Navigating the AI Revolution
- By infusing AI components into their programs, business schools can help students cultivate proficiency in using generative AI platforms.
- At the same time, schools should continue to focus on durable skills such as critical thinking, communication, emotional intelligence, ethical judgment, and cultural awareness.
- The five generations that currently make up the workforce have very different attitudes about AI, and managers must understand the strengths and weaknesses of each group.
As the business sector continues to increase the ways it relies on artificial intelligence (AI), more business schools are determining how to incorporate the technology into their classrooms. In fact, about 74 percent of business schools currently are teaching generative AI, according to a survey by the Graduate Business Curriculum Roundtable.
For example, a bachelor’s program at Carnegie Mellon University’s Tepper School of Business in Pittsburgh and a master’s program at Stanford University’s Graduate School of Business in California take deep dives into AI principles. These programs equip students with the skills they need to embark on various AI careers. Similarly, SKEMA Business School in France and the Schulich School of Business at York University in Canada have launched master’s degrees in AI and data science. These programs cater to students who wish to pursue careers in academia or industry research.
Schools also are using AI as a tool to promote learning in the classroom. At the Massachusetts Institute of Technology’s MIT Sloan School of Management in Cambridge, AI is used in courses such as AI for Business Strategy. The technology simulates market conditions, allowing students to test strategic decisions in a controlled yet dynamic environment. Stanford uses machine learning algorithms for financial modeling and market analysis, giving students hands-on experience in modern analytical techniques.
These are just a few examples of how generative AI is becoming a foundational topic in many business programs. And for good reason: Business schools must introduce new programs dedicated to AI and infuse AI components into existing courses if they—and their faculty and students—are to keep up with the technology’s growing prevalence in the workplace.
The New AI Curriculum
In the years ahead, most employers will likely expect business school graduates to be able to demonstrate a technical mastery of AI. To meet this expectation, schools need to teach students several facets of AI via offerings similar to the eight course descriptions that I outline below:
AI and Machine Learning Fundamentals. This course covers the core principles and practical applications of AI and machine learning. A module on natural language processing (NLP) demonstrates how AI interprets and generates human language. A section on prompt engineering shows students how they can guide AI to produce desired outputs, and a section about contextual relevance design ensures that students use prompts that are appropriate for the task. Students also learn how to be creative in prompt design and how to achieve unique and effective AI interactions.
Data Science for Decision-Making. Students master practical data analysis techniques using Python or R. In addition, they practice statistical modeling, predictive analysis, and data visualization with tools like Tableau. Students apply these principles to real-world business case studies and learn the impact of data-driven strategies in decision-making.
Ethical Implications of AI. This course introduces ethical theories and principles relevant to AI and explores concerns about privacy and bias in algorithms. Ethical dilemmas are highlighted through case studies. The curriculum addresses the development of ethical guidelines and governance for AI systems, which encourages students to think critically about innovation and moral responsibility.
Business schools must infuse AI into the curriculum if they—and their faculty and students—are to keep up with the technology’s growing prevalence in the workplace.
Leadership for Digital Transformation and Global Business Strategy. Students learn to make data-driven decisions by relying on AI to anticipate trends, identify opportunities, and reduce risks. They also use AI to personalize leadership development, hone skills, streamline workflows, and gain a competitive advantage in international markets.
AI in Marketing and Consumer Behavior. This class delves into how AI can personalize marketing efforts and predict consumer trends. Case studies look at examples such as the AI-powered recommendation engines used by e-commerce giants.
AI in Supply Chain and Operations Management. Instructors explore AI’s use in real-world contexts, such as how autonomous vehicles improve logistics or AI optimizes inventory management.
Human-AI Collaboration. By focusing on the synergies between human workers and AI, this course shows how technology can augment, rather than replace, human capabilities. Students might study AI-assisted design processes as part of the class.
Cybersecurity, Governance, and AI. Instructors discuss the government frameworks and regulations that ensure responsible AI usage, as well as the role of corporate and public governance in mitigating risks and ethical concerns. They also compare how different regulating bodies around the world implement AI. Cybersecurity topics might center on information security governance, risk management, compliance, incident management, and other program areas tailored to organizations.
