Effects of Artificial Intelligence on the Sustainable Performance of SMEs in the Tourism Sector in Nairobi, Kenya: The Moderating Role of Environmental Dynamism

Abstract

In Nairobi’s tourism sector, Small and Medium-Sized Enterprises (SMEs) significantly contribute to economic growth, employment and innovation. The rapid rise of artificial intelligence (AI) presents major opportunities to boost efficiency, customer engagement, and sustainability. Yet, many tourism SMEs face challenges in adopting AI. As global competition intensifies and environmental conditions grow more unpredictable, the ability of AI to enhance sustainable performance remains unclear. Furthermore, the environmental dynamism marked by shifting market and ecological factors may strengthen or weaken the impact of AI on SME sustainability. This study therefore examines the effect of AI on the sustainable performance of tourism SMEs in Nairobi, Kenya, while assessing how environmental dynamism moderates this relationship. The study was anchored on Technology-Organization-Environment (TOE) Theory and employed an explanatory research design. The target population comprised 1,200 managers from 120 registered tourism firms, from which a stratified sample of 300 respondents was selected using Taro Yamane’s formula. Primary data were collected through structured self-administered questionnaires using a 5-point Likert scale. The instrument’s reliability was confirmed through Cronbach’s alpha coefficients above 0.7, and validity was established via expert review and principal component analysis. Data analysis was conducted in SPSS 25, using descriptive statistics to summarize responses and inferential statistics, including correlation and hierarchical regression, to test hypotheses and moderation effects.  Results revealed a significant positive relationship between AI and sustainable performance (r = 0.410, p < 0.01) and a moderate positive link between environmental dynamism and sustainable performance (r = 0.235, p < 0.01). Regression results showed that AI positively and significantly influenced sustainable performance (β = 0.234, p < 0.05), while environmental dynamism significantly moderated this relationship (β = 0.254, p < 0.05). The study demonstrates that the adoption of artificial intelligence significantly enhances the sustainable performance of tourism SMEs in Nairobi, with environmental dynamism influencing the strength of this relationship. The study recommends that tourism SMEs in Nairobi integrate AI into their core operations as a strategic tool to enhance sustainable performance. Managers should invest in AI-driven decision systems, workforce training and environmental scanning to strengthen adaptability under dynamic market conditions. Also, policymakers should provide incentives, digital infrastructure and clear regulatory frameworks to promote AI adoption and resilience in the tourism sector. Future studies should explore the long-term impact of AI on SME sustainability across different regions and environmental contexts.