From Perception to Adoption: Exploring the Integration of Generative AI in Scientific Research in Omani Higher Education

• In Event: Global Transformations in Higher Education: Mobility, Technology, Language, and Outcomes

Proposal

Generative Artificial Intelligence (GenAI) has rapidly emerged as a transformative force in scientific research, enabling automation of literature reviews, hypothesis generation, data analysis, and academic writing (Wang et al., 2023; Lin, 2023). These capabilities of GenAI are reshaping research workflows, enhancing efficiency, and fostering interdisciplinary collaboration (Ahmed et al., 2025; Dwivedi & Elluri, 2024). Global adoption studies highlight potential gains in productivity and accessibility, especially for researchers in resource-constrained contexts (Buehler, 2024). Yet the integration of GenAI also raises significant concerns regarding academic integrity, authorship, algorithmic bias, intellectual property, and the erosion of critical thinking (Bozkurt, 2024; Park, 2023; Goretti et al., 2024).
Higher education institutions (HEIs) are expected to enhance research capacity, increase international engagement, and produce impactful scholarship. GenAI presents an opportunity to accelerate these aims, but empirical evidence from the Arab region on how academics perceive and adopt GenAI remains scarce (Leung et al., 2023). Without localized insights, policy responses risk being overly restrictive or insufficiently robust, especially given contextual differences in governance, resources, and research culture compared to the predominantly Western and Asian settings of existing studies.
This study addresses that gap by examining Omani academics’ familiarity with GenAI, perceived benefits and challenges, ethical concerns, and factors influencing adoption intentions. It also explores institutional strategies that can enable responsible and equitable integration of GenAI into research. The analysis is framed by the Technology Acceptance Model (TAM) (Davis, 1989), which explains technology adoption through perceived usefulness and ease of use, while recognizing the role of external influences. To address the distinctive ethical and contextual dimensions of GenAI, TAM is extended here to include perceived challenges, ethical considerations, and institutional readiness, reflecting recent AI adoption studies that emphasize trust, governance, and disciplinary norms (Gupta et al., 2025).
An explanatory sequential mixed-methods design was used. In Phase 1, a survey of 450 academics across Omani HEIs measured actual use, perceived ease of use, perceived usefulness, perceived challenges, and intention to use. Quantitative analysis examined the relationships among these constructs, revealing patterns of familiarity and adoption. In Phase 2, semi-structured interviews with 10 volunteer participants explored in depth how ethical concerns, policy gaps, and disciplinary cultures shape perceptions and practices. This approach ensured breadth and depth, aligning with best practices in technology adoption research (Venkatesh et al., 2016).
Emerging survey findings indicate moderate familiarity with GenAI, with higher engagement in disciplines involving literature synthesis and textual analysis. Perceived usefulness strongly predicts adoption intentions, particularly for tasks such as accelerating literature reviews, manuscript drafting, and preliminary data coding, findings consistent with global studies (Wu et al., 2025; Ahmed et al., 2025). However, enthusiasm is moderated by concerns over plagiarism, AI-generated inaccuracies (“hallucinations”), unclear authorship norms, and absence of institutional guidelines (Eaton & Sabbaghan, 2025; Liebrenz et al., 2023).
Interview insights reveal cautious optimism. Some faculty integrate GenAI experimentally, using outputs as starting points for critical refinement, while others avoid it due to inconsistent publisher requirements and uncertainty over compliance with institutional and international norms (Salvagno et al., 2023). Across participants, there is consensus that GenAI should augment rather than replace human judgment, reflecting calls for human oversight in AI-supported research (Bhargava et al., 2025; Ding & Li, 2025). Equity concerns also emerged: limited budgets for technology procurement in some institutions risk creating disparities in access and productivity, echoing broader warnings about digital divides in AI adoption (Lin, 2023; Buehler, 2024).
These findings suggest several implications for Omani HEIs. First, context-specific ethical guidelines are needed to align with evolving global standards while reflecting local academic norms. Second, targeted AI literacy programs should equip academics to critically evaluate GenAI outputs and apply them responsibly. Third, equitable institutional access to advanced GenAI tools should be prioritized to avoid widening research inequalities. Finally, transparency and disclosure requirements should be embedded in research governance, consistent with emerging publisher policies (Kaebnick et al., 2023).
By offering one of the first empirical investigations of GenAI adoption in scientific research within Oman, this study contributes to theory, policy, and practice. The extended TAM framework proposed here provides a more comprehensive model for understanding adoption in culturally diverse higher education systems. Methodologically, the mixed-methods design yields both generalizable patterns and context-rich narratives, making the findings relevant beyond Oman to other Global South contexts navigating the integration of disruptive technologies into research.
In conclusion, GenAI adoption in research is a negotiated process shaped by perceived benefits, ethical boundaries, and institutional readiness. Omani academics are cautiously exploring GenAI’s potential to enhance efficiency, creativity, and collaboration, while remaining alert to risks to integrity and equity. Responsible and sustainable adoption will require strategic investments in governance, capacity building, and access, ensuring that GenAI strengthens rather than undermines the integrity and impact of scientific research in higher education.

Author

• Alsaeed Alshamy, Sultan Qaboos University