INTEGRATION AND APPLICATION OF ARTIFICIAL INTELLIGENCE TO RECORDS MANAGEMENT IN SOME SELECTED TERTIARY INSTITUTIONS IN OYO STATE, NIGERIA
INTEGRATION AND APPLICATION OF ARTIFICIAL INTELLIGENCE TO RECORDS MANAGEMENT IN SOME SELECTED TERTIARY INSTITUTIONS IN OYO STATE, NIGERIA
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Date
2026
Authors
Oluchi, O. Okere
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Publisher
Library and Information Management Forum Vol. 28. No. 1 2026
Abstract
This study examined the integration and application of artificial intelligence (AI) to records
management in selected tertiary institutions in Oyo State, Nigeria. The study was guided by
four research questions including: “what is the level of awareness and current level of
application of AI in records management among personnel”? And “how adequate is the
existing infrastructure for AI integration?”. A descriptive survey research design was adopted.
The target population comprised 140 records management personnel (registry officers,
academic records officers, librarians, archivists, and clerical assistants) from selected tertiary
institutions. A total enumeration approach was used, and a structured questionnaire titled
Artificial Intelligence Integration in Records Management Questionnaire (AIIRMQ) was
administered. Out of 140 copies distributed, 120 were properly completed and returned
(response rate = 85.7%). Data were analyzed using descriptive statistics (frequency counts,
percentages, mean, and standard deviation) with a criterion mean of 2.50 on a 4-point Likert
scale. Findings revealed that while respondents had high general awareness of AI (mean =
3.42), their technical understanding of AI applications in records management was low (mean
as low as 1.85), and the actual level of AI application across all records functions was very
low (means ranged from 1.38 to 1.62). Existing infrastructure for AI integration (electricity,
internet, computers, AI software, technical support) was grossly inadequate (mean range =
1.38–1.82). Respondents strongly agreed on perceived benefits of AI, including improved
accessibility (mean = 3.55), efficiency (mean = 3.52), accuracy (mean = 3.48), and reduced
workload (mean = 3.38). However, major barriers to AI integration included poor digital
infrastructure (mean = 3.72), high cost of AI hardware/software (mean = 3.65), lack of skilled
personnel (mean = 3.58), lack of management support/policy framework (mean = 3.48),
resistance to change (mean = 3.40), lack of AI awareness (mean = 3.38), and data
privacy/security concerns (mean = 3.25).the paper concludes that tertiary institutions in Oyo
State, Nigeria, possess only superficial AI awareness with negligible practical application.
Severe infrastructural deficits and multiple barriers impede AI adoption, despite strong
recognition of AI’s potential benefits. The study recommended among others that institutions
should invest in digital infrastructure (stable power, internet, hardware); develop mandatory
AI training programs; establish national policy frameworks and public-private partnerships;
and create dedicated technical support teams for AI systems.
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Journal of Library and Information Management Forum