The Business

Generate AI (GenAI) has made a profound difference to the educational landscape, enabling new methods for learning, research and teaching, redefining student engagement and streamlining workflows.

And although GenAI and its possibilities are creating a fundamental shift in teaching and learning, institutional change is taking a slower path, with many educators remaining cautious about its adoption.

According to the Association to Advance Collegiate Schools of Business (AACSB), 80 percent of business school faculty say they would embrace the idea of using GenAI in their work. Yet only one in four use it weekly in teaching.

According to Alain Goudey, Associate Dean for Digital at France’s NEOMA Business School, teachers in higher education institutions worry about academic integrity, fearing students may misuse chat-style AI for assignments.

Because the technology is almost freely available, and adoption rate is above 90 percent among 18-24-year-olds, Goudey admits this is likely.

“There are also concerns over hallucinated content - inaccurate or biased outputs undermining trust - and the learning curve associated with mastering prompt engineering.

“Some faculty resist disrupting familiar pedagogies, questioning whether AI truly adds value versus complexity,” he tells QS Insights Magazine.

Personalised, inclusive and scalable learning

GenAI’s capacity to tailor education at scale is one of the most promising features for the programmes of tomorrow.

NEOMA and IIM Indore, for example, are using GenAI to create adaptive learning paths that respond dynamically to student progress.

Professor Himanshu Rai, Director of IIM Indore says: “Our faculty are beginning to see GenAI as a thought partner, not just a tool. It allows for rapid content generation, real-time adaptation and more meaningful learner engagement.”

Similarly, Goudey believes that GenAI enables educators to "create personalised, adaptive learning paths by automatically adjusting complexity based on student performance and providing tailored feedback, learning contents or learning experiences at scale”.

The fast and automated nature of GenAI can also take away educators' administrative load. Goudey notes GenAI’s content-generation capabilities freeing faculty to focus on higher-order tasks like mentoring and designing projects, as routine quiz authoring, content reformatting or content updates are automated.

Whether generating contextual feedback, simplifying complex concepts or supporting specialised communication, GenAI can make education more accessible and individualised.

GenAI tools generate custom problem sets, transform technical data into business narratives and offer real-time support, reducing participation barriers and levelling the academic playing field.

For quantitative courses like Business Statistics, Priyanka Shrivastava, Professor of Marketing and Analytics at Hult International Business School in the UK says: “We have observed a notable improvement in students' ability to interpret and articulate the output of statistical software.

“Students utilise GenAI to translate technical jargon into business language, which is assessed through their presentations to panels of faculty and peers.”

Enhanced engagement and applied creativity

GenAI offers students the opportunity to become active creators of ideas, rather than passive consumers of knowledge.

At NEOMA, students used GenAI to prototype a fully functional helmet, using sensors, connectors and coding aspects.

Goudey notes that initiatives like this enable students to delve deeper than before into project-based learning, energising the wider student community and faculty alike.

“Students are really interested in the topic as more than 82 percent of NEOMA’s students have been trained specifically on Gen AI, and not necessarily on a mandatory credited course,” he says.

Similarly, Imperial College London’s pilot of “Digital Twins”, AI-driven, video-based avatar models of a real lecturer which helps support teaching modules like marketing management, entrepreneurship and innovation, and organisational behaviour on the GMBA and EMBA has been a success.

Designed to replicate their visual presence, tone and teaching style, “Digital Twins” offer an innovative way to complement human lecturers with AI technology.

Dr Nai Li, Head of Research and Impact, IDEA Lab at Imperial Business School, says that the technology can answer students’ questions, provide feedback, interpret assessment criteria and understand complex concepts.

“This type of 24/7, always-on, responsive support can reduce isolation and boost confidence, especially in large or online programmes,” Adds Dr Li.

On a broader scale, HEIs are using GenAI to simulate roleplays, facilitate dynamic case discussions and co-create new business models, enabling learners to test hypotheses and iterate rapidly in a low-risk environment.

The result? Higher-quality outputs and deeper, more engaged learning.

Faculty productivity and pedagogical Innovation

Faculty using GenAI instinctively see it as more than a time saver, but a co-designer.

Martin Butler, Professor of Digital Transformation and Academic Director for the MBA at Belgian’s Vlerick Business School notes how GenAI enables faculty to generate fresh, topical cases within days of real-world events, transforming the pace and relevance of content creation.

He tells QS Insights Magazine: “GenAI reduces the cycle time to create very fresh and engaging content, even personalised per participant.

“I recently used a case about the Marks & Spencer cyberattack, just days after the event, because I could write it efficiently with GenAI.

“New exercises can be designed for the classroom where participants can apply knowledge and frameworks immediately, since the drudge of finding and assimilating information can be done quickly.”

What’s holding institutions back?

Despite this momentum, GenAI adoption remains uneven.

The gap in adoption may be explained by low levels of self-reported proficiency with the new technology - with only 7 percent of faculty identifying as experts at using GenAI in teaching, according to AACSB data.

But it isn’t just faculty proficiency that poses a challenge; structural, cultural and ethical hurdles also continue to slow integration across higher education institutions.

