By Robert Brunner, Professor of Accountancy and Chief Disruption Officer, Gies College of Business

Humans love to anthropomorphize. From seeing objects in cloud shapes to naming physical devices, we humanize our environment, making complex things easier to understand and to describe to others. This approach has carried over into the world of artificial intelligence, with the creation of named tools like Alexa and Siri, or when ChatGPT says “Let me know if …” within its response.

On the face of it, this may seem odd. But generative AI tools like ChatGPT and Claude aren’t just code—they are algorithms defined by the shared knowledge of our species. Thus, if you ask ChatGPT to explain special relativity in the voice of Shakespeare, it may seem as if the ghosts of Einstein and Shakespeare are collaborating to quickly generate the result. While this contrived example may have little bearing on the world of business, the embodied spirits in the model are not limited to these historical examples. In this analogy, these large language models are haunted by the cumulative expertise of billions of humans, or the ghosts in the machine, whose digital legacies are encoded in their parameters.

Ironically, the phrase “Ghost in the Machine” was coined by British philosopher Gilbert Ryle as a criticism of the idea that the mind could be considered separate from the body. Now, we use this phrase to describe our interactions with a super-powerful, non-corporeal digital mind—Generative AI. But these interactions are not limited to generating essays; these “ghosts in the machine”, trained on numerous examples, are now completing tasks once exclusively reserved for entry-level workers in marketing, finance, HR, and sales.

This begs the questions: if AI becomes the default “junior hire,” what becomes of recent graduates? And how should higher education, especially business schools, adapt to this new reality?

The Disruption of Entry Level Work

As educators, our first thought around AI tends to be how can we ensure the academic integrity of our classes? While this question has merit, by focusing on the how we educate, we risk missing the more important questions of why and what we educate. As the hyperbole around AI has grown, more students and their parents are questioning the value of a traditional college. These concerns follow from studies such as the well-covered State of the Tech Talent report by SignalGate, which showed a 50% reduction in new graduate hires by big technology firms from pre-pandemic levels. More recently, Dario Amodej, the CEO of Anthropic, a leading AI firm, stated that up to 50 percent of entry-level white-collar jobs could be eliminated by increased adoption of AI tools (i.e., the ghosts in the machine) over the next five years. Why should we expect that business as usual is still a viable approach for higher education? Will the ghosts in the machine take over?

To be clear, Amodej’s warning carries weight, but maybe the truth is more nuanced. Executives from OpenAI, a rival AI firm, paint a different picture. Brad Nightcap, COO of OpenAI argues that rather than AI eliminating entry-level roles, companies will embrace young people who have a level of fluency with AI that far transcends anyone else at those organizations. Likewise, Sam Altman, CEO of OpenAI emphasizes that AI will make employees more productive, leading to a positive sum game.

Powering every AI output is an intricate mosaic of human knowledge – knowledge created by countless professionals, creators, and experts. By leveraging this vast mosaic, AI can complete routine tasks such as writing reports, summarizing corpora, and drafting presentations in seconds. But the AI that powers these tasks must be told what to do and are then judged on how they did. The “ghosts in the machine” are not alive and they lack human values such as empathy, fairness, dignity, and autonomy. The AI excels at the middle work. Being fluent with AI will mean knowing how to interact with these tools by providing the inputs and knowing how to interpret and use the output.

This idea runs through the PwC 2025 Global AI Jobs Barometer, which analyzed nearly a billion job postings. They found that industries using AI report three times higher productivity growth and that professionals with AI skills commanded a 56% wage premium over those without AI skills. The message is clear: AI adoption is less about job displacement, and more about AI augmentation where workers shift from routine tasks to strategy, oversight, and problem solving. Human+AI teams outperform either individually.

The Higher Education Crossroads

The challenge for higher education is how do we meet this new and fast-growing market requirement, especially when constrained by the traditional academic bureaucracy?  As a simple example, how can we justify teaching marketing students the same way in a world where Meta plans to automate its online advertising business? Short-sighted thinking places us on the path to our own obsolescence. The alternative view is focusing on the needs of the student. A recent study showed that AI tends to complement human skills like digital literacy, teamwork and resilience far more than it could substitute for them, and that employees who embraced this collaboration experienced wage gains.

Student-centric thinking highlights that graduates need more than domain specific know-how; they require AI fluency and experience in applying AI in their domain. Meeting this requirement means approaching our educational mission with a different mindset. First, we need to embrace AI and AI tools in the educational process. This ensures students get the needed experience, which provides a new and strong argument for increased experiential learning. Second, we need to consider curricula revisions to prepare students for this AI augmentation of existing careers and new careers that arise from increased adoption of AI.

This means reimagining business education. Rather than a focus on the mastery of tasks, we must focus on the partnership between human and AI that can lead to better outcomes for all. By confronting this challenge, we can transform the ghosts in the machine from harbingers of doom to partners in a brighter future.