Artificial intelligence (AI) is transforming the landscape of media production at an astonishing rate. A recent study from Saudi Arabia sheds light on an important aspect of this transformation: the manner in which media professionals are embracing AI. The findings indicate that the pressing question is not whether these professionals will adopt AI, but rather how extensively, safely, and equitably they will integrate these tools into their workflows. According to a survey involving 400 audiovisual media professionals published in Discover Artificial Intelligence, an impressive 95.8% reported utilizing AI in their content creation processes.
Understanding the Adoption Landscape
The research, led by Saad Faraj Alenzi and Ahmad Tawalbeh of Gulf University, alongside Ferhat Yilmaz from St. Petersburg State University, challenges traditional views on technology adoption. Instead of considering adoption as a singular transition, the study introduces a Barrier–Enabler Ecosystem Model. This framework combines established theories, such as the Technology Acceptance Model, which examines how perceived benefits influence personal decisions; Digital Divide Theory, which highlights disparities in access and skills; and Institutional Theory, which addresses pressures organizations experience from regulations and social norms. By viewing barriers and enablers as interrelated rather than separate entities, the researchers emphasize the nuanced landscape of AI adoption.
Saudi Arabia serves as an intriguing case for this analysis, particularly under the government’s Vision 2030 initiative, aimed at enhancing national AI capabilities and digital transformation. Media organizations are expected to meet high technological standards, yet they face unique challenges, such as compliance with data protection laws, performance gaps in Arabic-language processing compared to English, and varied training capacities. This multifaceted environment necessitates a sophisticated framework to effectively assess both institutional support and structural constraints.
Key Barriers to AI Integration
Among the few respondents who do not utilize AI, concerns over privacy and security emerged as significant barriers, with 12 out of 17 citing these issues. Other challenges included high subscription costs, mentioned by 11 participants. While these results are exploratory due to the small sample size, the emphasis on privacy is critical. Audio-visual professionals frequently manage sensitive materials, including unpublished content and confidential client information. AI tools, especially cloud-based ones, often require data to be processed outside organizational control, raising profound privacy issues. Therefore, even if a tool is perceived as beneficial, practitioners might reject it if the conditions involved are deemed unacceptable.
The broader sample highlighted training programs and specialized workshops as the most crucial facilitating conditions for AI adoption, followed by the need for affordable tools and high-quality training resources. These findings suggest the necessity of addressing individual capabilities, organizational support, and sector-wide infrastructure. Although many professionals already use AI, there is a recognition that their engagement is not as deep or effective as it could be, spotlighting the need for further training and resources.
Demographic Insights on AI Readiness
The research provided additional insights into the demographics influencing AI readiness. Notably, readiness varied significantly by age, sector, geographic location, and income, but showed no variation based on gender or education. Professionals in the government sector demonstrated the highest readiness, while retired respondents reported the least, albeit from a small subset. The results suggest that institutional pressures modelled by state expectations drive practitioners towards greater technological adoption.
Interestingly, the study revealed regional disparities in AI readiness. Surprisingly, the Central region, home to Riyadh, displayed the lowest reported readiness, while the Southern region scored the highest. This phenomenon can be examined through a socio-technical lens, where practitioners in densely populated media markets are more familiar with the limitations of AI tools. In contrast, increased demand for promotional content in the South, driven by Vision 2030 initiatives, may have accelerated AI adoption.
In pursuit of effective AI integration, the study concludes with recommendations for national AI bodies to invest in the development of models tailored to Arabic-language contexts. Enhanced training resources could significantly enhance the effectiveness of AI tools in the media sector, bridging the gap between advanced technology use and the specific linguistic and cultural nuances of Arabic content creation. Moving forward, the focus must shift towards fostering equitable and resource-conscious AI adoption that genuinely meets the unique demands of media professionals in Saudi Arabia.