Research Coordination Network on Assessing and Predicting Jobs Outcomes in AI (RCN APJO-AI)

NSF Award Search · 01002526DB NSF RESEARCH & RELATED ACTIVIT · $499,983 · view on nsf.gov ↗

Abstract

The Assessing and Predicting Job Outcomes in AI (APJO-AI) research coordination network (RCN) will establish a national network across sectors, disciplines, and organizations focused on assessment of the current state of AI jobs and to predict future trends, in order to contribute towards a strong national economy given that AI is reshaping nearly every sector of society. There is a pressing national need to build a workforce equipped with AI skills and knowledge to meet emerging challenges. The APJO-AI network will focus on the core questions of (1) What defines an “AI job”? (2) What skills are needed for “AI jobs”? and (3) How do we build AI credentials and curricula? Given that the field of AI and the AI marketplace are rapidly evolving, ongoing assessments will be conducted of these core questions. The ability to predict trends in the AI job market will provide essential insights on expanding opportunities in this space and for strengthening the national AI infrastructure. The APJO-AI RCN will be guided by a Steering Committee consisting of individuals with expertise in AI across the range of K-12 education, higher education, workforce development, industry, and entrepreneurship. The network will bring together stakeholders across sectors, disciplines, and regions through coordinated activities including workshops, convenings, and public knowledge-sharing platforms. By convening stakeholders from academia, industry, and government, the RCN will generate knowledge and t

Key facts

NSF award ID
2537092
Awardee
Howard University (DC)
SAM.gov UEI
DYZNJGLTHMR9
PI
Talitha Washington
Primary program
01002526DB NSF RESEARCH & RELATED ACTIVIT
All programs
—
Estimated total
$499,983
Funds obligated
$499,983
Transaction type
Standard Grant
Period
10/01/2025 → 09/30/2027