Exploring artificial intelligence coaching’s role in translating business training into real-world applications

Abstract

Orientation: Small and medium enterprises (SMEs) in emerging markets face challenges in applying business training knowledge to real-world operations, necessitating scalable, cost-effective support mechanisms like artificial intelligence (AI) coaching.
Research purpose: This study explored how AI coaching supported SME entrepreneurs in translating business training into practical applications within emerging market contexts.
Motivation for the study: How AI coaching helps SME leaders turn business training into daily practice is not yet understood. Clarifying its influence on post-training application can show whether AI coaching could offer scalable support in resource-limited settings.
Research approach/design and method: A qualitative exploratory design was employed. Twenty SME owners and managers participated in a business training workshop, followed by a 4-week engagement with an AI coaching chatbot. Data were collected through engagement metrics and semistructured interviews, which were analysed using Braun and Clarke’s six-phase thematic analysis.
Main findings: Three themes emerged: functionality, methodology, and adoption. Participants valued real-time guidance and a nonjudgemental environment but faced challenges with onboarding and culturally mismatched phrasing. Trust in data handling was critical for adoption.
Practical/managerial implications: Artificial intelligence coaching provided accessible, scalable support for SMEs, enabling sustained knowledge application. Small and medium enterprise owners, managers, and trainers could integrate AI tools to enhance training outcomes in resource-limited settings.
Contribution/value-add: The study highlights AI coaching’s role as an affordable, context-sensitive tool for reinforcing business training in SMEs, contributing to adult learning and entrepreneurial development literature by demonstrating its impact on experiential learning in emerging markets.