ANALYSIS OF AI CONTRIBUTION TOWARDS REDUCING FUTURE PANDEMIC LOSS IN SME SECTOR: ACCESS TO ONLINE MARKETING AND YOUTH INVOLVEMENT

Abstract

The COVID-19 pandemic imposed unprecedented operational disruptions on small and medium-sized enterprises (SMEs), with youth-led businesses emerging as one of the most vulnerable segments due to limited capital reserves, constrained digital infrastructure, and dependence on in-person transactions. Lockdowns, mobility restrictions, and shifts in consumer demand patterns accelerated the imperative for digital transformation, positioning artificial intelligence (AI) as a strategic enabler of business continuity, market adaptation, and resilience. This study investigates the role of AI-enabled tools—specifically customer interaction systems, predictive analytics, social media marketing automation, eCommerce enablement, and personalization—in supporting the survival and competitive positioning of youth-led SMEs during the pandemic. Findings reveal that AI-driven customer interaction tools maintained service continuity and reduced operational costs by up to 40%, with youth-led SMEs exhibiting greater adaptability in deploying low-code AI due to higher digital fluency. Cross-regional comparisons underscore disparities in adoption depth, shaped by infrastructural readiness, data quality, AI literacy, and regulatory frameworks. While developed economies leveraged advanced digital ecosystems for comprehensive AI integration, SMEs in developing regions often adopted modular, low-code solutions to circumvent skill and infrastructure constraints. The study also identifies persistent ethical and governance challenges—such as algorithmic bias, privacy risks, and uneven access—that were deprioritized in favor of immediate operational survival. These findings contribute to the growing body of literature on AI-enabled SME resilience by highlighting the unique absorptive capacities of youth-led enterprises, the synergistic effects of integrating multiple AI applications, and the contextual factors mediating adoption outcomes. The paper concludes by proposing a conceptual framework for future research, emphasizing the need for longitudinal, cross-sectoral, and policy-oriented studies to examine AI’s long-term impact on SME competitiveness in post-crisis economies.