Artificial intelligence is revolutionising all sectors of the economy and property is no different. Whether it is landlords trying to decide whether a new property would make a good investment or tenants trying to find a new home that exactly matches their requirements, AI can help.
AI is still in its infancy, but companies like Spotahome are already using the technology to verify both landlords and tenants on their platform, whilst others have implemented large language models to better understand tenant searches, or created automated valuation models to more accurately set rent levels.
How AI is changing how landlords operate
Landlords need to be on the constant lookout for new opportunities to grow their portfolio, track the performance of their current investments, find new tenants for empty properties, estimate the refurbishment costs and gross development value (GDV) of properties, and keep agents, brokers, and tenants regularly updated. The information flow can be overwhelming and trying to switch between numerous different tools to create a single unified snapshot can be a gargantuan task.
Therefore, it is of little surprise that technology firms see the property sector as a major source of growth. Many PropTech firms have attempted to solve one or two of the wealth of issues facing landlords over the last decade, but with AI everything can be tied together and simplified.
AI tools can do the legwork to keep property investors on top of their portfolio with easy-to-understand dashboards. These can include overviews of a landlord’s own financials, but also bring in information from third parties which can highlight how a portfolio is performing compared to others and find gaps and opportunities for potential future deals.
AI can also scour the web for local information about property refurbishment and development costs and nearby house prices to help investors make the right decision on a potential new property. It can verify tenant information and help protect against fraud and draft the emails to keep agents, brokers, and tenants updated with any changes that may affect them.
Even the question of how much to charge for rent and when to put up prices an be helped with AI. Historically, rental valuations relied heavily on the experience of agents and broad comparisons with similar properties in the area, which was often subjective and vulnerable to outdated or incomplete data. Now, AI-powered Automated Valuation Models (AVMs) allow landlords to set rent based on a combination of up-to-the-minute market data, seasonal demand patterns, and property-specific factors such as amenities, renovations, or recent changes to local infrastructure.
A series of tasks that could have taken weeks or months and possibly involved a handful of additional consultants for help can now be done with a few clicks. Data that was previously siloed can now be interpreted in a holistic way. The AI revolution has come to property.
How is AI impacting tenants?
Artificial intelligence is already helping tenants find potential new properties to let, with large language models (LLMs) making sense of real human queries and turning them into real property searches. Where previously tenants might need to have a broad understanding of a area before narrowing their search, they can now say something as simple as “A 3 bedroom property near a public park with nearby cycle lanes, good public transport links, and a large supermarket”. Trying to filter a traditional property search like this would take hours or days of research.
Big data platforms can also offer incredibly detailed neighbourhood profiles, pulling in crime statistics, school ratings, transport options, air quality indexes, and even social media reviews of local businesses. All this information means tenants can make more informed choices about where they want to live, balancing their budget with other lifestyle factors.
AI can also helps tenants filter out potential bad landlords by scouring the web for information about the landlord and previous tenants as well as searching public databases for any other potential issues with the property that have been flagged.