Intelligent Infrastructure Planning: Applying AI to Capital Investment Strategy in the Public and Private Sectors for Sustainable Growth

Intelligent infrastructure planning is rapidly emerging as a transformative approach to optimizing capital investment strategy in both public and private sectors. This research explores how artificial intelligence (AI) is revolutionizing decision-making processes related to large-scale infrastructure development particularly in energy, transportation, housing, and water systems by enhancing data integration, risk evaluation, and long-term scenario simulation. As governments and corporations face increasing pressure to allocate capital efficiently while aligning with sustainability mandates, AI-powered tools are being deployed to model complex variables and deliver evidence-based investment strategies. AI technologies, including machine learning, predictive analytics, and natural language processing, are enabling decision-makers to process vast datasets, uncover hidden patterns, and forecast infrastructure performance across decades. These capabilities support more accurate cost-benefit analyses, lifecycle planning, and early identification of risks associated with climate change, demographic shifts, and economic fluctuations. By simulating a range of potential outcomes and constraints, AI enhances the ability to prioritize projects that deliver the highest value under diverse scenarios. This study also highlights the integration of Environmental, Social, and Governance (ESG) criteria into AI investment frameworks. By embedding ESG metrics into capital planning models, organizations can evaluate the long-term social and environmental impacts of proposed projects, promote responsible investment, and align with global sustainability standards. In doing so, AI supports more transparent, equitable, and inclusive infrastructure development that addresses community needs, regulatory expectations, and investor requirements. Furthermore, the paper examines cross-sectoral applications where AI has enabled smarter infrastructure decisions, from optimizing renewable energy site selection to predictive maintenance in water systems and congestion reduction in urban transportation networks. These case studies underscore how AI is reshaping capital allocation frameworks to ensure resilience, sustainability, and efficiency in infrastructure systems. Ultimately, intelligent infrastructure planning empowered by AI represents a critical pathway toward sustainable growth. It enhances institutional capacity to navigate complexity, improves stakeholder engagement, and ensures that infrastructure investments are both forward-looking and aligned with national and global development goals.