New Delhi, June 4 -- As enterprises accelerate investments in artificial intelligence (AI), analytics and automation, business schools are transforming their own. Institutions are increasingly moving beyond traditional classroom teaching to build AI and data labs that mirror real-world business environments, creating a new generation of managers who are as comfortable with data as with strategy.
According to Dr Prof. Saurabh Mittal, Programme Chair, Big Data Analytics, at FORE School of Management, the shift marks a fundamental evolution in management education-from teaching data literacy to enabling data fluency.
"Students today need to move beyond understanding what data is to understanding what insights can be drawn from it and how those insights influence business decisions," Mittal said.
The transformation reflects broader changes underway across the industry. As organisations embrace AI-led decision-making, the demand for professionals who can bridge business judgment and analytical reasoning is rising sharply.
At FORE, this shift is visible through initiatives such as the Data Experience Lab (DEL), where students work on datasets, live projects and business problems ranging from customer churn and employee retention to demand forecasting, process optimisation and digital marketing performance. Rather than focusing solely on technical execution, students are encouraged to identify business problems, interpret findings and translate them into strategic recommendations.
The model increasingly resembles consulting and analytics environments that graduates are likely to encounter in industry.
AI laboratories are also emerging as talent pipelines for startups and Global Capability Centres (GCCs), sectors that are among the largest recruiters of analytics and AI talent. According to Mittal, employers are increasingly looking for candidates who can navigate ambiguous business situations, work with complex datasets and operate in rapidly changing technology environments.
This changing demand is giving rise to what he describes as the "hybrid manager"-professionals who understand business realities while engaging confidently with data, systems and analytical outputs. "Managers can no longer remain disconnected from data-led decision-making," he noted.
The evolution is also reshaping the relationship between academia and industry. Partnerships with technology firms and analytics platforms are increasingly influencing curriculum design, classroom discussions and applied learning experiences. Such collaborations help ensure students work with contemporary tools and business challenges rather than relying solely on textbook examples.
However, Mittal cautions against viewing AI adoption purely through the lens of technology. As institutions standardise around similar tools and platforms, there is a risk that learning could become overly uniform, producing students who know how to operate software but lack the ability to think critically about business problems.
To address this, educators are increasingly focusing on interpretation, problem framing and independent thinking, ensuring students become creators of AI-driven solutions rather than passive consumers of technology.
Looking ahead, Mittal believes AI labs could evolve beyond learning centres into innovation hubs and startup incubators, provided institutions create ecosystems that encourage experimentation, interdisciplinary collaboration and industry engagement.
As AI becomes embedded across enterprise functions, dedicated AI labs may soon become as fundamental to business schools as finance labs and libraries. The shift underscores a larger digital transformation story: preparing the workforce not merely to use AI, but to build, govern and lead with it.
Published by HT Digital Content Services with permission from TechCircle.