For Hasan Pasha WEMBA’26, the Mack Institute’s Collaborative Innovation Program (CIP) offered a chance to apply classroom ideas to a real business challenge. The experiential learning course pairs Wharton students with corporate partners to tackle complex problems and develop innovation strategies.
Pasha entered Wharton after more than two decades working across consulting, hardware product design, and technology. Before coming to Wharton, he worked at Apple and is currently developing a startup venture focused on commercializing hydrogen storage technology patented by the University of Hawaii.
At Wharton, he found himself drawn to projects that could bridge classroom ideas with real-world implementation.
“I’m very passionate about taking ideas from the classroom and seeing how I can operationalize them,” he said. “Not only does it help me internalize the material that I learn in the classroom, but it also helps me put those ideas into practice.”
That focus led him to CIP, where he joined a team working with Tata Communications, the India-based global communications technology company, on a project exploring how agentic AI could support high-stakes operational decisions during disruptions such as port closures or sudden spikes in fuel prices.
Beyond a Technical Problem
Tata Communications asked the team to study how agentic AI could help reduce “capital drag” in the container shipping industry: inefficiencies created when assets, inventory, or shipping containers sit idle or move inefficiently through the system.
At first glance, the project appeared to be a technical AI challenge. But the team quickly realized the problem extended far beyond logistics optimization.
“Initially, we thought the problem was purely financial or operational,” Pasha said. “But soon we realized that it was fundamentally a multi-stakeholder coordination problem.”
In large shipping companies, different teams respond to disruptions in very different ways. Operations teams prioritize flexibility and service continuity. Finance teams focus on reducing idle capital and protecting the balance sheet. Commercial teams care about customer relationships and revenue.
“They often operate with completely different incentives,” Pasha explained. “Even their time horizons differ. Operations teams focus on weekly and monthly realities, while finance teams focus on quarterly and yearly performance.”
The team’s breakthrough came when they reframed the problem entirely.
“We stopped thinking about the problem as an optimization problem and started thinking about it as a coordination problem,” Pasha said. “That shift changed everything.”
Modeling Multiple Perspectives With AI
Based on that insight, the team developed and demonstrated an agentic AI tool capable of modeling different stakeholder perspectives simultaneously. Rather than producing a single “correct” answer, the tool was designed to help users evaluate tradeoffs across competing priorities.
“We created different AI agents representing different stakeholders in the company,” Pasha said. “Each one evaluated potential responses differently.”
The system generated multiple possible actions and displayed the tradeoffs between them. Pasha described this as a newer form of AI that can represent multiple stakeholder perspectives, reason through tradeoffs, and support human coordination alongside automation.
“We built what’s called a Pareto frontier,” Pasha explained. “One axis represented operational priorities, and the other represented financial priorities. We could show the best possible outcome for operations, the best possible outcome for finance, and then multiple balanced options in between.”
The goal was not to eliminate disagreement, but to structure it productively.
“Our challenge was to create a shared window where different teams could make better decisions together,” he said.
Learning From Different Backgrounds
The Collaborative Innovation Program brings together students from different professional and academic backgrounds, allowing teammates to learn from one another’s experiences. Pasha said the interdisciplinary nature of his group became one of the team’s greatest strengths.
His team included Executive MBA students with backgrounds in hardware engineering, consulting, real estate, and marketing. Team members were also geographically distributed across Seattle, Washington, D.C., India, and the Bay Area.
“I’m a firm believer that diversity of thought has real business value,” Pasha said.
One teammate was a first-year student who had not yet encountered many of the frameworks the others had already studied. Rather than slowing the team down, those questions strengthened the group’s thinking.
“When someone unfamiliar with the concepts asked questions, it forced us to explain things more clearly,” Pasha said. “That ended up helping us prepare for client interviews and presentations.”
Applying Classroom Frameworks
Pasha says the project gave the team an opportunity to apply frameworks learned in the classroom to a practical setting. Frameworks from strategy and operations courses helped the group analyze the industry and structure the project, with Porter’s Five Forces serving as one of the first tools they applied.
But some of the most useful lessons came from outside the technical curriculum. Pasha pointed specifically to Professor Cade Massey’s Influence class, which shaped how the team approached communication and stakeholder engagement. Applying those strategies to meetings and communications helped the team operate with greater authority and confidence.
“As MBA students, it’s easy to default to technical frameworks,” he said. “But there’s a much broader set of tools that we learn in the MBA program.”
Rethinking the Role of AI
For Pasha, the project ultimately reshaped how he thinks about AI inside organizations.
“People often think AI projects fail because the models aren’t good enough,” he said. “But I think many projects fail because organizations don’t know how to integrate decision-making across functions.”
The experience reinforced his belief that the future value of AI may extend beyond automation alone and demonstrated how Wharton students can engage with frontier AI as a practical business capability. Pasha connected the success of the project to the “founder mindset” he is developing at Wharton.
“Start with an ambiguous technical problem, understand the human and organizational context around it, and build tools that help people make better decisions,” he said.