. In administration, AI can perform predictive analytics to forecast trends in student enrolment, resource demands, and other operational metrics, enabling data-driven planning. It is also worth noting how AI can support personalised learning by analysing student performance data to identify where additional support and help might be needed.

Toby: It’s clear we are heading for many changes over the next few years, but to conclude could I ask each of you how you think the adoption of AI in our business schools will influence curriculum design and importantly accreditation standards?

Dejan: It is clear that AI offers more personalisation and flexibility and therefore adaptive curriculum design, where student data can be used to develop customised learning paths. However, this will need to be done while complying with AI regulation (especially the AI Act in the EU) and privacy rules. I would like to see where we can use real-time student performance data to dynamically adjust course content to better meet students’ needs.

Accreditation bodies may require schools to integrate AI-focused coursework, covering topics like machine learning, AI ethics, and data analytics, and could encourage interdisciplinary approaches involving computer science and business departments. Faculty qualifications could also become more AI-oriented. Ethical considerations are key, such as data privacy and bias mitigation, along with industry-aligned career services that prepare students for AI-influenced roles. Standards may also assess AI-related research output, international collaborations, and readiness for global AI regulations.

Pinnaree: To ensure the balance between human attributes and AI, I’d suggest curriculums need to be redesigned to emphasise uniquely human skills like strategic thinking, ethical judgment, and interpersonal communication. With that, we need to refine assessment methods that measure these competencies beyond what AI can replicate. With AI becoming more embedded in business schools at an organisational level, accreditation will need to replicate that. The challenge for both business schools and accreditation agencies is to keep up with the speed of AI developments.

Oguz: Yes, with AI set to transform industries, business schools need to update their curricula to include foundational AI knowledge, hands-on experience with AI tools, and a focus on AI’s ethical and strategic implications.

On the accreditation side, standards may evolve to make AI competencies a key learning outcome. Accreditation bodies could (and perhaps should) soon specifically require schools to show that they’re preparing students to use AI responsibly—not just building technical skills, but also covering important areas like ethical AI, bias awareness, and understanding AI’s impact on society. Schools may need to demonstrate that graduates leave with not only strong AI skills but also the ability to make thoughtful, ethical choices about how they use them.

Toby: that is a great point to finish on, thank you to you all for taking part. It’s been fascinating getting your views on AI and its place within business schools. Interesting times ahead!