Date of Award

Spring 5-10-2025

Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)

Department

Economics

First Committee Advisor

Andrew Crawley

Second Committee Member

Todd Gabe

Third Committee Member

Caroline Noblet

Abstract

The first section of this research develops a systematic framework to understand how to categorize the complex evolving research agenda related to artificial intelligence (AI) through a bibliometric approach. In doing so, this assesses and understands the core AI research areas and their evolution. This paper finds that AI research has grown exponentially over the past decade, moving from a niche research area of computer science to an emerging domain across many academic disciplines. Through its growth, AI research and the ecosystem of Ai research has become a conjoined amalgamation of technologies and applications.

The second section of this research conducts a regional analysis of AI skill demand in U.S. states using job postings data from 2011 – 2022. AI skills are defined in a novel manner via a bibliometric analysis of AI related publications developed in section one of this research. This research seeks to explore the market introduction and diffusion of AI technology to understand regional differences in AI skill demand as well as the evolution of AI skill demand between 2011 – 2022. The findings reveal that unique regional patterns for AI skills have emerged over the last decade, creating labor market challenges. More specifically, it finds that AI skills demand remains relatively clustered throughout the U.S. Additionally, this research provides insight into how cutting-edge AI research eventually leads to changes in the demand for different labor skills.

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