Reputation In The Age Of AI: What Business Schools Must Teach Tomorrow’s Leaders

When Warren Buffett quipped that it takes 20 years to build a reputation and five minutes to ruin it, he could hardly have imagined a world where reputations are being rewritten and swayed not by journalists or accreditors but by algorithms. Yet this is precisely the reality business schools and the leaders they train must now confront.

Generative AI has become a massive reputational gatekeeper. As of July 2025, ChatGPT alone had 800 million weekly active users, handling nearly 2 billion queries daily. In this new paradigm, consumers are replacing traditional search behaviors by conversations with Gen AI tools which whom they chat about the best product/service to buy. This shift reveals a new reality: reputation is no longer mediated solely by humans. Increasingly, it is curated, scripted, and steered by machines.

FROM HUMAN-MEDIATED TO AI-REFORGED REPUTATION

Traditionally, institutions have built reputation on three building bricks:

• Signals, that is, observable indicators like rankings, accreditations, or citation counts. Signals generate social proof that speak to the institution’s unique position and difference (e.g., being the best school for entrepreneurship) .
• Stories, which are the narratives that schools tell about themselves: alumni achievements, campus histories, origin myths. They greatly hep to stick the school’s position in the memories of core audiences.
• Sentiment, that people’s reactions (good or bad) reflecting feelings about a school. Partly shared by media tone and word-of-mouth, they can quickly trigger spark changes in one’s reputation.

In the AI era, these pillars are no longer fully under institutional control:

• Signals are curated by AI. Your rank on AI – and how the model contextualizes it – is an increasingly important basis on which people judge and decide their educational journeys.
• Stories are scripted by AI. Narrative ownership shifts from schools to algorithms piecing together fragments of data.
• Sentiment is steered by AI framing. Depending on prompts, sources, and its own
  “understanding” of these sources, a model might amplify trust or suspicion.

This is the new world of AI-reforged reputation.

WHY THIS MATTER FOR BUSINESS EDUCATION

For schools, the stakes are existential. Students and employers are increasingly asking ChatGPT, Gemini, or DeepSeek where to study, how to upskill, which companies to join, or which brands to trust. If an institution’s signals, stories, and sentiment are absent from or misinterpreted by the data ecosystem that large language models draw upon, it risks invisibility or misrepresentation.

Consider how prospective students now search. A generation ago, they might have typed “best MBA for finance” into Google and received a ranked list. Today, they ask: “Which MBA will best prepare me to become a CMO in Europe and Asia?” The AI’s answer is not just a list. It is a curated explanation of strengths and weaknesses. Visibility, and even perceived identity, hinge on how effectively schools embed their proof and narratives into the AI’s knowledge base.

The lesson is clear: strategies that once burnished reputation may no longer work and may even backfire if institutions do not adapt to machine interpretation.

LESSONS FOR SCHOOLS

• Arm the AI with Proof. Ensure rankings, accreditations, achievements and other structured data are embedded in the public datasets AI pulls from. If models cannot access your signals, your legitimacy will not surface.
• Seed the Narrative. Share alumni case studies, transformation stories, and faculty thought leadership widely. These are the building blocks AI uses to script reputations.
• Monitor Machine Sentiment. Just as schools track social media chatter, they must now track what AI systems say about them and actively engage to shape perception.
• Audit and Control Content. In the Google era, visibility was shaped mainly by paper and text. In the generative AI era, models draw equally from video, audio, and written material. Schools must systematically audit the content ecosystem around them to ensure that their narrative is consistent, accurate, and discoverable across every medium.

LESSONS FOR STUDENTS

Tomorrow’s executives will face reputational battles on two fronts: human perception and AI-mediated framing. Recruiters are already using AI to filter résumés, customers are asking algorithms which brands to trust, and even personal credibility is being shaped by what models surface online. A single offhand joke once posted on LinkedIn or Twitter may resurface in an AI-generated summary years later, reminding us that the internet never forgets. Learning how to seed, curate, and monitor reputation in this algorithmic age will be as essential as mastering finance or strategy. 

Just as schools must embed their proof and stories into the data ecosystem, students must do the same for their professional journeys, from LinkedIn profiles to articles, podcasts, and public speaking. Evaluating schools, therefore, is no longer just about curriculum or cost. It is also about how well institutions prepare leaders to navigate and leverage AI-driven trust.

THE FUTURE OF BUSINESS EDUCATION

Reputation is no longer only what you say or what others feel. It is also what AI believes and tells the world. For schools, that means reputation management increasingly need to pay attention to their visibility and perceptions on LLMs. For students, leadership training must include mastering AI-mediated trust.

The schools that win will not be those with the flashiest campaigns, but those whose reputations are legible to both humans and machines. The leaders who thrive will be those who can manage trust in two arenas at once. With Google, we learned to shape visibility through SEO. With generative AI, the rules are not yet written. Business education must rise to this new frontier or risk being left behind.

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David Dubois is an associate professor at INSEAD with a focus on AI and data-driven innovation and transformation around the customer. Benjamin Stevenin is special adviser to Poets&Quants and former Director of Business School Solutions and Partnerships at Times Higher Education.

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