There is near constant talk about a disconnect between what colleges are teaching and what employers want graduates to know. 

Industry advisory committees are the standard way community colleges try to bridge that gap. Yet these committees have historically acted as a rubber stamp for the curriculum proposed by faculty members, says Ann Beheler, director of innovation at the Center for Occupational Research & Development. 

More than two decades ago, Beheler developed the Business & Industry Leadership Team (BILT) model to make industry-higher education partnerships more productive. 

Miami Dade College’s artificial intelligence (AI) programs exemplify the BILT model in action. 

Antonio Delgado Fornaguera, vice president of innovation and tech partnerships at MDC, scoured the nation for AI experts who would be willing to meet and answer two key questions:

  • “What are the knowledge, skills, and abilities that businesses need?”
  • “How do we translate that into academia?”

Unlike a traditional advisory committee, MDC didn’t present a curriculum for members of the BILT team to review. The model instead requires institutions to provide a list of knowledge, skills, and abilities (KSAs) that may be required for a career in the field the program is addressing; in this case, AI. BILT members meet in person and rate how important each KSA is expected to be in 12 to 36 months, on a scale of one to four. 

“This is flipping the model,” Fornaguera says. “They are the ones talking; the academic side is mostly listening and not talking.”

Under the BILT model, faculty then compare the KSAs rated most important to what is already included in their curriculum. This helps identify the gaps in instruction, and academics later return to the committee to explain how they will address KSAs not already covered in the existing program. 

BILT helped MDC determine what math concepts should be required for its AI programs, Fornaguera says. The faculty discovered that while calculus isn’t necessary, students should graduate knowing matrices, regressions, and algebra.

This helped create a more optimized program, he says.

Anshul Sonak, principal engineer at Intel Corp., says that without direct industry input, employers typically must spend months training employees on key KSAs after they’ve been hired.  

“The cost of inaction is huge,” Sonak says.

Community colleges provide the safest ground to address missing skillsets and abilities, he says. It takes less investment from businesses and two-year institutions have the flexibility to move quickly. It’s for this reason that Intel supplies an AI for Workforce Program model that includes content, training and support for community colleges and vocational schools across the U.S. 

Still, while national standards are helpful, the BILT model thrives under local partnerships, Beheler says. BILT committees should be made up largely of high-level technical executives and first-line hiring managers from local businesses, because they are most in tune with the skills graduates will need to thrive in that region. 

“I want the busiest people on the cutting edge of tech,” she says. 

Those experts, however, are often crunched for time. The BILT model tries to accommodate that by adhering to a strict meeting format to ensure committee members can discuss each KSA and rate how necessary each is within a two-hour window. Altogether, BILT members only need to devote four to five total hours across three to four annual meetings, Beheler says. 

The standardization and structure of the BILT model is what makes it so effective, Shalin Jyotishi, managing director of New America’s Future of Work and Innovation Economy initiative, says. Conversely, it is often the informality of traditional advisory committees that leads to shortfalls in the curriculum. 

But BILT still isn’t standard practice in part because of the time and money required. Recruiting and rallying industry partners takes resources that faculty and administrators may be hesitant to redirect, and the entire process takes up faculty time that might otherwise be spent working directly with students. 

“All of these things require resources, and most community colleges are under-resourced,” Jyotishi says. “Capacity building is a distinct kind of investment.”

Beheler, however, says the approach is about being more focused with the time and resources colleges are already spending on advisory board meetings, which many states require by law. While the BILT model requires more intentionality, she says, it’s not drastically more expensive than running an advisory council—and AI tools can help lessen the administrative burden. 

“You’re going to do it anyway,” she says, “so whatever cost you have in that is already done.”

Some colleges that have embraced BILT have added efficiency by running committees for a large number of programs, and then hiring an administrator to coordinate meetings and facilitate evaluations across the various committees. 

National committees, like one started by Miami Dade College, could also be more cost-effective for community colleges, though they lack regional specificity about skills. Following the success of its certificate, associate, and baccalaureate programs in AI, MDC co-launched the National Applied AI Consortium (NAAIC) and created a BILT committee filled with AI leaders across the nation, including Microsoft, Intel, and Lenovo. Rather than responding to regional workforce demands, the broader committee identifies KSAs that can be applied to community colleges in all 50 states. 

Emerging AI programs can use NAAIC’s course syllabi, workshop recordings, and KSA framework to launch without needing to start their own BILT committee. 

It’s a good first step, Fornaguera says.

Without partnering with local businesses, though, a college program may teach the skills students need, but not develop the employer relationships that lead to the internships and other opportunities that allow students to graduate with work experience.

At the end of the day, BILT is as much about connections as it is curriculum.