• Studies show that effective AI adoption in universities depends on faculty digital literacy and confidence, not just the availability of tools (Zuo et al., 2025).

• Institutions that do not provide structured support often face uneven technology adoption and inconsistent teaching quality.

• Research highlights that motivation, perceived usefulness, and accessible training strongly influence whether instructors accept new systems (Gautreau, 2025).

• Employee training literature shows that short modules, clear progression, and certification improve participation and long term learning outcomes (Kannan, 2024).

• Evidence from LMS and LTI research shows that faculty benefit from hands-on practice before using AI tools in real classrooms (Shotarova and Stoyanova-Petrova, 2023).

• Studies show that dashboards and visual feedback help faculty stay engaged by displaying progress and achievements in a clear way (Lucio et al., 2018).

• Research on collaboration confirms that instructors adopt technology more successfully when they can ask questions, share ideas, and learn from peers (Seonghee and Boryung, 2008).

• Digital upskilling programs have been shown to improve teaching quality and instructor confidence, which directly supports better student learning outcomes (Areej ElSayary, 2023).

Key Findings