This study examines barriers to faculty adoption of generative AI (GenAI) in Saudi higher education and proposes expert-informed solutions, aligning with Saudi Vision 2030's AI priorities through initiatives like SDAIA. While Saudi universities like King Saud University (through its Generative AI Office and research laboratories) and KFUPM (via engineering applications) have actively integrated GenAI in academic and research domains, significant gaps remain in classroom implementation.

Employing a mixed-methods approach combining faculty surveys and expert interviews, the research systematically investigates:
(1) technical, pedagogical and institutional challenges;
(2) faculty readiness levels; and
(3) optimal implementation frameworks.

The study bridges the crucial disconnect between institutional AI investments and practical adoption, offering empirically grounded recommendations drawn from both faculty experiences and AI specialists' insights. Findings aim to optimize GenAI integration through context-specific strategies that address current adoption barriers while leveraging existing infrastructure and training initiatives in Saudi universities.

Keywords: Generative AI, Higher Education, Artificial Intelligence in Education (AIEd), Saudi Universities, Higher education.