Executive Summary

It is a national security imperative to grow, sustain, and diversify U.S. artificial intelligence (AI) talent pipelines. But to date, the predominant focus of U.S. policymakers and industry continues to be on four-year degrees. Such a narrow focus is leaving talent behind and limiting opportunity, as many AI careers do not require a four-year college credential.

Community and technical colleges offer enormous potential to grow, sustain, and diversify the AI talent pipeline. They are a critical part of the U.S. postsecondary system with a student body that represents many segments of the population.

However, these institutions are not being leveraged effectively in educating and training AI talent. To understand the current landscape of AI and AI-related education at these institutions, we evaluated current program offerings and the associated number of graduates. We focused on programs where associate’s degrees could be a powerful source for training and upskilling AI talent.

Our analysis found:

1. Community and technical colleges awarded few AI and AI-related degrees and certificates in 2020, with virtually none in AI-specific fields.
2. Two promising technical fields for AI-related degrees and certificates, computer and information science (CIS) and engineering technologies, saw flat or falling associate’s degree attainment over the last decade.
3. Although community and technical colleges attract a highly diverse student body, in 2020, women comprised only 23 percent of graduates who earned a CIS associate’s degree or certification, and 15 percent of graduates who earned an engineering technology associate’s degree or certification.
4. In 2020, less than 7 percent of awards in business management administration and operations were in the subspecialties most related to AI product development and acquisition.
5. There is a small but growing number of promising industry partnerships specific to AI education and training at community and technical colleges.

These findings show that there is substantial room for improvement. This starts with building upon or modifying existing programs in AI-related fields, but also includes creating new programs with stackable certificates and industry certifications to meet the future demand for AI and AI-related competencies.

However, there are significant barriers that must be addressed for community and technical colleges to realize their full potential in training tomorrow’s AI workforce. This includes the persistently uncertain funding environment; low completion rates; low female and underrepresented student participation in technical programs; faculty recruitment, development, and retention challenges; and an overload of competing priorities from system administrators and state legislatures. That these institutions often serve populations more diverse than traditional four-year institutions, with a wide range of student needs, further exacerbates these barriers.

To overcome these barriers, federal, state, and industry prioritization of AI education and workforce development is needed. Such prioritization must start at the top, with a dedicated office in the White House. It must also include additional state and federal financial support to create and elevate quality AI and AI-related programming. It also requires incentives for community and technical colleges to partner with industry to design AI and AI-related programs where employers recognize the resulting credentials and use them to hire AI talent.

To help community and technical colleges realize their potential, we propose:

1. The National Artificial Intelligence Initiative Office within the White House Office of Science and Technology Policy, in coordination with the Office of the First Lady, establish a strategic line of effort related to community and technical colleges.
2. Congress establish a federal joint Department of Labor and National Science Foundation grant program for industry-institution partnerships in AI and AI-related degree and nondegree programs, including high school dual enrollment programs.
3. Congress enact federal tax credits for companies that form industry partnerships with community and technical colleges related to AI and AI-related programs.
4. Congress fund the National Institute of Standards and Technology, or other federal entity if appropriate, to conduct multi-stakeholder collaboration to develop a framework of technical and nontechnical AI work roles and competencies, updated regularly.
5. U.S. states facilitate articulation agreements between public two-year and four-year institutions for transfer and reverse transfer for AI and AI-related programs.

Creating AI and AI-related programs as a series of stackable credentials–– nondegree certificates that demonstrate a skill or competency––will transform how community and technical colleges prepare tomorrow’s AI workforce. First, it will promote lifelong learning by facilitating acquisition of new skills at any time. Second, it will enable agility in program offerings in a rapidly changing skills landscape. Third, it will encourage the mixing and matching of credentials for the unique blend of skills and competencies that matches an individual’s interests, aptitude, and employment marketability. This would provide accessible and affordable education and training options not readily available elsewhere in our education system. Institutions could design programs using promising practices and lessons learned from states offering stackable credentials in other fields, such as in Ohio.

We have a vision where community and technical colleges become a core part of educating and training AI talent in the United States. They will reach underrepresented and nontraditional college populations, and provide new avenues of access and opportunity to a key segment of tomorrow’s high-wage jobs. However, they cannot do this alone. Working with federal, state, and industry partners, we believe it is possible for community and technical colleges to create a truly viable alternative pathway for AI careers.