Assessing The Capabilities of AI in Private Real Estate Development Within the Construction Sector
Abstract
In Mumbai’s fast-growing private real estate construction sector, persistent challenges—cost overruns, schedule delays, and inconsistent quality—continue to limit project performance despite rising demand and increasing urban pressures. Artificial Intelligence (AI) has emerged globally as a transformative tool capable of reshaping construction planning, execution, and monitoring. Yet, in Mumbai, AI adoption remains at a formative stage, shaped by a complex interplay of technological limitations, cultural resistance, and organisational readiness. This study explores how AI is currently being used, where it creates value, and what barriers must be overcome for meaningful transformation. A mixed-methods research design was employed to capture both the breadth and depth of AI adoption. Quantitative insights were gathered through a structured survey of 99 construction professionals, spanning developers, engineers, consultants, and project managers. To complement this, qualitative interviews and focus group discussions were conducted with industry experts to understand their lived experiences, perceptions, and concerns regarding AI-enabled practices. Data were analysed using descriptive statistics, factor analysis, and thematic coding to produce an integrated, evidence-based understanding of AI’s real-world impact within Mumbai’s construction environment. Findings reveal that while AI adoption is still emerging, its footprint is steadily expanding. The most recognised and frequently applied AI tools include predictive analytics for cost estimation, automated scheduling systems, and computer-vision-based quality inspections. Respondents involved in AI-enabled projects reported heightened confidence in the technology’s potential to enhance efficiency, reduce rework, and improve decision-making. However, this optimism exists alongside significant obstacles. The study identifies notable barriers such as low digital literacy, fragmented data systems, regulatory ambiguity, and organisational cultural resistance. Many firms struggle to integrate AI into legacy workflows, and small and medium-sized enterprises face higher financial and technical hurdles. The discussion highlights that successful AI-enabled transformation requires more than just technological investment—it demands structural, cultural, and behavioural shifts within organisations. AI’s impact is therefore as socio-technical as it is operational, requiring alignment across people, processes, and platforms. This research confirms that AI holds strong promise for reducing chronic inefficiencies in Mumbai’s real estate construction sector. Yet, the gap between theoretical potential and on-ground performance remains wide. To bridge this divide, organisations must adopt a phased, context-appropriate strategy that prioritises digital literacy, data standardisation, regulatory clarity, and targeted workforce upskilling. The study offers a practical implementation roadmap tailored to Mumbai’s unique ecosystem, serving as a valuable resource for developers, project managers, policymakers, and technology providers. Ultimately, AI is positioned not as a replacement for human expertise, but as a powerful enabler of smarter, safer, and more resilient urban development.
Citations
IRE Journals:
Dr. Ruchi Natekar, PMP, FIE, Dr. Dulari Rajput "Assessing The Capabilities of AI in Private Real Estate Development Within the Construction Sector" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 308-315 https://doi.org/10.64388/IREV9I6-1712568
IEEE:
Dr. Ruchi Natekar, PMP, FIE, Dr. Dulari Rajput
"Assessing The Capabilities of AI in Private Real Estate Development Within the Construction Sector" Iconic Research And Engineering Journals, 9(6) https://doi.org/10.64388/IREV9I6-1712568
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