Challenges and Opportunities of Artificial Intelligence Integration in Higher Education in Somalia

Abstract The integration of artificial intelligence (AI) promises to bring about numerous opportunities and challenges in higher education while enhancing teaching, learning, and quality improvement in this sector. This study focused on the opportunities and challenges of the integration of AI in higher education as well as its contribution to quality improvement. A quantitative survey research design was selected for this study. The target population comprised students, ICT staff, lecturers, and administrators in higher education institutions in Somalia. A sample of two hundred and twenty-four (224) respondents was selected from the target population. The study used frequencies, percentages, means, and standard deviation in reporting the results of the study. The results of this study revealed that challenges of the integration of AI in higher education were perceived to be high (M = 3.289). The major challenges included low perception of students regarding the applications of AI in higher education, the need for enhanced ICT infrastructure, the cost of AI technology, the absence of AI-related institutional policies, and the low level of knowledge and skills on part of academic staff handling AI technology. However, participants perceived the opportunities presented by AI technology in higher education to be high (M = 3.547). The opportunities included; boosting the chances of students accessing learning materials, promoting readiness and skills for future jobs, promoting innovative strategies for teaching and learning, enhancing effective teaching and learning, and improving administrative processes. In addition, the study found that the contribution of AI to quality improvement in higher education was high (M = 3.488). Personalized learning was the most perceived contribution of AI to quality improvement in higher education (M = 3.929), followed by improved teaching and learning (M = 3.732), and more effective teaching and learning by lecturers (M = 3.571). The study recommends that for AI systems to promote quality in higher education, there is a need to invest more in ICT infrastructure, invest more in AI, raise awareness among students about AI, develop institutional policies on AI, and implement quality assurance measures.