Conclusion

This study explored how business students’ AI literacy influences their intention to use AI technologies in the workplace, using students from Emory’s Goizueta Business School as a case study. It also examined three key mediators perceived usefulness, ease of use, and credibility to understand how these perceptions help transform AI knowledge into action.

The findings showed that students with higher AI literacy were more likely to see AI as useful, easy to use, and trustworthy, and thus more likely to adopt it in the future. Importantly, perceived usefulness and ease of use acted as strong bridges between literacy and usage intent, while perceived credibility although slightly weaker added ethical depth and addressed AI-specific risks like misinformation or hallucinations.

Here’s what this study contributes:

Theoretical insight: By extending the classic Technology Acceptance Model (TAM) to include perceived credibility, the study adapts the model to modern AI contexts, making it more relevant for current educational and workplace needs.
Practical value: It offers a roadmap for educators and institutions to design AI courses that don’t just teach skills but also help students trust, understand, and confidently use AI.
Curriculum suggestions: Courses should not only include hands-on projects but also ethics discussions, credibility checks, and real-world applications to boost both skill and mindset.

Of course, there are limitations:

The sample only included students from one U.S. university results may differ in other regions or academic disciplines;
The study used a snapshot-in-time approach perceptions of AI may evolve rapidly over time;
It focused on five core variables future research could expand to include tech readiness,institutional support, or tool-specific design features;
Convenience sampling may introduce selection bias, as students with more interest in AI may have been more likely to participate.

In short, this research confirms that AI literacy matters not just as a concept, but as a real driver of students’ readiness for an AI-powered future. It also provides a practical, research-backed framework that educators and administrators can use to bridge the gap between AI education and career readiness in today’s fast-changing world.