AI-DRIVEN PORTFOLIO MANAGEMENT FOR IBADAN WASH INFRASTRUCTURE

Rapid urbanization has become a defining feature of the twenty-first century, reshaping population distribution, infrastructure needs, and the spatial structure of cities worldwide

AI-DRIVEN PORTFOLIO MANAGEMENT FOR IBADAN WASH
INFRASTRUCTURE: A STRATEGIC FRAMEWORK FOR SUSTAINABLE
PLANNING IN IBADAN METROPOLIS
ODUNFA Victoria O.*, PhD, ELEGBEDE Olufola. T., TAIWO Olushola S.
& OGUNDIRAN A. A.

Department of Estate Management and Valuation,
The Polytechnic, Ibadan, Nigeria.

Corresponding author: odunfactorivictoria@gmail.com | 08034835625

Abstract

Accelerated urbanization in Ibadan has significantly intensified pressure on Water, Sanitation, and Hygiene (WASH) infrastructure, resulting in persistent inefficiencies in service delivery, inequitable access, and suboptimal resource allocation across the metropolis. As one of the largest and rapidly expanding urban centers in Nigeria, Ibadan exemplifies the complex challenges faced by cities in developing countries, where conventional WASH portfolio management approaches struggle to effectively prioritize projects and respond to dynamic urban growth. Despite the growing relevance of data driven planning, the potential of Artificial Intelligence (AI) to enhance forecasting, planning, and decision-making within Ibadan’s WASH sector remains largely underutilized. This study develops a strategic framework for integrating AI into urban WASH portfolio management, with specific application to Ibadan metropolis. Adopting a conceptual framework approach, the research is supported by secondary data analysis drawn from global and national WASH datasets, alongside comparative insights from cities that have implemented AI enabled infrastructure solutions. The study demonstrates how AI tools including predictive analytics, optimization algorithms, and intelligent decision support systems can improve project prioritization, optimize resource allocation, and enhance overall service delivery efficiency within the Ibadan context. The proposed framework provides context-specific guidance for urban planners, policymakers, and infrastructure stakeholders, with a focus on improving operational performance, promoting equitable service access, and strengthening the long-term sustainability of WASH systems in Ibadan. By situating AI within the realities of a rapidly urbanizing African metropolis, this study contributes to ongoing discourse on smart cities, sustainable development, and resilient urban planning, highlighting the role of intelligent technologies in transforming urban infrastructure management.

Keywords:

Artificial Intelligence, Water, Sanitation and Hygiene (WASH), Portfolio Management, Urban Planning, Infrastructure Sustainability, Smart Cities.