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

• URL: http://arxiv.org/abs/2601.18234v1
• Date: Mon, 26 Jan 2026 07:40:41 GMT
• Title: Generative AI in Saudi Arabia: A National Survey of Adoption, Risks, and Public Perceptions
• Authors: Abdulaziz AlDakheel, Ali Alshehre, Esraa Alamoudi, Moslim AlKhabbaz, Ahmed Aljohani, Raed Alharbi,
• Abstract summary: Generative Artificial Intelligence (GenAI) is rapidly becoming embedded in Saudi Arabia's digital transformation under Vision 2030.<n>This study provides an early snapshot of GenAI engagement among Saudi nationals.
• Score: 0.6010778467667774
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

Related papers

• Integrating Generative AI-enhanced Cognitive Systems in Higher Education: From Stakeholder Perceptions to a Conceptual Framework considering the EU AI Act [0.7945222903786706]
  GenAI is expected to enhance cognitive systems by enabling personalized learning and streamlining educational services.<n> stakeholders perceptions of GenAI in higher education remain divided, shaped by cultural, disciplinary, and institutional contexts.<n>This study investigates how GenAI is perceived within the disciplines of Information Technology and Electrical Engineering.
  arXiv  Detail & Related papers  (2026-02-11T12:44:03Z)
• "If You're Very Clever, No One Knows You've Used It": The Social Dynamics of Developing Generative AI Literacy in the Workplace [16.792964152066638]
  We conducted in-depth interviews with 19 knowledge workers across multiple sectors to examine how they develop GenAI competencies.<n>We found that, while knowledge sharing from colleagues supported learning, the ability to remove cues indicating GenAI use was perceived as validation of domain expertise.<n>These behaviours ultimately reduced opportunities for learning via knowledge sharing and undermined transparency.
  arXiv  Detail & Related papers  (2026-02-01T18:41:30Z)
• Generative AI Practices, Literacy, and Divides: An Empirical Analysis in the Italian Context [32.495879271249414]
  This study presents the first comprehensive empirical mapping of GenAI adoption, usage patterns, and literacy in Italy.<n>Our findings reveal widespread adoption for both work and personal use, including sensitive tasks like emotional support and medical advice.<n>We identify a significant gender divide where women are half as likely to adopt GenAI and use it less frequently than men.
  arXiv  Detail & Related papers  (2025-12-03T11:01:28Z)
• AssurAI: Experience with Constructing Korean Socio-cultural Datasets to Discover Potential Risks of Generative AI [50.802995291689086]
  We introduce AssurAI, a new quality-controlled Korean multimodal dataset for evaluating the safety of generative AI.<n>We define a taxonomy of 35 distinct AI risk factors, adapted from established frameworks to cover both universal harms and relevance to the Korean socio-cultural context.<n>AssurAI is a large-scale Korean multimodal dataset comprising 11,480 instances across text, image, video, and audio.
  arXiv  Detail & Related papers  (2025-11-20T13:59:42Z)
• Reduced AI Acceptance After the Generative AI Boom: Evidence From a Two-Wave Survey Study [40.26767449635043]
  We examine shifts in public attitudes toward AI before and after the launch of ChatGPT.<n>The proportion of respondents finding AI "not acceptable at all" increased from 23% to 30%.<n>These shifts have amplified existing social inequalities in terms of widened educational, linguistic, and gender gaps post-boom.
  arXiv  Detail & Related papers  (2025-10-27T17:47:58Z)
• Generative AI for Biosciences: Emerging Threats and Roadmap to Biosecurity [56.331312963880215]
  generative artificial intelligence (GenAI) in the biosciences is transforming biotechnology, medicine, and synthetic biology.<n>This Perspective outlines the current state of GenAI in the biosciences and emerging threat vectors ranging from jailbreak attacks and privacy risks to the dual-use challenges posed by autonomous AI agents.<n>We advocate a multi-layered approach to GenAI safety, including rigorous data filtering, alignment with ethical principles during development, and real-time monitoring to block harmful requests.
  arXiv  Detail & Related papers  (2025-10-13T00:24:41Z)
• Analyzing Security and Privacy Challenges in Generative AI Usage Guidelines for Higher Education [13.414092505955205]
