Evaluating AI Proficiency in the Workforce Through Cross-Industry Analyses of Credentialing Programs

Session Number

2

Advisor(s)

Alvin Chin, University of Illinois- Chicago

Location

A147

Discipline

Computer Science

Start Date

15-4-2026 11:10 AM

End Date

15-4-2026 11:55 AM

Abstract

This project examines the alignment between artificial intelligence credentialing programs and the practical application of AI across major industries, including education, healthcare, technology, transportation, finance, manufacturing, agriculture, and energy. As AI tools become increasingly integrated into professional environments, the demand for standardized training and certification has grown significantly. However, a potential gap may exist between the skills these programs advertise and the competencies actually required in the workplace. To investigate this, we reviewed credentialing programs offered by leading institutions and technology companies, such as Johns Hopkins, MIT, Berkeley, DataCamp, Coursera, IBM, and Google Cloud, focusing on the skills they claim to develop, including Machine Learning, Responsible AI, and Natural Language Processing. We will also analyze government and industry reports to assess how AI is currently being deployed across our focus sectors. Additionally, we will conduct a survey of professionals to measure their confidence in using AI tools, determine whether they have completed any credentialing programs, and evaluate how well those programs prepared them for professional application. Human participants will be protected through informed consent and anonymized data collection. The findings will allow us to identify gaps in existing training curricula and offer recommendations for improving AI literacy and workforce readiness.

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Apr 15th, 11:10 AM Apr 15th, 11:55 AM

Evaluating AI Proficiency in the Workforce Through Cross-Industry Analyses of Credentialing Programs

A147

This project examines the alignment between artificial intelligence credentialing programs and the practical application of AI across major industries, including education, healthcare, technology, transportation, finance, manufacturing, agriculture, and energy. As AI tools become increasingly integrated into professional environments, the demand for standardized training and certification has grown significantly. However, a potential gap may exist between the skills these programs advertise and the competencies actually required in the workplace. To investigate this, we reviewed credentialing programs offered by leading institutions and technology companies, such as Johns Hopkins, MIT, Berkeley, DataCamp, Coursera, IBM, and Google Cloud, focusing on the skills they claim to develop, including Machine Learning, Responsible AI, and Natural Language Processing. We will also analyze government and industry reports to assess how AI is currently being deployed across our focus sectors. Additionally, we will conduct a survey of professionals to measure their confidence in using AI tools, determine whether they have completed any credentialing programs, and evaluate how well those programs prepared them for professional application. Human participants will be protected through informed consent and anonymized data collection. The findings will allow us to identify gaps in existing training curricula and offer recommendations for improving AI literacy and workforce readiness.