Data Governance Frameworks for Enabling Responsible AI in Small, Medium, and Micro Enterprises: A Systematic Literature Review

Abstract

Disruptive technologies such as Artificial Intelligence (AI) have brought about changes in how organisations function. The adoption of AI has been applied in various industries, ranging from smart energy, smart transportation, smart health such as cancer treatment to managing automated cybersecurity threats and responding to sophisticated cyber threats. This presents opportunities and challenges as small, medium and micro enterprises (SMMEs) are also adopting AI to drive innovation, efficiency, and competitiveness. When compared to large organisations, SMMEs often lack the resources, expertise, and infrastructure necessary to implement comprehensive data governance frameworks, which are essential for responsible AI deployment. This study aims to investigate how data governance frameworks can enable responsible AI practices, specifically within the context of SMMEs. This study adopts a systematic literature review where the PRISMA framework is used to extract information on the data governance principles, challenges and opportunities that SMMEs can use for responsible AI. This study's findings reveal that effective governance plays a critical role in the adoption of AI within SMMEs. Existing data governance frameworks provide guidance, even though they are complex, which is a limitation for SMMEs. This study highlights opportunities for SMMEs in the data governance frameworks in enabling responsible AI. This study also reveals the need for a universal data governance framework.