Abstract
This paper proposes an original co-adaptive workflow termed Valuer-in-the-Loop, which establishes a pathway for integrating artificial intelligence within real estate valuation. Structural changes in real estate markets, driven by the rise of hybrid working, e-retail and evolving occupier behaviours, are reshaping the built environment and increasing uncertainty within real estate markets. These changes are accelerating demand for advanced property technologies capable of supporting risk analysis and investment profiling under rapidly evolving market conditions. The increasing adoption of artificial intelligence within real estate valuation raises fundamental questions regarding the relationship between computational analysis and professional judgement. While advances in automated valuation models have improved the ability to analyse large volumes of market data, valuation remains a professional activity in which the application of professional judgement is central. Adopting a deductive research design based on a novel conceptual review, the paper synthesises professional valuation standards and valuation theory to conceptualise real estate valuation as a structured workflow. Within this workflow, valuation models are positioned as quantitative tools that are used to implement valuation methods in whole or in part within a broader automated valuation system. The workflow provides an original theoretical contribution to the field by clarifying and extending the hierarchical relationship between valuation approaches, methods and models. It also newly conceptualises AI-enabled real estate valuation as a co-adaptive process, termed herein “Valuer-in-the-Loop”, through which valuation knowledge is represented through repeated interactions between the valuer and the automated valuation system. In practice, the Valuer-in-the-Loop workflow provides a conceptual basis for professional bodies and practising valuers to integrate AI within established valuation workflows, while offering a set of principles for technology developers and researchers to design co-adaptive AI systems.
| Original language | English |
|---|---|
| Article number | 3727 |
| Number of pages | 21 |
| Journal | Buildings |
| Volume | 16 |
| Issue number | 18 |
| DOIs | |
| Publication status | Published - 18 Sept 2026 |
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