Adopting AI Means Adapting Business Models

Alumni, faculty, and business leaders gathered on the Cornell Tech campus in New York City on March 15 for the 2025 Cornell Executive MBA Alumni Summit, hosted by the Samuel Curtis Johnson Graduate School of Management, to explore one of the most pressing issues in business today: the adoption of AI.

While AI has been a buzzword for years, this year’s summit challenged attendees to move beyond the hype and examine how the technology is fundamentally reshaping industries.

The discussions centered on how AI is forcing organizations to rethink traditional structures, redefine leadership, and solve problems in innovative ways.

The missing piece in the AI revolution

Karan Girotra, the Charles H. Dyson Family Professor of Management and professor of operations, technology and innovation at Cornell Tech and the Cornell SC Johnson College of Business, delivered a sharp critique of how businesses are currently approaching AI. Girotra delivered his remarks following updates on the state of the SC Johnson College from Andrew Karolyi, Charles Field Knight Dean of the college, and on the state of the Executive MBA programs at the Johnson School by Vishal Gaur, Anne and Elmer Lindseth Dean of the Johnson School.

While AI’s capabilities have surged, Girotra argued that most companies are failing to harness its full potential in meaningful ways. “We haven’t created just one Einstein; we’ve created millions, and they work for almost nothing,” he said, emphasizing AI’s unprecedented scalability and cost-effectiveness. Yet rather than rethinking their business models, most organizations are engaging in what he called “innovation theater”—highly visible but ultimately superficial AI initiatives. “Most organizations aren’t actually changing the way they work. They’re adding AI like a decoration, not an engine,” he said.

Girotra highlighted a critical misalignment between AI’s capabilities and how businesses are structured. He compared the current AI wave to the Industrial Revolution, explaining that while the steam engine revolutionized industry, its full impact wasn’t realized until companies completely overhauled their production and management systems. “The missing piece in the AI revolution isn’t smarter AI,” he said. “It’s leaders who know how to restructure their businesses around it.”

He pointed to decision-making as a key area where AI’s potential is being underutilized. Many executives still rely on intuition or outdated models rather than leveraging AI’s ability to process vast amounts of data with greater accuracy and speed. “This isn’t just about replacing tasks—it’s about augmenting human capabilities at a scale we’ve never seen before,” Girotra said. AI has the ability to reshape how organizations make strategic choices, but only if leaders are willing to trust and adapt to data-driven decision-making.

Another fundamental shift, Girotra argued, is the role of expertise in organizations. Traditional corporate structures place decision-making power in the hands of senior leaders with years of experience, but AI can democratize expertise by providing real-time insights that are accessible at all levels of an organization. “AI allows us to scale expert decision-making in a way that was previously unimaginable,” he said. “The companies that embrace this shift will gain a massive advantage.”

Girotra also discussed AI’s evolving role in problem-solving, describing how modern AI models go beyond simply analyzing past data. Thanks to recent advancements in reasoning and planning, AI can now generate complex, multi-step strategies and iterate on them—essentially mimicking human decision-making processes at an accelerated rate. He illustrated this with a personal example: Instead of spending hours researching and comparing different camera models for a purchase, Girotra used an AI-powered search agent that compiled product specifications, aggregated user reviews, and made a recommendation in minutes. “What used to take me two hours now takes two minutes,” he said. “AI doesn’t just provide information. It makes decisions more efficient.”

Despite AI’s transformative potential, Girotra noted that many organizations struggle with meaningful integration. Companies eagerly adopt AI-powered tools but often fail to rethink fundamental processes. “The organizations that will benefit the most from AI aren’t just automating old workflows; they’re reimagining them entirely.” He warned that without this deeper structural change, businesses risk treating AI as a short-term efficiency play rather than a long-term strategic asset.

He also addressed a common concern: whether AI will replace human jobs. He argued that while automation is inevitable, the real opportunity lies in AI enhancing human work rather than replacing it. “This isn’t just automation—it’s augmentation at an unprecedented scale.” Companies that invest in AI not just as a tool but as a foundational part of their business strategy will be the ones that thrive.

AI’s challenges in healthcare and organizational decision-making

The theme of AI’s potential versus real-world application extended beyond business strategy. Geraldine McGinty, MD, professor of radiology at Weill Cornell Medicine, highlighted AI’s promise in healthcare, particularly in diagnostics and clinical documentation. However, she pointed out that adoption remains slow due to regulatory challenges, data privacy concerns, and a lack of alignment with existing healthcare payment structures.

“The technology is ready, but the [applications] aren’t,” McGinty said. While AI-powered tools could free doctors from administrative burdens, she cautioned that healthcare leaders must actively shape AI’s integration rather than wait for regulations to catch up.

Elizabeth McClean, associate professor of management and organizations at the Johnson School, focused on another critical issue: bias in AI-driven decision-making. While AI has the potential to improve fairness in organizational processes, it can also reinforce existing inequities if not carefully designed and monitored, she warned. “AI is only as unbiased as the data it’s trained on,” she said. “If we don’t correct for historical inequities, we risk codifying them into our decision-making processes.”

Moving beyond AI hype

The discussions throughout the summit made one thing clear: AI is not just a trend: It’s a fundamental shift in how businesses operate. But, as Girotra emphasized, simply adopting AI tools isn’t enough. To fully harness its potential, organizations must undergo deep structural changes.

The key takeaway from the summit was that AI isn’t just about making businesses smarter; it’s about making them more scalable, efficient, and adaptable. The real revolution isn’t in the technology itself, but in how leaders choose to wield it.