AI-Driven Education, Careers, and Entrepreneurship for a Transformed Tomorrow

Abstract

In this in-depth exploratory case study of artificial intelligence (AI), the researchers applied a scaled, reactive, and parallel approach relating to education, employment, and entrepreneurship, wherein the data from the previous case study was used to inform the next of three case studies. Dissimilar to what was supposed from extant literature, the results revealed that AI may support learning without escalating biases or inequities. Increased and continued learning occurred within two weeks of the first pilot.The findings contribute to the resourcing literature by unveiling the capability to apply AI-driven data to boost an increase in behavioral learning, whether classical, operant, or observational. Specifically, the data shows that underperforming students, those lagging on standardized tests, and those of lower income levels can increase their learning when offered individualized and adaptive learning tailored to distinct needs, preferences, and abilities. The change is due to increased purposive attention that is AI-driven and maintains learners' interests through an avatar. This study shows how AI progress, particularly scaled, reactive, and parallel AI, can lead to new tools and services for advancements that impact performance support, employment trends, corporate learning, and professional development. Also, the study shows that AI-driven education can improve job prospects and career growth, benefiting learners, academics, and practitioners. This exploratory research results inform widespread AI implementation, fostering educational and career synergies.