Optimizing AI Chatbot Adoption for MSME Competitiveness

Abstract

Purpose: This study reviews empirical evidence on AI chatbots in micro and small MSMEs to explain their impact on sales performance and customer satisfaction and to identify key drivers, barriers, and adoption strategies relevant to Society 5.0.

Methodology: A PRISMA-guided systematic literature review was conducted across Scopus-indexed sources (ScienceDirect, Emerald, MDPI), covering July 2014–July 2025. Thirty-nine articles met the inclusion criteria.

Findings: Flow and Technology Interactivity explain how readability, transparency, personalization, responsiveness, and ubiquitous connectivity create flow, thereby enhancing communication quality and satisfaction. TAM/UTAUT and meta-UTAUT show perceived usefulness as the most consistent driver of intention and continuance, with perceived intelligence and anthropomorphism reinforcing acceptance; privacy risk, time risk, technological anxiety, and data/security concerns inhibit adoption. The TOE lens groups context-specific enablers and constraints across technology, organization, and environment, while RBV and Dynamic Capabilities clarify how AI-CRM, data governance, multichannel integration, and sensing–seizing–reconfiguring convert conversational value into advantage.