The Durable Skills Revolution
But AI skills aren’t the only ones that business students will need in the 21st-century workplace. To make sure their graduates are well-rounded business leaders who will thrive amidst technological advancements, business schools must offer courses that cover a range of soft and durable skills:
Critical thinking, problem solving, and systems thinking. AI provides vast data but can’t make decisions. Students must learn to dissect complex challenges, consider multiple viewpoints, and develop well-reasoned solutions. Once they gain an understanding of how different systems interact, they will be able to make strategic decisions in complex, interconnected business environments.
Because the business landscape increasingly will be governed by technology, students must have the capacity to make decisions rooted in moral principles and integrity.
Communication, collaboration, and negotiation. In an age where digital communication often supersedes face-to-face interactions, learners need to master the art of articulating ideas clearly and effectively in both written and verbal forms. Students must learn how to build and maintain dynamic team relationships, which will allow them to collaboratively solve problems and promote innovation. Students also need to practice the art of reaching mutually beneficial agreements by balancing assertiveness and empathy, both of which are crucial in diverse business scenarios.
Emotional intelligence, resilience, adaptability, and stress management. When students understand and can manage their emotions, they will be able to empathetically navigate interpersonal relationships with team members and clients. They must develop the ability to manage stress and bounce back from the challenges they will face in a high-pressure business world. They also must learn to adapt fluidly to change and uncertainty, which will be constantly present in a fast-evolving business world influenced by AI.
Ethical judgment, integrity, and cultural awareness. Because the business landscape increasingly will be governed by technology, students must have the capacity to make decisions rooted in moral principles and integrity. They also must be prepared to respect and leverage cultural differences as they operate in a diverse, global environment.
It’s interesting to note that different generations have different levels of comfort with technical skills and durable skills. My research shows that while older workers commonly possess soft skills, younger ones either don’t have them or struggle to use them effectively. But younger employees are more fluent in technology than their older counterparts. In fact, technology has widened the gap between generational groups in the workplace.
As business schools integrate AI into their programs, they need to consider how each of these groups will use and respond to technology on the job:
Boomers (born between 1946–1964). While some of them already have retired, or are about to, many of those who are still in the office fear AI. They find it particularly difficult to communicate with members of younger generations who prefer to interact digitally.
Generation X (1965–1980). These workers often are considered members of the last generation to ascribe to a work ethic—and the last one to possess innate, durable skills. They have a mixed reaction to AI and are reluctant to implement it in their work.
While older workers commonly possess soft skills, younger ones often don’t have them. But younger employees are more fluent in technology than their older counterparts.
Generation Y (1981–1996). Employees from this group, also known as millennials, desire a work-life balance and are not loyal to companies. They use AI mainly to search for information and write documents. Because they’re comfortable both with in-person and digital communications, they’ve emerged as the new connectors in the workspace, which makes them ideal team leaders for mixed-generational teams.
Generation Z (1997–mid 2010s). These workers expect quick rewards, resist adapting to workplace hierarchies, dislike making discretionary effort, and have promoted mass office movements such as “quiet quitting.” They expect managers to provide precise job descriptions and manage workloads effectively. Their employee lifecycle is approximately one year.
Members of Gen Z are tech-savvy and expect their managers to be the same. They dislike working in places that don’t have technological integration, and they hope for thorough onboarding—often through AI. They respond better to text-based communication than to verbal leadership.
Generation Alpha (mid 2010s–mid 2020s). For these digital natives, technology has always been an integral part of life. They already use AI wearables to check their health status and help them navigate any activity. When they join the workforce, many will be fully onboarded through AI. They will have their own AI HR managers who can provide on-demand advice. When they work from home, they will have AI assistants and receive gamified tasks to help them maintain engagement. Like members of Gen Z, they will likely have trouble communicating outside of digital contexts.
Business Education in the AI Age
Business is balanced on the precipice of the AI revolution. Technical abilities such as AI, data analysis, and machine learning are indispensable for tomorrow’s leaders. Yet, such competencies must be complemented with timeless human-centered skills that include critical thinking, emotional intelligence, ethical judgment, and adaptability. The future of business leadership hinges on the ability of educators to help students develop and harmonize these two distinct skill sets.
Employers, too, will need to be savvy about bridging generational divides where AI is concerned. It will be essential that they offer onboarding and professional development options that help employees navigate the AI revolution and enable the organization to thrive.
When business graduates possess both technical expertise and durable skills, they will be prepared to navigate the complexities of an AI-enhanced world, while maintaining the human touch they need to be effective leaders.