Published: September 15, 2026 by Dr. Yu Chi

Generative artificial intelligence (GenAI) is rapidly becoming part of the job-search process. Students can use tools such as ChatGPT to revise résumés, tailor cover letters, prepare for interviews, explore career options, and draft networking messages. Yet access to these tools does not necessarily mean that students know how to use them effectively or responsibly.

In our recently published study, “From Literacy to Behavioral Intention: A Survey of Soon-to-Graduate Students’ Intention to Use Generative AI for Job Search Through the Technology Acceptance Model,” my coauthor Dr. Huai-yu Chen and I examined how GenAI literacy influences students’ intention to use these tools for job searching.

We surveyed 300 U.S. undergraduates who expected to graduate within 12 months. Drawing on the Technology Acceptance Model, we explored whether students were more likely to use GenAI when they perceived it as useful and easy to use. We also examined five dimensions of GenAI literacy: technical proficiency, critical evaluation, communication proficiency, creative application, and ethical competence.

Our findings showed that students with higher GenAI literacy were more likely to view GenAI as both useful and easy to use. Most importantly, perceived usefulness, not perceived ease of use, helped explain their intention to use GenAI for job-search tasks. In other words, students appeared to care more about whether GenAI could help them achieve better career outcomes than whether the technology was effortless to operate.

The different dimensions of GenAI literacy also played distinct roles. Creative application, that is, using GenAI to generate and develop new ideas, was the strongest contributor to both perceived usefulness and intention to use. Communication proficiency, including the ability to formulate effective prompts and interact strategically with GenAI, contributed most strongly to perceived ease of use.

Ethical competence made the smallest contribution across the outcomes we studied. This does not mean that ethics is unimportant. Instead, it suggests a concerning gap: students may focus on GenAI’s immediate practical benefits without giving equal attention to privacy, bias, accuracy, accountability, or the risk of misrepresenting their qualifications.

These findings have clear implications for universities, career centers, and libraries. GenAI education should move beyond technical demonstrations. Students need opportunities to practice writing and refining prompts, evaluating outputs, adapting AI-generated content, protecting personal information, and maintaining their authentic professional voice. Career-related exercises, such as critiquing an AI-generated résumé or conducting an AI-assisted mock interview, can make this instruction concrete.

As GenAI becomes increasingly integrated into recruitment and career preparation, AI literacy is becoming an essential component of career readiness. Our goal should not simply be to help students use AI, but to help them use it creatively, critically, equitably, and responsibly.