Generative AI in Saudi Arabia: A National Survey of Adoption, Risks, and Public Perceptions

Abdulaziz AlDakheel, Ali Alshehre, Esraa Alamoudi, Moslim AlKhabbaz, Ahmed Aljohani +1 more
1/26/2026
cs.CYcs.AIcs.CL

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Abstract

Generative Artificial Intelligence (GenAI) is rapidly becoming embedded in Saudi Arabia's digital transformation under Vision 2030, yet public awareness, adoption, and concerns surrounding these tools remain underexplored. This study provides an early snapshot of GenAI engagement among Saudi nationals. Using a nationwide survey of 330 participants across regions, age groups, and employment sectors, we examine seven dimensions of GenAI use: awareness and understanding, adoption patterns, perceived impacts, training needs, risks and barriers, data-sharing behaviors, and future expectations. Findings show that 93% of respondents actively use GenAI primarily for text-based tasks, while more advanced uses such as programming or multimodal generation are less common. Despite the prevalence of use, overall awareness and conceptual understanding remain uneven, with many reporting limited technical knowledge. Participants recognize GenAI's benefits for productivity, work quality, and understanding complex information, yet caution that sustained reliance may undermine critical thinking and key professional skills. Trust in AI-generated outputs remains cautious, with widespread concerns about privacy, misinformation, and ethical misuse, including potential job displacement. Respondents show strong interest in structured GenAI training that combines foundational skills, domain-specific applications, and clear guidance on privacy, ethics, and responsible use. These results establish a baseline for GenAI engagement in Saudi Arabia and highlight priorities for policymakers and developers: expanding AI literacy, ensuring culturally and linguistically aligned GenAI solutions, and strengthening frameworks for privacy and responsible deployment.

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Cite this paper

@article{aldakheel2026generative,
  title  = {Generative AI in Saudi Arabia: A National Survey of Adoption, Risks, and Public Perceptions},
  author = {Abdulaziz AlDakheel and Ali Alshehre and Esraa Alamoudi and Moslim AlKhabbaz and Ahmed Aljohani and Raed Alharbi},
  year   = {2026},
  eprint = {2601.18234},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2601.18234v1}
}

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