The potential for students to misuse GenAI has been a concern since its creation, over fears of students submitting AI-generated assignments or bypassing the critical thinking process altogether.

In disciplines requiring precise calculations or data interpretation, there’s a risk that students may arrive at the “right” answer without understanding the underlying methods and necessary problem solving required for the real-world.

At the same time, GenAI is prone to generating plausible but inaccurate content known as ‘hallucinations’ as well as reproducing biases present in its training data.

Professor Butler notes: “This is an ongoing challenge for business schools globally, and we are all working together (e.g. FOME alliance) to determine the best way forward. We do use GenAI tools, but with great care due to well-known limitations.

“We ask that students disclose their GenAI usage after the references by stating both what they have used and the platforms that they used.”

At Hult, Professor Shrivastava notes addressing algorithmic bias as a teachable moment: “Our faculty are encouraged to use the inherent biases in AI outputs as an opportunity for critical discussion.

“Students in a marketing course might be asked to analyse an AI-generated customer persona for demographic biases, or a strategy class might critique the ethical implications of an AI-recommended business decision,” she tells QS Insights Magazine.

Managing GenAI risks remains an open challenge.

Educators must teach students to interrogate AI outputs critically, just as they would with any secondary source.

One overlooked barrier is the gap in student readiness, some students arrive with sophisticated GenAI skills; others with none.

“If we design an exercise or activity for them to use GenAI, we also need to have a somewhat uniform level of capability, which is not always the case. We have designed a mandatory GenAI course for all students to ensure a minimum level of proficiency,” Professor Butler says.

Many schools have GenAI guidelines, however, few have comprehensive frameworks that keep pace with the ever-evolving technology.

Faculty and administrators are navigating grey areas around responsible integration, acceptable use and data privacy, often without consistent or enforceable policy backing.

How institutions can lead with purpose

If the benefits are clear and the barriers are known, the next logical question is: What should institutional leaders do now?

Within the next three years, Hult International Business School plans to integrate a mandatory module on AI literacy into the core curriculum for all incoming students.

This reflects a growing consensus that these skills are not optional, but essential for graduates in a GenAI-enabled workforce.

Faculty also need targeted, discipline-specific training; workshops that focus on applying GenAI with real courses, for example.

To train 90 percent of the faculty at NEOMA, the business school set up their own learning content - available online and asynchronously - as well as face-to-face training sessions to answer concrete needs from the faculty.

Goudey says: “During these sessions, they have been trained to use AI tools but also to rethink their pedagogical approach through the lens of GenAI.

“Our training sessions were mandatory because we are fostering innovation in the school, so it’s important for our professors to be really confident with this technology.”

Redesign assessments for an AI-enhanced world

Rather than resist GenAI, forward-looking educators are redesigning assessments to include it, meaning more oral defences, in-class synthesis tasks, iterative writing assignments and evaluation of AI-generated outputs.

Hult and Vlerick support assignment redesigns that balance GenAI usage with individual critical input, ensuring integrity without stifling innovation.

Dr Li says Imperial’s approach has been to start from first principles, revisiting what they assess, why and how.

“Our approach has been to start from first principles—revisiting what we assess, why, and how,” she says.

“Our working group on AI in teaching and assessment has encouraged departments to “stress-test” existing assessments to ensure they genuinely measure the intended learning outcomes, even in a world where students routinely use AI.”

Foster a culture of experimentation and recognition

Universities and business schools pride themselves on fostering curious individuals, ready to tackle the problems of the world.

Institutions must normalise experimentation among students and faculty to become AI natives for the future.

The goal of Hult’s faculty development programme is to build a culture of thoughtful experimentation and to empower faculty to become leaders in the pedagogical application of AI.

IIM Indore believes GenAI should be embedded into the ethos of continuous improvement, not enforced through rigid metrics.

“Teaching evaluations can include prompts for faculty to reflect on how they have experimented with technology or personalised learning, but this reflection should be qualitative and exploratory, not prescriptive.

“Our approach is to nurture a culture of experimentation, provide supportive ecosystems, and recognise innovation, rather than impose rules. That’s how we ensure that GenAI is adopted meaningfully and sustainably,” Professor Rai adds.

Experimentation is key to sustainable AI integration according to Professor Butler: “The pace is relentless, and the only way to somewhat keep up is to continually learn new things through experimentation.

“Vlerick is very entrepreneurial, and we also display this entrepreneurial mindset in how we deal with GenAI. Try things, learn from what works and what does not, and then improve.”

Beyond adoption, toward transformation

Whether students and faculty think about GenAI positively or not, it isn’t going anywhere.

This means the challenge for higher education institutions isn’t about whether to adopt the technology, rather how to do so meaningfully.

Universities and business schools that see the value in GenAI aren’t rushing to mandate, they are aligning its usage with their core educational missions: developing critical thinkers, ethical leaders and agile professionals ready for a complex world.

Institutional leaders need to invest in infrastructure, training, governance and most importantly, a culture of purposeful experimentation.

GenAI can serve as a catalyst for lasting pedagogical innovation when used intellectually.

The future of higher education isn’t just AI-enabled, it’s AI-informed, human-led and impact-driven.