Artificial intelligence is beginning to reshape almost every part of the property sector, and one of the most significant developments is happening in valuations. For years, property valuations have relied on a combination of local market knowledge, comparable sales data and professional judgement. While that approach still has real value, it can also leave room for inconsistency, delay and uncertainty, especially in fast-moving markets.
Now, that may be starting to change. Researchers at The University of Manchester have developed an AI system designed to improve the accuracy of property valuations, with reported accuracy of more than 96%. In the university’s own reporting, that represents a notable step up from the roughly 70% to 85% accuracy often associated with more traditional valuation approaches.
For buyers, sellers and investors, this matters because valuation is one of the most important parts of any property decision. It influences asking prices, mortgage lending, investment planning and long-term expectations around growth. If valuations become more precise and more transparent, the knock-on effect could be significant across the wider housing market.
Why property valuations have often been imperfect
Valuing a property has never been as simple as plugging in a postcode and receiving a perfectly reliable number. Even in areas with strong transaction data, no two homes are exactly the same. Layout, condition, street-level appeal, nearby development, transport access and even changing buyer sentiment can all affect what a property is truly worth.
Traditional valuations are also shaped by timing. In a market that is moving quickly, a valuation based heavily on historic comparable sales may already be behind the curve. In slower markets, small differences between properties can distort the picture in other ways. This is one reason valuations can sometimes feel inconsistent, particularly to buyers and sellers who compare different estimates and wonder why the figures do not align.
Artificial intelligence is attractive in this context because it can process huge volumes of information far more quickly than a conventional manual process. Rather than relying on a narrower sample of comparable properties, AI models can analyse broader datasets and identify patterns that might otherwise be missed.
What makes this new AI approach different
The University of Manchester research is especially interesting because it is not simply presenting AI as a faster shortcut. The project is focused on improving both accuracy and trust in the valuation process. According to the university, Dr Yishuang Xu and her team have been working on machine learning applications in real estate, particularly where high-stakes decisions require more transparency rather than less.
That point is crucial. One of the biggest concerns around AI in property has always been the so-called “black box” problem. It is one thing for a model to generate a figure; it is another for buyers, lenders, valuers or investors to understand why that figure has been reached. In property, confidence matters. People are far more likely to trust a system if they can see that its outputs are grounded in meaningful data and can be interpreted sensibly alongside human expertise.
This is why the Manchester development feels more relevant than the usual headlines about tech disruption. It suggests that AI is not just being used to automate valuations, but to improve the quality of decision-making around them.
What this could mean for buyers and sellers
For buyers, more accurate valuations could help reduce the uncertainty that often surrounds an offer. One of the most frustrating parts of buying a property is the gap that can emerge between an agreed purchase price and a lender’s valuation. If valuation methods become more refined, there may be fewer surprises during the mortgage process and a stronger sense of confidence around what a property is actually worth.
For sellers, AI-enhanced valuation tools could make pricing strategy more informed from the beginning. Overpricing can slow down a sale and lead to repeated reductions, while underpricing can mean leaving value on the table. A more data-rich starting point could help sellers position their property more effectively in the market.
There is also a wider consumer benefit in terms of transparency. If valuation systems become better at capturing real-world market conditions, buyers and sellers may find it easier to understand how certain features, locations or improvements influence value.
A sign of where the property sector is heading
The University of Manchester’s research points to something bigger than one new tool. It reflects a wider shift in the property industry toward smarter, data-led decision-making. As AI becomes more advanced and more explainable, it is likely to influence not just valuations, but also lending, investment analysis, planning and asset management.
For anyone involved in buying, selling or investing in property, that makes this more than just an interesting tech story. It is a sign of how the market itself is evolving. In 2026, accurate valuations are no longer just about experience and comparables alone. Increasingly, they are about how data and human insight work together to produce better outcomes.
