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

Howard University, Washington DC

Investigators

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 the corresponding frameworks to help understand AI-related workforce trajectories. The network will produce synthesis reports, workshop proceedings, curated labor data dashboards, and a public-facing knowledge base website. Information captured from RCN activities will also be shared through the website, press releases, and targeted email listservs to maximize reach and impact. The RCN will generate timely insights into the state of AI jobs and AI job trends to assist in building a stronger AI workforce. The reports, analyses, and other products generated by the network will help guide employers, academic leaders, and decision-makers in aligning curriculum design, hiring practices, and workforce strategies with real-time skill needs, resulting in a robust AI-enabled workforce. The project will be evaluated based on the Results-Based Accountability (RBA) framework that serves to assess both the quantity and quality of the RCN’s activities and outcomes. The evaluation will provide ongoing feedback to inform project decision-making and improve the project as it progresses. The APJO-AI RCN provides a foundation for sustained national engagement to inform future directions in AI workforce development and to develop strategies for expanding national capacity in AI. Drawing on input from educators, industry leaders, government agencies, workforce innovators, and the broader public, the RCN will accelerate the development of strategies to strengthen the nation’s ability to respond to emerging AI workforce needs through public-private partnerships. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.