Review2024

Artificial intelligence and family businesses: a systematic literature review

45 citations0/0 files storedJournal of Family Business Management

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Family Business Performance and Succession Artificial Intelligence Applications Impact of AI and Big Data on Business and Society

Abstract

Purpose This paper examines the integration of artificial intelligence (AI) within family businesses, focusing on how AI can enhance their competitiveness, resilience and sustainability. The study seeks to provide insights into AI’s application in family business contexts, addressing the unique strengths and challenges these businesses face. Design/methodology/approach A systematic literature review was conducted to synthesize existing research on the adoption and integration of AI in family businesses. The review involved a comprehensive analysis of relevant academic literature to identify key trends, opportunities, challenges and factors influencing AI adoption in family-owned enterprises. Findings The review highlights the significant potential of AI for family businesses, particularly in improving operations, decision-making and customer engagement. It identifies opportunities such as analysing customer data, enhancing brand building, streamlining operations and improving customer experiences through technologies like Generative AI, Machine Learning, AI Chatbots and NLP. However, challenges like resource constraints, inadequate infrastructure, low customization and AI knowledge gaps inhibit AI adoption in family firms. The study proposes an AI adoption roadmap tailored for family businesses and outlines future research directions based on emerging themes in AI use within these enterprises. Originality/value This paper addresses the underexplored area of AI integration in family businesses, contributing to the academic understanding of the intersection between AI and family-owned enterprises. The study offers a comprehensive synthesis of existing research, providing valuable insights and practical recommendations for enhancing the competitiveness and sustainability of family businesses through AI adoption.

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References

2006Using thematic analysis in psychology 2003Towards a Methodology for Developing Evidence‐Informed Management Knowledge by Means of Systematic Review 2016How the machine ‘thinks’: Understanding opacity in machine learning algorithms 2017The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms 2020The art of crafting a systematic literature review in entrepreneurship research 2021Artificial intelligence for supply chain resilience: learning from Covid-19 2019Application of Artificial Intelligence in Automation of Supply Chain Management 2023Enhancing Customer Loyalty through Artificial Intelligence (AI), Internet of Things (IoT), and Big Data Technologies: Improving Customer Satisfaction, Engagement, Relationship, and Experience

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