AI and the Next Evolution of Higher Education

Emmanuelle Houet, Digital Learning Experience Director, EDHEC Business School

Emmanuelle Houet, Digital Learning Experience Director, EDHEC Business School

Emmanuelle has been a staff member at EDHEC since 2008. She joined the school to manage the European Apprenticeship Track on the Paris Campus.

Since July 2018, she has been the manager and, from 2023 Director of the Pedagogical Innovation Laboratory (PILab) in Lille, where her mission is to develop the offer of EDHEC digital courses (blended/fully online) by training & supporting faculty and students; and to initiate pedagogical innovations (AI, learning analytics, student engagement, etc.).

She has an MA degree in Political Science (Sorbonne, Paris) and began her career working as a professor in applied semiology (corporate communications), research methodology, art and aesthetics. Emmanuelle has also been Program Director for a communication school.

Over the past decade, the learner experience in higher education has shifted from traditional teacher-centered models to dynamic, learner-centered ecosystems that leverage digital technologies to foster collaboration, personalization, and continuous engagement.

Following the period of forced digital transformation triggered by COVID-19, institutions were compelled to reflect on the pedagogical value of different formats and how they could be used in a structured and complementary way to shape a sustainable “new normal.”

At the same time, this new context has reshaped learners’ expectations. Personalization, self-paced learning, and interactive technologies have become central components of the educational experience.

Digital transformation, however, is not an end in itself. It must serve pedagogy. Its purpose is to rethink core processes and learning experiences, adapting them to new ways of accessing and interacting with knowledge.

I envision the future of management education as intrinsically phygital, where in-person, asynchronous, and virtual classroom formats coexist and reinforce one another. Blended learning is for me the dominant paradigm, offering flexibility while preserving high-value face-to-face moments dedicated to mentoring, peer exchange, and experiential learning.

Hybrid education responds to the diversity of learners’ needs and can significantly enhance engagement, provided it is intentionally designed. The integration of in-person and online elements must be pedagogically coherent rather than additive.

“Hybrid education responds to the diversity of learners’ needs and can significantly enhance engagement, provided it is intentionally designed.”

These models require thoughtful alignment between teaching strategies and technological integration. Without this coherence, the experience can become fragmented or ineffective. The objective is to allow both instructors and students to focus on learning outcomes rather than on navigating tools.

As digital tools and generative AI rapidly enter higher education, questions arise about the role of instructional designers. Do they still have a role to play? Is generative AI sufficient to design a pedagogical scenario and generate course content instantly?

Instructional design remains essential to ensure that technology enhances rather than distracts from meaningful learning. Learning objectives, teaching activities, and assessments must be coherent and constructively aligned.

Recent work by Philippa Hardman emphasizes that AI should support critical and analytical thinking, such as evaluation, synthesis, and transfer, rather than automate low-level tasks alone.

In this context, the role of the instructional designer is reinforced, not diminished.

In technology-rich environments, instructional design is not optional; it is the strategic lever that safeguards academic rigor while enabling innovation.

Personalization and human connection should be seen as complementary rather than opposing priorities. Learning analytics and adaptive systems can tailor content and pacing to individual needs, but they must strengthen, not replace, relational dimensions such as mentoring, peer interaction, and belonging to learning communities.

Thoughtful use of AI tools (virtual teaching assistants, automated formative feedback, alternative content generation) can provide students with 24/7 support when needed and offer more personalized learning pathways, including activities connected to their interests.

At the same time, these tools allow instructors to monitor learner progress more precisely, foster engagement, and adapt explanations accordingly. This enables more targeted support and ultimately makes teaching more efficient and impactful.

While the pace of change since 2021 makes precise predictions difficult, several trends appear particularly significant and desirable for me in the coming five years:

- AI-driven personalization and adaptive learning: Moving toward genuinely adaptive models that allow students to revisit concepts in different ways rather than repeating identical explanations, while enabling highly motivated learners to explore topics more deeply.

- Support for student well-being: Using AI to help students better organize their learning and structure their academic routines, taking into account individual learning styles.

- Valuing teachers’ work: Allowing instructors to focus on their expertise and mentoring rather than administrative tasks or slide production, through AI-assisted design and grading tools.

- Simplified hybrid learning architectures: Moving beyond the traditional online vs. in-person dichotomy toward fluid, experience-based designs that support learning across contexts.

- Stronger anchoring in real-world practice: Reinforcing the bridge between academia and professional environments through expanded learning-by-doing opportunities, immersive simulations using VR and AI, and greater emphasis on peer learning.