Adoption of artificial intelligence to mitigate and resolve disputes in the Sri Lankan construction industry

Abstract

Construction industry is a sector frequently affected by conflicts arising from contractual ambiguities, delayed payments, scope variations, and quality deficiencies. These disputes often cause project delays, cost overruns, and deterioration of professional relationships, while conventional mechanisms such as litigation and arbitration remain adversarial, time consuming, and costly. Consequently, there is a clear need for more efficient, technology enabled approaches to dispute management such as natural language processing, machine learning, and expert systems. These technologies can support automated contract review, prediction of claims, early identification of dispute risks, and data driven support for negotiation and mediation. However, despite the global diffusion of such tools, their integration into the Sri Lankan construction sector remains limited. Therefore, this study examines the adoption of artificial intelligence (AI) technologies to enhance dispute mitigation and resolution within the Sri Lankan construction industry. It aims to assess the current level of awareness and willingness among industry professionals to implement AI tools, alongside evaluating the perceived benefits and utility of these technologies in managing construction disputes. The study employed a quantitative research design and targets construction and information technology professionals actively engaged in the sector. Data were collected using structured questionnaires developed from the Technology Acceptance Model, Innovation Diffusion Theory, and Institutional Theory to capture awareness, perceived usefulness, perceived ease of use, and institutional pressures. The data are analysed using descriptive statistics to concerning the determinants of AI adoption intention. The findings indicate that perceived usefulness and awareness of AI are the most influential drivers of willingness to adopt AI based tools, while technological complexity, regulatory ambiguity, organizational resistance, and cost related concerns significantly hinder adoption. Cognitive and institutional factors emerge as more critical than mere technological readiness. The study proposes strategic actions including targeted professional training, phased implementation of AI solutions, clearer regulatory guidance, and investment in digital infrastructure. These initiatives are expected to narrow the gap between AI’s potential and its practical deployment, and to support the evolution of a more transparent, efficient, and collaborative dispute resolution environment aligned with Sri Lanka’s long term development objectives.