Artificial intelligence for real estate valuation in Uganda

Abstract

This research explored the current state, challenges, and potential mechanisms for adopting Artificial Intelligence (AI) in real estate valuation in Uganda. The study gathered insights from property valuers to assess the feasibility of AI integration within Uganda’s property market. The findings revealed a growing awareness of AI’s potential to improve valuation efficiency, accuracy, and objectivity. Respondents acknowledged that AI could automate valuation processes, reduce human error, and support predictive analysis. However, uptake remained limited due to significant barriers, such as financial constraints, insufficient AI infrastructure, a shortage of skilled professionals, data quality issues, and trust concerns surrounding AI-generated outputs. Additionally, cultural resistance, particularly among older professionals, further hindered adoption. The study identified several key recommendations to support AI integration. It emphasized the importance of capacity building initiatives, including AI training programs within academic curricula, continuous professional development courses, and partnerships with global AI experts. Infrastructure development was highlighted as a crucial factor, with the digitization of land and property records and the creation of a centralized property database seen as foundational steps. The research also stressed the need for policy and governance, urging the development of a national AI policy tailored to the real estate sector, which should include provisions for data governance, algorithm transparency, and legal recognition of AI-generated valuations. Financial investment from the government, along with public private partnerships, was identified as critical for the long-term sustainability of AI adoption. Furthermore, stakeholder engagement and inclusion were deemed essential for fostering trust and ensuring equitable access to AI-enabled services. The research concluded that, while AI held significant promise for transforming property valuation in Uganda, its successful adoption required a coordinated effort involving government, academia, industry, and local communities. Further research into algorithmic fairness, transparency, and client perceptions was recommended to guide future AI integration in Uganda’s property market.