Artificial Intelligence: The key to Information and Knowledge Management Maturity in Organisations

Abstract

This study investigates the role of artificial intelligence (AI) as a catalyst for the maturity of information and knowledge management (IKM) within South African organisations. Positioned within the context of the Fourth Industrial Revolution (4IR), the research responds to the growing complexity of data environments characterised by big data, cloud computing, and advanced analytics. Traditional IKM approaches are increasingly inadequate for managing data variety, velocity, and volume, necessitating the integration of AI-driven capabilities such as machine learning (ML), natural language processing (NLP), and augmented analytics. Adopting an interpretivist paradigm, the study utilised a monomethod qualitative design. Semi-structured interviews were conducted with 12 strategically positioned IKM professionals across diverse functional areas, including knowledge management, business intelligence, records management, data governance, competitive intelligence, and social media management. Data were analysed using open, axial, and selective coding, supported by ATLAS.ti and thematic analysis. This approach enabled the development of an empirically grounded understanding of technology adoption patterns in IKM units, with a particular focus on AI adoption. The findings reveal that AI is widely perceived as central to achieving IKM maturity. Participants emphasised the importance of data analytics and visualisation platforms, many of which are enhanced by AI capabilities. AI-supported automation, predictive and prescriptive analytics, environmental scanning, anomaly detection, and generative content creation emerged as critical enablers of operational efficiency and strategic decision-making. Maturity was associated with process automation, infrastructure upgrades, enhanced data quality, and AI-driven system integration. While participants recognised AI as indispensable for competitiveness and innovation, concerns were raised regarding overreliance on AI, potential job displacement, and ethical implications. The study concludes that IKM units must strategically embed AI to remain relevant while balancing automation with human judgment and governance. By identifying foundational prerequisites for AI adoption, this research provides AI insights that can inform policy development, digital transformation strategies, and IKM's future positioning as a strategic organisational pillar.