From AI Capability to Sustainable Performance in Resource-Constrained SMEs: The Mediating Role of Resource Bricolage Capability

HRMARS - Resource-constrained small and medium-sized enterprises (SMEs) face increasing pressure to improve sustainable performance while operating with limited financial slack, uneven digital infrastructure, and constrained managerial capacity. Although artificial intelligence (AI) capability can improve decision quality, process efficiency, resource visibility, and sustainability-oriented action, its value does not automatically translate into economic, environmental, and social performance. The organisational mechanism through which resource-constrained SMEs convert AI capability into sustainable firm performance remains underexplained. Focusing on resource-constrained SMEs, this Conceptual Paper develops a resource bricolage capability framework to address this gap. Drawing on the Resource-Based View, Composition-Based View, Bricolage Theory, Resource Orchestration Theory, and the Triple Bottom Line (TBL) perspective, the paper argues that AI capability contributes to sustainable performance when SMEs use AI-enabled insights to identify, recombine, and redeploy resources already at hand. Resource bricolage capability is positioned as the organisational bridge between AI-enabled resource visibility and the actions that produce cost savings, waste reduction, operational adaptation, employee involvement, and stakeholder value. The framework advances three propositions and offers guidance for SME managers and policymakers seeking to convert AI capability into sustainable value under resource constraints.