In Episode 126 of The mbaMission Podcast, mbaMission Senior Consultant Harold Simansky and Founder Jeremy Shinewald welcome back Jim Caruso, chief innovation officer at Elevate and a graduate of the Michigan Ross Online MBA program. Jim has built and sold companies, leads innovation for sports and entertainment brands, and now teaches artificial intelligence (AI) as an adjunct instructor at Montclair State University. As a result, he can view AI and its development from the perspective of the undergraduate classroom, the C-suite, and the MBA world.
Table of Contents
Why Should You Embrace AI Rather Than Fearing It?
In his course, Jim’s students have told him that they hate AI and fear it will eliminate their target jobs before they even graduate. His response is to help them see AI as just the latest technology in a series of developments they already live with every day. The internet, mobile phones, and social media all displaced jobs and created new ones, as AI has done and will continue to do. Jeremy notes that the role of “graphic designer” was expected to be made obsolete by the internet in its early days, but instead, the job actually grew as the tools these professionals use improved. And recently, chief executives have begun walking back their initial predictions of a complete job apocalypse. Jim shares that by the end of his course, the students who had arrived terrified report that he changed their perspective. The goal is to use AI to get better at the things you already do well.
What Is the Relevance Economy?
Jim argues that for years, business ran on a knowledge economy: Whoever had the most expertise held the advantage. AI now gives everyone access to that expertise, quietly erasing the associated advantage and ushering in a relevance economy, in which value comes from taking widely available information and making it into something of substance. AI levels the playing field, but the underlying thinking still has to be yours. Jim regularly sees nonsensical outputs because someone merely accepted what the AI produced in response to their prompt without applying any judgment to it before passing it along.
How Should Schools Teach AI?
Jim originally assumed that his undergraduate students were constantly using AI. They were not. Many had been taught that they should never use it for coursework. But Jim believes that rather than banning the technology, teachers should instruct students in how to use AI ethically. For example, copying and pasting the answer to an assignment would be considered out of bounds, but relying on AI to gather base information quickly and efficiently so that more time can be devoted to analyzing and synthesizing that data would be acceptable. He compares AI to the word processor and Excel, explaining that garbage in still produces garbage out.
Why Is AI Not One Thing?
Jim acknowledges that the AI label is easily misunderstood. “AI is an incredibly broad way to frame things,” he says. “It could mean so many things.” A tool that can generate content in seconds, a large language model that can quickly decipher a mountain of data, and agentic platforms such as ChatGPT and Claude are all different applications with very different skill sets. Adoption and application are currently uneven across industries, disciplines, and roles, which is why Jim feels that the useful question to ask is not should you use AI but what are you trying to accomplish with it?
How Can Large Language Models Convert Data into Insight?
Data analytics is where Jim makes his strongest case for AI. At his previous company, his team had access to massive amounts of consumer data, and although dashboards could display this information, extracting insight from it was prohibitively difficult. Companies spent a decade hearing that data was the new oil and collecting more of it than they could use, and clients would tell him that they knew value was buried in the data but that they had no idea how to get it out. At Elevate, large language models can process ticketing and fandom data and What Does an MBA Program Teach That Technology Cannot Replace?generate insights at a speed and scale no human could match. Jim explains that the key is pairing models with quality data, sharp questions, and people who can translate insight into action.
When asked what he learned in his MBA program that AI could not replicate, Jim states that the ability to collaborate with others, work for people, and mentor people is foundational. No single class can teach it, but rather, it is the cumulative result of the MBA program as a whole. In Jim’s view, that is what makes the degree invaluable, whether you attend a full-time program or earn your degree online or part-time while maintaining a job and raising a family.
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