Why Limit a College Program Reboot Due to Generative AI to only MBA Programs?

Last week, I read a Forbes article written by Villanova University graduate business school professor Noah Barsky that argued for MBA programs to utilize generative AI for a massive reboot.

Mr. Barsky cited Microsoft’s announcement about the release of Co-Pilot, a generative artificial intelligence tool to be integrated into its Office 365 suite, as a game changer in that it hands AI to the “masses” via the popular applications of Microsoft Word, Excel, PowerPoint, and Outlook.

Delivering these tools to workers will mean that companies will be “challenged to rethink business models, talent needs, and resource usage” according to Mr. Barsky. He further writes that “it will spur creativity, shorten work timelines, and improve results.”

The disruption of generative AI on businesses “may be more than many B-Schools can handle” according to Mr. Barsky. Those with outdated curriculum, outdated delivery models, inadequate budgets, and workplace cultures not apt for innovation will bear the stiffest consequences. Employers may opt to not pay for MBA graduates whose credentials do not include the skills required by the products enhanced by generative AI.

According to Mr. Barsky, the Graduate Management Admission Council reported in its 2022 Application Trends Survey that 60 percent of MBA programs received fewer applications, with part-time programs seeing the biggest impact (note: the overall decline in applications was 3.4 percent). Mr. Barsky further notes that this decline in applications occurred before generative AI became mainstream. To prove his point, he prompted ChatGPT to respond with ways in which generative AI will impact an MBA education. Its answer is below.

“Generative AI has the potential to significantly impact MBA education in a number of ways:

Customized learning: Generative AI can be used to create personalized learning experiences for MBA students. By analyzing data on students’ learning styles, preferences and performance, AI algorithms can generate customized content and activities to help each student learn more effectively.

Real-world simulations: AI can be used to generate realistic simulations of real-world business scenarios, allowing MBA students to practice decision-making and problem-solving in a safe and controlled environment.

Data analysis: AI can be used to analyze large datasets, allowing MBA students to gain insights into business trends and patterns that would be difficult or impossible to identify manually.

New teaching tools: AI-powered tools such as chatbots, virtual assistants, and intelligent tutors can provide MBA students with on-demand assistance and feedback, helping them to learn more efficiently and effectively.

Improved decision-making: By leveraging AI-powered analytics and insights, MBA graduates can make more informed and data-driven business decisions, leading to improved outcomes for themselves and their organizations.

Overall, generative AI has the potential to revolutionize MBA education by providing students with more personalized, data-driven and immersive learning experiences.”

Mr. Barsky poses the question: “how many schools can substantively address any of those five expectations.” His answer: “Very few.” He writes that lagging programs often rely on aging textbooks, yellowed lecture notes, obtuse theories, and stale case studies which are a mismatch for an AI co-piloted world.

Four concerns were raised by Mr. Barsky. These are:

  1. Universities struggle to incentivize faculty to build innovative curriculum. Pressure to adapt decades old teaching to the expectations of an AI world may accelerate faculty retirement.
  2. Market entrants are often underestimated by legacy enterprises. Emerging entities may have the incentive to “build coalitions, broaden educational offerings, develop innovative delivery methods, and establish meaningful credentials. These upstarts will shatter the status quo of business education.”
  3. To address data analytics demand, many business schools teach coding. Generative AI tools can generate accurate coding. How will curricula adjust to cultivate the critical thinking and communication skills far beyond computations?
  4. The nature of AI to transform the market will require strategic agility, compelling leadership, and novel solutions. That’s a bad match, writes Mr. Barsky, for “bureaucratic universities lacking meaningful incentives, curricular governance, unified stakeholders, and novel tech teaching platforms.”

Mr. Barsky concludes his article with the statement that over “the next 1-3 years, generative AI will transform education at all levels.” Innovative schools will “prepare students for dynamic futures.” Those schools that don’t innovate will struggle “for relevance and existence.”

I wholeheartedly agree with Mr. Barsky’s observations and conclusions. If one of my daughters applied to a full-time MBA program, I would advise her to review the curriculum for relevancy to the accelerating trend of analytical and other software programs to include generative AI co-pilots. There’s no reason to spend two years of time and tuition reviewing outdated case studies.

That said, if the child of a friend or relative was applying to any college’s undergraduate program, business or otherwise, I would ask the same question. I wonder how long it will take for our universities to revamp their curriculum to prepare their graduates for a future far different than experienced by any of their predecessors? Degrees are completed in years, not months. Not providing students with the tools to utilize generative AI will leave them with a competitive disadvantage as they seek post-graduation employment.

Subjects of Interest

EdTech

Higher Education

Independent Schools

K-12

Student Persistence

Workforce