Digital Readiness Factors for AI Adoption in Indonesian SMEs: Integrating Systematic Review and Bibliometric Analysis

Artificial intelligence (AI) presents significant opportunities for small and medium enterprises (SMEs), yet successful adoption requires comprehensive digital readiness beyond basic technology infrastructure. Existing frameworks lack AI-specific adaptation and developing economy validation. This study aimed to develop a hierarchical digital readiness framework for AI adoption in Indonesian SMEs through an integrated Systematic Literature and Network Analysis (SLNA) approach. Following PRISMA 2020 guidelines, we systematically reviewed 17 high-quality studies representing 4,265 SMEs across 12 countries from the Scopus database, with concurrent keyword co-occurrence network analysis using VOSviewer on 405 keywords from 86 studies. Six hierarchical digital readiness factors emerged in three tiers: universal prerequisites (human capital, technology infrastructure, strategic management), contextual success factors (external environment, organizational culture), and one conditional factor (financial resources). Strategic management demonstrated the largest effect size (β=0.54), while human capital showed universal significance across all studies. Network analysis confirmed that AI-specific research remains isolated despite its central importance. The hierarchical framework provides evidence-based resource allocation guidance for SME digitalization policy, with human capital as the highest-priority intervention applicable across developing economies.