Evaluation of Artificial Intelligence (AI) Adoption Barriers and Strategic Solutions for Port Decongestion at Apapa Wharf, Nigeria.

Abstract:

The adoption of Artificial Intelligence (AI) in port operations presents significant opportunities for addressing persistent congestion challenges, yet implementation in developing country contexts faces substantial barriers. This study examined the Evaluation of AI Adoption Barriers and Strategic Solutions for Port Decongestion at Apapa Wharf, Nigeria, and identified strategic solutions for full AI integration. Using a descriptive survey design with quantitative methodology, data were collected from 210 management staff of the Nigerian Ports Authority at Apapa Wharf. Descriptive statistics (mean and standard deviation) and inferential statistics (chi-square test) were employed for analysis. Findings revealed significant challenges including inadequate digital infrastructure (mean=3.18), lack of technological expertise (mean=3.30), resistance to change from workers benefiting from old systems (mean=3.28), poor data management and availability (mean=3.10), limited local innovator ecosystem (mean=3.24), and policy and regulatory gaps (mean=3.24). Corresponding solutions identified included investment in modern ICT infrastructure through public-private partnerships (mean=2.92), capacity-building programs for port staff (mean=3.04), early stakeholder engagement through awareness campaigns (mean=3.36), standardized data collection protocols (mean=3.38), robust cybersecurity frameworks (mean=3.26), and clear national AI governance policies (mean=3.24). Chi-square tests confirmed significant challenges (χ²=154.28, p<0.05) and significant solutions (χ²=168.30, p<0.05). The study concludes that addressing infrastructural, human capital, organizational, and regulatory barriers through coordinated multi-stakeholder efforts is essential for successful AI adoption in Nigerian ports.