Customer adoption of AI-enabled telecom services and their influence on the quality of customer insights in Oman’s telecommunications sector - Shanmugam, Ms. Kavitha; Jayashree, Rajendran; Ghafri, Amira Zayid Sultan Al; Siyabi, Ms. Hanna Said Nasser Al (Edelweiss Applied Science and Technology, 2026)
This study examines how customers' adoption of AI-enabled services enhances data-driven insights within Oman's telecommunications sector, focusing on chatbots, predictive analytics, and personalized recommendation systems and their contribution to improved decision-making aligned with Oman Vision 2040. A mixed-methods design combines quantitative and qualitative data, integrating constructs from TAM, UTAUT, and Trust Theory, including perceived usefulness, ease of use, personalization, trust, and privacy concerns, to comprehensively assess adoption behavior and its impact on customer insight quality. AI-enabled solutions improve the accuracy, interpretability, and strategic value of customer insights, enabling more personalized and proactive service delivery. However, adoption varies considerably due to digital literacy gaps, trust deficits, and persistent concerns about data privacy, transparency, and potential misuse of personal information. AI serves as a strategic enabler of data-driven decision-making in Oman's telecom sector. Widespread adoption requires addressing trust-related barriers, improving digital literacy, and reinforcing transparent AI communication strategies aligned with Oman Vision 2040. Telecom operators should prioritize AI transparency, robust data governance frameworks, digital literacy programs, and AI-powered predictive analytics to foster proactive customer engagement, reduce churn, and advance national digital transformation objectives.