The grandmaster of chess, Garry Kasparov, lost a series to the AI program Deep Blue, and that was, for most practical purposes, the first widely reported instance of an expert being outperformed by a computer program. Long before that, science fiction had imagined worlds in which machines would take over human decision-making. One may recall the HAL computer in 2001: A Space Odyssey, refusing to open the pod bay doors. Such scenarios still seem unlikely in real life. The rules of robotics envisioned by Isaac Asimov continue to influence the ethical imagination of technologists, and deliberate harm to humans is actively guarded against. Yet, modern AI systems are increasingly capable—some can even identify vulnerabilities in complex systems—raising legitimate concerns about their reach and control.
With that context, let us turn to management education. Management is not merely about systems and processes; it is about leading organizations, making judgments under uncertainty, and dealing with people. Leadership, empathy, negotiation, and ethical reasoning remain deeply human capabilities that AI cannot fully replicate.
However, it would be misleading to assume that AI’s impact will be limited to “lower levels” of management. While it is true that routine and operational tasks are the first to be automated, the influence of AI is steadily moving upward into decision-making, strategy, and analytics.
Consider how software development has evolved. With tools like generative AI assistants, a programmer can now produce working prototypes in hours rather than weeks. This acceleration is not confined to coding. Activities such as report writing, financial modeling, marketing content creation, and even legal drafting are increasingly supported—or partially automated—by AI systems. Tasks that once required teams of analysts can now be initiated by a single individual equipped with the right prompts.
Implications for Management Education
This shift raises important questions for management education:
- What do we teach at Rajalakshmi School of Business (RSB)?
If AI can generate reports, analyze data, and even suggest strategies, the emphasis must shift from doing to understanding and interpreting. Students learn how to ask the right questions, validate AI outputs, and make informed decisions. We discuss output and reports as a support to decision-making. - How do we teach at Rajalakshmi School of Business?
Traditional case-based teaching remains relevant, but it must now incorporate AI-assisted analysis. Students are encouraged to use AI tools critically—not as crutches, but as collaborators. - What skills matter most?
Analytical thinking, domain knowledge, ethical reasoning, and communication skills will become even more valuable. The ability to integrate AI insights with human judgment will define effective managers. In both years of the RSB curriculum, we teach courses in Business Analytics, Python, Forecasting, and Machine Learning.
The Indian Context
India presents a particularly interesting case. With its large and young workforce, expanding digital infrastructure, and strong IT services sector, the country is both a major beneficiary and a potential disruptor in the AI-driven world.
- Transformation of the IT and Services Sector
India’s IT industry has traditionally relied on large-scale human effort for coding, testing, and maintenance. AI-driven automation threatens to reduce demand for routine programming roles while increasing demand for higher-order skills such as AI model management, data engineering, and system design. - Skilling and Reskilling Challenges
A significant portion of the workforce will need reskilling. Management education in India must therefore integrate AI literacy across disciplines—not just in specialized courses but in finance, marketing, operations, and HR. - Democratization of Entrepreneurship
AI tools lower entry barriers for startups. A small team—or even a single entrepreneur—can now build products, conduct market research, and scale operations with minimal resources. This could lead to a surge in entrepreneurship, particularly in Tier-2 and Tier-3 cities. - Public Sector and Governance
AI is also influencing governance in India—through initiatives in digital public infrastructure, smart cities, and data-driven policymaking. Management graduates will increasingly find roles that intersect with public systems and require understanding of both technology and societal impact.
Global Workforce Implications
Across the world, AI is reshaping the nature of work:
- Job Polarization: Routine jobs—both manual and cognitive—are being automated, while demand grows for creative, strategic, and interpersonal roles.
- Hybrid Roles: The future manager is not just a domain expert but also a “technology translator” who can bridge business needs and AI capabilities.
- Continuous Learning: The shelf life of skills is shrinking. Lifelong learning is no longer optional but essential.
- Ethical and Regulatory Considerations: Issues such as data privacy, algorithmic bias, and accountability are becoming central to management decisions.
Conclusion
AI is not replacing management—it is redefining it. The role of a manager is shifting from executing tasks to orchestrating systems where humans and machines work together. Management education must evolve accordingly, preparing students not just to survive in an AI-driven world, but to lead in it.