As the demand for personalised learning experiences continues to grow, business schools are turning to advanced technologies to meet the expectations of today’s digitally native learners. This case study explores how one innovative institution implemented AI-powered personalisation in business education—and the remarkable outcomes that followed.
The result was a scalable model that improved engagement, supported diverse learner needs, and empowered faculty with actionable insights.
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The Institutional Context
A mid-sized, globally ranked business school offering MBA and executive education programs sought to improve:
- Student engagement in core modules
- Academic performance in quantitative courses
- Retention rates in blended and online formats
- Timeliness and consistency of assessment feedback
The faculty recognised that traditional delivery models were not meeting the diverse learning preferences of their increasingly international student body.
The AI-Powered Solution
In partnership with an education technology provider, the school deployed an AI-enhanced learning platform across key MBA modules such as:
- Financial Accounting
- Strategic Management
- Operations Analytics
- Organisational Behaviour
The platform included:
- Real-time performance dashboards
- Learning profiles for each student
- AI-driven content sequencing
- Automated feedback on assignments
- Custom assessment journeys based on progress
Educators were trained through The Case HQ’s educator development programs, ensuring responsible implementation of the new technologies.
How It Worked: Learning Personalisation in Action
Here’s how the AI-powered personalisation functioned:
1. Adaptive Content Delivery
Students received content based on their initial performance diagnostics. For example, students with prior finance exposure moved quickly through foundational concepts, while those who needed reinforcement were given remedial videos and exercises.
2. Smart Assessment Sequencing
Assessment quizzes adapted based on each student’s knowledge trajectory. Those demonstrating mastery advanced to case-based application questions, while others received scaffolded support.
3. Instant Feedback
AI-generated feedback on written reports included structure, clarity, and alignment with learning outcomes. Students could revise based on this real-time guidance before final grading.
4. Faculty Insights
Faculty dashboards displayed real-time data on individual and cohort performance, enabling targeted interventions and tutorial planning.
Measurable Outcomes
After two semesters, the business school reported:
| Metric | Before AI Integration | After AI Integration |
|---|---|---|
| Student Engagement | 64% active participation | 91% active participation |
| Assignment Resubmission Rate | 15% | 38% (more iterative work) |
| Pass Rate in Quantitative Courses | 76% | 93% |
| Faculty Satisfaction (Surveyed) | 62% | 88% |
| Average Turnaround Time for Feedback | 5 days | Same day |
These figures indicate that AI-powered personalisation significantly improved the overall learning experience.
Student Feedback
Students described the experience as:
“Like having a personal tutor 24/7. I knew what to improve and how.”
“I didn’t feel lost in the numbers-heavy subjects anymore.”
“I appreciated how the system adjusted to my pace. I could go deep when I wanted to, and get help when I needed it.”
International students particularly appreciated the language support tools embedded in the platform’s writing feedback engine.
Lessons for Other Institutions
Based on this case, other business schools should consider the following when implementing AI personalisation:
Start small – Pilot one or two modules before scaling
Train faculty – Leverage courses like those on The Case HQ to build confidence in using AI tools
Respect data ethics – Ensure transparency, bias audits, and GDPR compliance
Use feedback loops – Continuously refine the system based on faculty and student input
Maintain human connection – Use AI to augment, not replace, educator-student relationships
The Future: AI as a Strategic Education Partner
With AI evolving rapidly, future developments in business education may include:
- Career pathway predictors based on learning analytics
- AI-generated practice simulations using real-time financial data
- Cross-course knowledge tracking to build holistic learner profiles
- Smart mentoring systems linking students with AI-matched faculty advisors
These innovations will further integrate AI into curriculum design, assessment, and lifelong learning support.
This case study demonstrates the powerful impact of AI-powered personalisation in business education. When implemented thoughtfully, it can boost student performance, reduce faculty workload, and deliver learning that is as adaptive as it is effective.
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