Market Insight

Where is AI going in the property sector and what are the benefits & potential risks?

Artificial Intelligence (AI) and its use in Proptech is growing in momentum.
May 8, 2024
Everyone is talking about Artificial Intelligence (AI) and great strides are being made in this area – both from the software / app developer side as well as in the burgeoning area of risk management.

But how is AI being used in the property sector, what benefits does it bring, and what are the potential risks?

Charlie Nicholson, Partner at Vail Williams, explores how the potential of AI is being unleashed in the property sector.

AI and ‘proptech’ innovations are disrupting the property sector. It has become part of our regular vernacular and is being increasingly integrated into real estate, in one form or another.

Whilst the term AI is en vogue, the reality is that AI, in various forms of PropTech, has been used by us for some time now.

Where using data for predictive analytics, our cloud-based property management system, or in the automation of certain processes using machine learning models and manipulation of open-source datasets.

Of course, artificial intelligence has boundless possibilities – from improved and more informed decision-making based on data, to process efficiency, and improvements in customer experience thanks to efficiency gains and more.

How is AI being applied in the property sector?
Predictive Analytics

Property firms use AI-powered predictive analytics tools to forecast property market trends, identify investment opportunities, and predict property values.

These tools analyse large datasets including historical sales data, demographic information, economic indicators, and even social media sentiment to provide insights into market dynamics.

There is significant benefit in this, however, there is much to be said for the experience and knowledge of regional property agents on the ground too.

Smart Property Management

AI is also used in property management systems to optimise building operations, enhance energy efficiency, and improve maintenance processes.

Smart building technologies such as IoT sensors, predictive maintenance algorithms, and automated HVAC systems are integrated with AI platforms to monitor building performance in real-time and proactively address issues.

In a similar way, we use our own tools to support clients with the management of their property portfolios through a cloud-based Tenant Portal, facility management tool, Elogs and MRI Software to give clients data insight, risk management and convenience in the management of their properties / portfolio.

Virtual Assistants and Chatbots

AI-driven virtual assistants and chatbots are being deployed by some commercial property companies and estate agents to enhance customer service and streamline communication with clients.

These tools can do everything from handling inquiries, scheduling property viewings, and providing personalised recommendations, to assisting with the buying or renting process.

However, what this sort of service also risks, is that removal of the ‘people experience’ which can really matter.

Property Valuations

AI algorithms are being used by some companies to automate property valuation processes, providing more accurate and efficient assessments compared to traditional methods.

Machine learning models trained on large datasets of property transactions can analyse various factors such as location, size, amenities, and market trends to estimate property values.

However, AI should not be relied upon solely in the production of property valuations. These ought to always be thoroughly reviewed for accuracy by the boots on the ground. You cannot remove the importance of human knowledge around the specifics of each property.

Personalised Recommendations

Around for some time now, AI-driven recommendation engines are being employed by property listing platforms to deliver personalised property suggestions to users based on their preferences, search history, and behaviour patterns.

These recommendation systems leverage machine learning algorithms to analyse user data and identify properties that match their criteria. However, what such systems don’t do is offer up a potential curve ball option that they may not have thought of.

Again, this is where there is true value in a property agent who spends time in getting to know a business and its culture and might throw in a potential property that they know would work but might not necessarily be within their geographical specification.

Risk Assessment

AI is also being used for risk assessment in property transactions, including mortgage lending and insurance underwriting. Machine learning models analyse factors such as borrower profiles, property characteristics, and market conditions to evaluate the likelihood of default or insurance claims, enabling more informed decision-making by lenders and insurers.

Again, the importance of first-hand investigation by a local surveyor who knows the property, or who is able to monitor ongoing works, cannot be underestimated.

Virtual Reality (VR) and Augmented Reality (AR)

AI-powered VR and AR technologies continue to transform the way properties are marketed and showcased.

Virtual tours and 3D property visualisations created using AI algorithms provide immersive experiences for potential buyers or tenants, allowing them to explore properties remotely and even visualise themselves living or working in the space.


These examples of how AI is driving innovation and transforming the property sector don’t come without their risks, including:

Data Privacy and Security

AI often relies on vast amounts of sensitive data, including personal information about tenants, property owners, and financial transactions.

If adequate measures are not in place to protect this information, data breaches or misuse of data are possible, with potential legal and reputational repercussions.

Bias and Fairness

AI algorithms may inadvertently perpetuate biases present in historical data, leading to discriminatory outcomes in property-related decisions such as pricing, lending, and tenant selection.

This is where careful data selection, algorithm design and ongoing monitoring are vital, to ensure fairness and equity.

Accuracy and Reliability

AI models used for property valuation, market analysis and decision-making are only as accurate as the data they’re trained on.

Errors or inaccuracies in input data can lead to flawed predictions or recommendations, potentially resulting in financial losses or missed opportunities for property stakeholders, so great care must be taken.

Lack of Transparency

AI algorithms, particularly complex machine learning models, can be opaque and difficult to interpret, making it challenging to understand how they arrive at their decisions.

This lack of transparency raises concerns about accountability and trustworthiness, especially in high-stakes property transactions or regulatory compliance.

Dependency on Technology

Overreliance on AI systems without human oversight or intervention can lead to a loss of human judgment and decision-making capabilities, not to mention the importance of the client relationship.

We, as property professionals, need to balance the use of AI with human expertise to ensure that critical factors such as ethics, empathy, and creativity are not overlooked in property-related processes.

Regulatory Compliance

Regulatory and ethical considerations, particularly concerning data protection, consumer rights, and algorithmic accountability, are of great concern currently.

The property sector is navigating the evolving legal frameworks and industry standards to ensure compliance with relevant regulations and mitigate the legal risks associated with AI deployment.

Addressing these risks requires a multidisciplinary approach involving collaboration between technologists, policymakers, industry stakeholders, and society to develop responsible AI practices and governance mechanisms in the property sector – something which is evolving on a day-to-day basis.

How we use AI & Proptech to benefit clients

Here are just some examples of how we use Artificial Intelligence (AI) and cloud-based proptech to benefit clients whilst remaining a people business founded on relationships and trust.

  1. VW Tenant Portal, Elogs, MRI Software – asset management
  2. VW HUB – proprietary market data and insight
  3. Kato – agency occupier / landlord matching
  4. CoStar – third party market research
  5. Landstack – land registry and planning data
  6. Salesforce, FOI data – business rates evidence

As this technology continues to evolve, we can expect further advancements and applications of AI across various aspects of real estate, from property development and construction to sales and management.

The key will be ensuring that firms can keep pace with the associated regulatory requirements, whilst also ensuring that the all-important relationship between client and adviser remains a core focus.

Vail Williams - property buying and selling services