Sarcouncil Journal of Applied Sciences Aims & Scope

Sarcouncil Journal of Applied Sciences

An Open access peer reviewed international Journal
Publication Frequency- Monthly
Publisher Name-SARC Publisher

ISSN Online- 2945-3437
Country of origin-PHILIPPINES
Impact Factor- 3.78, ICV-64
Language- English

Keywords

Editors

Artificial Intelligence, Education, and Economic Growth: Evaluating Government Strategies for Workforce Readiness and National Development in America

Keywords: Artificial intelligence policy, workforce readiness, educational technology, economic development, human capital theory, national AI strategy, digital equity, labor market disruption, reskilling, STEM education.

Abstract: The accelerating integration of artificial intelligence (AI) into virtually every sector of the American economy has created both an extraordinary opportunity and an urgent challenge for national policymakers. This paper investigates the intersection of AI adoption, educational reform, and macroeconomic development, with specific attention to the strategic policy frameworks that federal and state governments have deployed or conspicuously neglected in preparing the United States workforce for an AI-transformed economy. Drawing on a multi-dimensional analytical framework that incorporates human capital theory, systems thinking, and comparative policy analysis, the study evaluates the adequacy, coherence, and implementation fidelity of existing government initiatives, including the National AI Initiative Act of 2020, the CHIPS and Science Act of 2022, and various state-level workforce development programs. The paper argues that while the United States has made measurable progress in AI research and high-skill talent development, a structural mismatch persists between elite-level AI education investments and the scale of workforce transformation needed across mid-skill, service, and manufacturing sectors. The findings reveal that government strategies remain fragmented, inequitably distributed, and insufficiently aligned with the pace of technological displacement. The paper concludes with a policy architecture model, the Adaptive Workforce Ecosystem (AWE) Framework, that proposes a more integrated, equity-centered, and continuously adaptive national strategy for AI-driven workforce readiness and sustainable economic growth.

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