IMPACT OF ARTIFICIAL INTELLIGENCE ON WORKFORCE PLANNING IN COLLEGES OF EDUCATION IN KADUNA STATE, NIGERIA (Journal of Association of Educational Management and Policy Practitioners, 2024)
The study investigated the Impact of Artificial Intelligence on Workforce Planning in Colleges of Education in Kaduna State, Nigeria. The study was conducted with the objective to: assess the impact of artificial intelligence on workforce planning in colleges of education in Kaduna State, Nigeria. In line with the objective, a research question and a hypothesis were formulated and tested. The study adopted survey research design with population of 3,181 respondents which comprised 1,658 lecturers and 1,523 senior management staff in the two (2) government owned Colleges of Education in Kaduna State, Nigeria. A sample size of 346 participants, consisting of 180 lecturers and 166 senior management staff were used in the study. The instrument titled ―Artificial Intelligence and Workforce Planning Questionnaire (ARIWPQ)‖ was used for data collection in the study. The validated instrument was pilot tested, the reliability co-efficient was determined using Cronbach Alpha statistic and a reliability coefficient of 0.82 was obtained. The data collected in the study was computerized into database using Statistical Package for Social Sciences (SPSS) version 23.0. The descriptive statistics of frequency counts, mean and standard deviation were used to answer the research question, while Kruskal-Wallis was used to test the hypotheses at 0.05 level of significance. Findings revealed that; artificial intelligence had no significant impact on workforce planning in colleges of education in Kaduna State, Nigeria. Based on the findings of the study, it was recommended among others that: The management of the colleges of education should exercise caution in applying artificial intelligence to determine the skill gap of the workers so as to avoid an unwarranted situation whereby the majority of their workforce will be affected, consequently leading to job losses.