Want To Jump-Start AI? Leverage Students

When COE Distributing was hunting for the ideal location for its next office-furniture distribution center, the company turned to data. CEO James D. Ewing Jr. tapped a team of data analytics students from the Katz Graduate School of Business at the University of Pittsburgh, who worked on the site selection for three months.

“They took into account multiple bits of information: distribution space, cost of distribution space, customer concentration, cost of logistics and so on,” explains Ewing. After a three-month review, they chose a location in Houston, down to the block. The company leased a building that spans a quarter of a million square feet.

AI is going to be a game changer. Currently, only 3.9 percent of companies report they are using AI, according to the U.S. Census Bureau. But 6.5 percent report they plan to use AI in the next six months.

$10,000 Per Semester

After his successful experiment, Ewing next tasked students to use AI to forecast which products would be most successful, leveraging predictive analytics. That positioned his company as one of the more forward-thinking in AI application, especially for a Pittsburgh-based office furniture company.

Ewing, for his part, funded the class with $10,000 per semester. For far less than a consultant would cost, he has been able to launch impactful projects while giving these students real-world business challenges to apply their data analytic talents. This approach allows companies to test AI solutions affordably.

Data Analytics Department

Given the challenge of finding trustworthy AI consultants, why not leverage a class of students? You’re unlikely to find an “AI department” at your local university, but university data analytics classes can provide companies with an affordable entry point into AI.

Taking a page from COE Distributing, my firm, Scaling Up, has turned to Harvard’s Engineering Sciences 139: Innovation in Science and Engineering class, which has an AI focus. The students create ventures around a product ecosystem for executive coaching tools we’ve proposed. They build demos and conduct research, culminating in a final showcase. Shuya Gong, who helps lead the class, is always looking for additional projects.

There is likely a professor at your local college or university looking for similar projects for their students. Reach out to them.

Off-the-shelf solutions: Eliminate “administrivia.” Companies can start small with student-led data analytics projects, scale to specific solutions and, ultimately, build in-house AI capabilities. For instance, when Ewing found AI was helping him to run his company more efficiently, he brought in an AI solution called Olivia, which was created in partnership with Forethought but has since been brought in-house for additional development. During the pandemic, his staff spent countless hours tracking down answers on product availability—questions customers wanted answered instantly. Olivia became a smart AI bot that could handle inquiries regarding inventory availability and order updates efficiently. “This is still pretty new for us, but it has been met with a wonderful reception,” says Jennifer Jubin, VP of customer experience for COE.

Hire a few students to build AI capability in-house. After several projects, Ewing went a step further and hired several of the students, creating an internal data analytics and AI function. He’s now using AI tools in various parts of the business, particularly with the design team. They can use AI to predict trends, such as which wood colors and designs will become popular. AI generates the photos, designs the furniture and avoids the need for physical mockups and photo shoots, speeding up the process significantly.

Don’t put it off. We’re all feeling our way in AI. Universities are an excellent place to start exploring, and every company—especially scale-ups—should consider the type of partnership COE Distributing worked out with the University of Pittsburgh.