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Applications of Artificial Intelligence in Small and Medium Scale Business

Author

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  • Md. Kamruzzaman

    (MBA in Data Analytics, (University of New Haven, CT, USA), Master of Business Administration, Accounting & Information Systems (University of Dhaka, Bangladesh), Master of Social Science, Political Science (National University, Bangladesh), Bachelor of Social Science, Political Science (National University, Bangladesh))

  • Sujoy Saha

    (Master of Science in Business Analytics, (University of New Haven, CT, USA), Master of Science in Statistics, (National University, Bangladesh), Bachelor of Science in Statistics, (National University, Bangladesh))

  • Md. Shoeb Siddiki

    (MBA in Data Analytics, (University of New Haven, CT, USA), Master of Business Administration (Dhaka International University, Bangladesh), Bachelor of Business Administration (Dhaka International University, Bangladesh))

  • Rabi Sankar Mondal

    (Master of Science in Business Analytics, (University of New Haven, CT, USA), Master of Pharmacy (Jamia Hamdard, New Delhi, India), Bachelor of Pharmacy (Jamia Hamdard, New Delhi, India))

  • Md Nazmul Alam Bhuiyan

    (MBA in Data Analytics, (University of New Haven, CT, USA), Bachelor of Business Administration (East West University, Bangladesh))

Abstract

This study investigates the adoption, implementation, and impact of artificial intelligence (AI) technologies in small and medium-sized enterprises (SMEs) across multiple sectors and regions. Using a mixed-methods approach combining surveys (n=583), semi-structured interviews (n=47), and case studies (n=18), we provide comprehensive insights into how resource-constrained businesses leverage AI to enhance competitiveness and operational efficiency. Results reveal a significant acceleration in AI adoption among SMEs, with 64.7% of surveyed businesses implementing at least one AI application—predominantly in customer service, marketing, and operations. Three distinct implementation approaches were identified: problem-first (63.8%), technology-push (24.7%), and competitive-response (11.5%), with the problem-first approach demonstrating superior outcomes. Despite persistent challenges in technical expertise and resource availability, successful SMEs employed strategic partnerships (67.4%) and phased implementation (83.2%) to overcome these limitations. Implemented AI solutions delivered meaningful business improvements in operational efficiency (27.3%), customer satisfaction (24.8%), and cost reduction (22.4%), with an average ROI timeframe of 8.8 months. Structural equation modeling revealed that AI implementation positively influences business performance (β=0.43, p

Suggested Citation

  • Md. Kamruzzaman & Sujoy Saha & Md. Shoeb Siddiki & Rabi Sankar Mondal & Md Nazmul Alam Bhuiyan, 2025. "Applications of Artificial Intelligence in Small and Medium Scale Business," Journal of Business and Management Studies, Al-Kindi Center for Research and Development, vol. 7(4), pages 314-325, July.
    • Handle: RePEc:alk:jbms00:v:7:y:2025:i:4:id:10625
    DOI: 10.32996/jbms.2025.7.4.20.21
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