  Universities are developing policies to guide GenAI use while safeguarding security and privacy.<n>This work examines these emerging policies and guidelines, with a particular focus on privacy and security dimensions.<n>We identify key challenges and opportunities institutions face in providing effective privacy and security protections.
  arXiv  Detail & Related papers  (2025-06-25T14:12:18Z)
• "We need to avail ourselves of GenAI to enhance knowledge distribution": Empowering Older Adults through GenAI Literacy [0.49157446832511503]
  Older adults often exhibit greater reservations about adopting emerging technologies.<n>This study examines strategies for delivering GenAI literacy to older adults.<n> Quantitative data indicated a trend toward improved AI literacy, though the results were not statistically significant.
  arXiv  Detail & Related papers  (2025-06-06T16:38:37Z)
• Enterprise Architecture as a Dynamic Capability for Scalable and Sustainable Generative AI adoption: Bridging Innovation and Governance in Large Organisations [55.2480439325792]
  Generative Artificial Intelligence is a powerful new technology with the potential to boost innovation and reshape governance in many industries.<n>However, organisations face major challenges in scaling GenAI, including technology complexity, governance gaps and resource misalignments.<n>This study explores how Enterprise Architecture Management can meet the complex requirements of GenAI adoption within large enterprises.
  arXiv  Detail & Related papers  (2025-05-09T07:41:33Z)
• The GenAI Generation: Student Views of Awareness, Preparedness, and Concern [1.5709900716890133]
  Outpacing the development of uniform policies and structures, GenAI has heralded a unique era and given rise to the GenAI Generation.<n>This study examines students' perceptions of GenAI through a concise survey with optional open-ended questions.<n>Students with greater curricular exposure to GenAI tend to feel more prepared, while those without it more often express vulnerability and uncertainty.
  arXiv  Detail & Related papers  (2025-05-04T19:37:13Z)
• Generative AI Literacy: Twelve Defining Competencies [48.90506360377104]
  This paper introduces a competency-based model for generative artificial intelligence (AI) literacy covering essential skills and knowledge areas necessary to interact with generative AI.<n>The competencies range from foundational AI literacy to prompt engineering and programming skills, including ethical and legal considerations.<n>These twelve competencies offer a framework for individuals, policymakers, government officials, and educators looking to navigate and take advantage of the potential of generative AI responsibly.
  arXiv  Detail & Related papers  (2024-11-29T14:55:15Z)
• Early Adoption of Generative Artificial Intelligence in Computing Education: Emergent Student Use Cases and Perspectives in 2023 [38.83649319653387]
  There is limited prior research on computing students' use and perceptions of GenAI. We surveyed all computer science majors in a small engineering-focused R1 university. We discuss the impact of our findings on the emerging conversation around GenAI and education.
  arXiv  Detail & Related papers  (2024-11-17T20:17:47Z)
• Hey GPT, Can You be More Racist? Analysis from Crowdsourced Attempts to Elicit Biased Content from Generative AI [41.96102438774773]
  This work presents the findings from a university-level competition, which challenged participants to design prompts for eliciting biased outputs from GenAI tools. We quantitatively and qualitatively analyze the competition submissions and identify a diverse set of biases in GenAI and strategies employed by participants to induce bias in GenAI.
  arXiv  Detail & Related papers  (2024-10-20T18:44:45Z)
• AutoML in The Wild: Obstacles, Workarounds, and Expectations [37.813441975457735]
  This study focuses on understanding the limitations of AutoML encountered by users in their real-world practices. Our findings reveal that users actively exercise user agency to overcome three major challenges arising from customizability, transparency, and privacy.
  arXiv  Detail & Related papers  (2023-02-21T17:06:46Z)
• Empowering Local Communities Using Artificial Intelligence [70.17085406202368]
  It has become an important topic to explore the impact of AI on society from a people-centered perspective. Previous works in citizen science have identified methods of using AI to engage the public in research. This article discusses the challenges of applying AI in Community Citizen Science.
  arXiv  Detail & Related papers  (2021-10-05T12:51:11Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.