The study examined the relationship between Participation in Lifelong Learning Models and Reskilling of Workers Displaced by Artificial Intelligence in Cross River State Nigeria. Guided by Human Capital Theory, the study adopted a correlational design with simple linear regression analysis. A sample of 228 workers displaced by AI-driven automation between 2022 and 2026 was selected using purposive and snowball sampling techniques. Data was collected using a validated 5-point Likert scale questionnaire with reliability coefficient of 0.84 and 0.88 for the participation and reskilling outcome scales respectively. Pearson Product Moment Correlation and Simple Linear Regression were used to analyse the data at 0.05 level of significance. The findings revealed a strong positive and significant relationship between Participation in Lifelong Learning Models and Reskilling outcomes, r(226) =0.61, p <0.001. Participation significantly predicted reskilling outcomes for 37.5% of the variance, F(1, 226) =237.47, p<0.001. The study concluded that engagement with AI-driven and competency-based lifelong learning platforms is a critical pathway for reskilling and employability among displaced workers by AI in Cross River State. It was recommended that government agencies, NGOs, and industry stakeholders should invest in accessible, scalable learning models to support workforce transition in the age of AI.