Tech, Business, and Education Belong Together, Leaders Agree
Cornell leaders discuss AI at Cornell Convenes; from left to right, Karan Girotra, Andrew Karolyi, Thorsten Joachims, Paul Krause, and Greg Morrisett
On June 18, the Cornell SC Johnson College of Business, Cornell Tech, and the Cornell Bowers College of Computing and Information Science hosted Cornell Convenes: The Race to Keep Pace with AI, an in-person roundtable of academic and business leaders exploring the transformative potential of artificial intelligence (AI) for business and society.
Meeting at Cornell Tech in New York City, Cornell faculty and deans engaged with chief corporate AI and technology officers in multiple sessions on AI advancements and implications. Expert presentations were followed by open discussion and Q&A, observing the Chatham House Rule, allowing participants to share information without attribution.
“The way information is generated, communicated, and understood will require incredible facility in us today and in the future leaders we’re educating,” opened Andrew Karolyi, Charles Field Knight Dean of the Cornell SC Johnson College of Business. “Their AI literacy, problem solving ability, communication skills, and creativity will be increasingly important as they grow into a new kind of workforce.”
The day started with reporting on AI progress in cognitive capabilities and embodied applications, like prostheses and robotics. Then the discussion turned to exploring transformations—in access to products and services, productivity, new business strategies, and business models. The event closed with a focus on education and preparing students to meet emerging needs.
The Collaboration Imperative
All present agreed that neither academia nor industry can tackle AI’s complexities alone. Universities possess the structural freedom to explore long-term, uncertain questions—the kind of foundational research that led to today’s language models. Meanwhile, industry brings practical implementation challenges, real-world data, and immediate application needs.
As one panelist noted, “Companies want results in six to 12 months,” while academic research operates on longer time frames. This tension creates opportunity: Cornell’s research institutes and centers are designed to bridge this gap, delivering applicable insights within industry schedules while maintaining academic rigor.
Institutions like Cornell also offer crucial support in designing AI-native business architectures, especially in regulated industries like healthcare or finance. Karan Girotra, Charles H. Dyson Family Professor of Management at Cornell Tech and the SC Johnson College of Business, pitched the industry members in the room, “What questions does your organization need to tackle? What are the data sets you’d like to see analyzed?”
Greg Morrisett, Jack and Rilla Neafsey Dean and Vice Provost, Professor of Computer Science, thanked the attendees for their candor, which “helps us better understand the evolving needs of industry. As we shape our academic programs and research priorities, your input is essential to ensuring that our graduates are not only technically strong but also ready to contribute meaningfully from day one.”
Beyond Technology: Human-Centered Innovation
Recognizing AI’s potentially profound impacts, researchers presented findings showing that AI can measurably affect belief systems, even debunking conspiracy theories, while they also warned that over-reliance on automation could erode worker independence and agency. AI can undermine credibility and trust in human intuition.
Attendees reflected that automation does not equal progress. Tasks like conversation, craftsmanship, and mentorship require the intrinsic value of human experience and perspective. “Sometimes people just get value out of doing a task—even if it could be automated,” observed a faculty panelist, highlighting the need for thoughtful integration of AI tools. Wholesale replacement of human judgment is not recommended.
Ultimately, said one participant, “The real challenge isn’t technology—it’s leadership.” Senior executives often misunderstand what AI can and cannot do. Organizations face a change management imperative—technical gains must be paired with structural adaptation, talent reskilling, and leadership transformation. Like the steam engine or assembly line, AI demands rethinking how work is organized. “Every business should be a lab,” said Girotra. “Every leader should be a scientist.”