JCARM Journal of Contemporary Academic Research and Methodologies JCARM 3139-7247 Ivory and Finch Publishers 10.5281/zenodo.23280180 JCARM_SEP_26_130 Original Research Article ARTIFICIAL INTELLIGENCE ADOPTION AND ORGANIZATIONAL PERFORMANCE OF SMEs IN ANAMBRA STATE, NIGERIA KACHIKWULU ANASTECIA (PhD) ODINANWA, Department of Business Administration and Management, School of Business Studies, Federal Polytechnic, Oko. Anambra State, Nigeria. k.odinanwa@federalpolyoko.edu.ng 10 10 2026 1 8

The growing accessibility of artificial intelligence (AI) technologies presents new opportunities for small and medium-sized enterprises (SMEs) to improve efficiency, customer engagement, decision-making and competitiveness. However, the level of AI adoption among SMEs remains uneven, particularly in developing economies where financial, technological and infrastructural constraints may limit effective utilization. This study examined the extent of AI adoption, its relationship with organizational performance, and the major constraints affecting adoption among SMEs in Anambra State, Nigeria, with particular focus on the Onitsha and Nnewi business clusters. A descriptive cross-sectional survey design was employed. From a population of 1,200 registered SMEs, a sample of 300 owner-managers and managers was determined using Taro Yamane’s formula and selected through proportionate stratified sampling. Data were collected using a structured questionnaire and analysed using descriptive statistics and simple linear regression with SPSS version 27 at the 5% level of significance. The findings revealed a moderate overall level of AI adoption, with relatively higher use of AI-supported customer communication and generative AI applications for marketing and content creation, while advanced applications for sales analysis, inventory management and personalization recorded lower usage. The regression results showed that AI adoption was positively associated with organizational performance (B = 0.576, β = .518, R² = .268, p < .001), indicating that higher levels of AI adoption corresponded with improved organizational performance. The major constraints to AI adoption were high implementation cost, inadequate AI and digital literacy, unreliable electricity supply, lack of technical expertise and poor or expensive internet connectivity. The study concludes that although AI adoption among SMEs in Anambra State remains moderate and uneven, its effective integration into business activities is associated with improved organizational performance. It therefore recommends practical AI-literacy programmes, affordable digital-financing support and improved electricity and internet infrastructure to facilitate wider and more effective adoption among SMEs.

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