The Impact of Artificial Intelligence Utilization on Enhancing the Competitiveness of Startups: A Quantitative Descriptive Study in the Arab Context

Abstract

This study addressed the limited and uneven adoption of artificial intelligence (AI) within startups and examined how financial, organizational, and technical barriers influence the ability of these firms to translate AI adoption into competitive advantage. The study aimed to investigate the impact of AI utilization on startup competitiveness, with particular attention to the effectiveness of intelligent tools, organizational and regulatory barriers, internal readiness, and supportive policies that enable responsible AI adoption. A quantitative descriptive-analytical approach was employed, and data were collected through an online questionnaire distributed to 118 participants representing startup companies. The findings showed that partial AI adoption was the most common pattern among participating firms (48.3%), followed by pilot-level adoption (26.3%), whereas only 11.0% reported no AI adoption. Recommendation and personalization systems achieved the highest effectiveness score (M = 3.63), followed by computer vision technologies (M = 3.59) and AI-powered customer service solutions (M = 3.58). Financial cost emerged as the most significant barrier to adoption (M = 3.51), followed by resistance to organizational change (M = 3.44) and regulatory uncertainty (M = 3.42). Inferential analysis partially supported the first hypothesis: one-way ANOVA indicated statistically significant differences across adoption levels, F(3,114) = 5.567, p = .001, eta squared = .128, and the multiple regression model was also significant, R² = .195, F(7,110) = 3.805, p = .001. The mediating effect of data quality was not statistically supported because the 95% bootstrap confidence interval for the indirect effect included zero [-.129, .054]. The moderating effect of institutional support was not significant (B = .053, p = .408), although its direct effect was strong and significant (B = .728, p < .001, R² = .588). Governance showed a strong positive effect on internal readiness (B = .620, β = .798, t = 14.259, p < .001, R² = .637).