University Of Phoenix And OpenAI Could Redefine The AI Skills Gap

Consider three individuals vying for a place in a baking contest. One has ample time and resources at her disposal, while another juggles caregiver duties for an elderly relative, and the third manages a full-time job and child-rearing. Despite their differing circumstances, all three are expected to demonstrate proficiency in their culinary skills on the day of the competition.

The judges will evaluate the final products, not the preparation process, and the "skills gap" between the contestants is not a uniform phenomenon. Now, let us substitute the baking contest with the acquisition of AI proficiency for the workplace. Employers seek individuals capable of integrating AI into their workflows, exploring new agentic tools, assessing the quality of AI-generated outputs, and determining the genuine value AI can bring to their tasks.

Mastering these skills, much like baking, requires ample practice, repetition, and the freedom to make mistakes. However, not all employees have the luxury of carving out time for such learning. Some possess more free time after work than others, and this disparity can widen the skills gap. Yet, the groups experiencing this gap are not homogeneous.

A woman with no caregiving responsibilities, one caring for a parent, and a working mother are not identical, and they may not lag behind to the same extent. The University of Phoenix's recent partnership with OpenAI promises to shed light on this issue. The collaboration aims to investigate AI adoption across various demographics, including gender, caregiving status, career stage, and industry.

By analyzing differences in AI adoption among these groups, the research could reveal whether the skills gap reflects a true lack of ability or merely a lack of time to practice. Crucially, the study could pinpoint which demographic—women in general, caregivers in general, or working mothers specifically—exhibits the widest gap.

While the collaboration builds on existing faculty training and AI competencies, the true value lies in understanding how these skills translate into real-world applications. As AI becomes increasingly prevalent in the workforce, the need for AI fluency is more pronounced than ever. It is not just about knowing a particular tool but comprehending the broader application of AI within a job.

Researchers must observe how AI can expedite certain tasks, introduce privacy or security concerns, and when human intervention is still necessary due to factors such as empathy, judgment, or accountability. The 2026 Stanford AI Index indicates a growing demand for AI skills, with mentions of AI appearing in 2.5% of U.S. job postings, a 55% year-over-year increase.

Agentic AI skills, in particular, have surged more than 280%. However, the available data mostly focuses on gender, neglecting the broader picture. To truly understand the skills gap, researchers must isolate working mothers from other groups and examine how access to AI tools affects their adoption and performance. The collaboration's significance lies in its focus on a largely working adult student population at the University of Phoenix, where the average new student is 38 years old, with 62% employed and 70% being women.

Nevertheless, the experiment faces challenges in workplaces that remain unchanged. If employers do not adjust their hiring and promotion practices to accommodate these findings, the skills gap may persist, even as the gap in career mobility remains unchanged.