Effect of Artificial Intelligence Tools on Records Classification and Retrieval Efficiency in Nigerian Corporate Organisations

This study empirically examines the effect of artificial intelligence (AI)-powered tools on records classification accuracy and retrieval efficiency in Nigerian corporate organisations, with evidence from financial services, telecommunications, and manufacturing sectors. AI applications in records management, including natural language processing for automated classification, machine learning for predictive retrieval, and intelligent workflow routing, are transforming records management capabilities globally, yet their adoption and measured effects in Nigerian corporate settings remain understudied. The research employs a quasi-experimental design comparing AI-enabled records systems with non-AI systems in matched pairs of organisations (n=16). Records classification accuracy rates, retrieval response times, and user satisfaction scores are the primary outcome variables, measured using system performance logs and validated user experience instruments. The Technology Adoption and Diffusion Theory and the Records Automation Framework provide the theoretical grounding, with literature from 2021 to 2024 on AI in records management supporting the analysis. The study produces a rare experimental comparison dataset for AI records management in Nigeria. Recommendations target the Institute of Records Management of Nigeria and corporate information governance committees. Keywords: artificial intelligence, records classification, retrieval efficiency, corporate organisations, Nigeria