There’s something of a misunderstanding in the UK property industry that agents are luddites, clinging to fax machines and Rolodexes, but quite the opposite is true. Sales and letting agents like nothing more than finding new efficiencies – whether through careful outsourcing, digital signatures or virtual tours, begging the question, Are you embracing AI?
Now, a new piece of research indicates that property is ready for a greater integration of AI. The teams at Vouch and Goodlord surveyed over 400 letting agents and found almost half were optimistic about the adoption of AI tools across the industry. In addition, 70% said they thought lettings professionals were open to the adoption of new technology, while 60% believed that the lettings industry should use technology more to improve the customer experience.
Elsewhere, analysis by Landmark Information Group found 94% of estate agents surveyed believe that by 2028, admin tasks will be largely automated, allowing them to concentrate on generating revenue.
Examples of property-related AI
The full depth and breadth of AI is developing every day but here are some of its applications in the property sector:
Optical Character Recognition (OCR) Technology
This is the process of extracting text that appears on an image, such as a scanned bank statement and hand-written fields on an application form. OCR will convert the image text into a text document that can be edited, searched and added to.
Digital identity document validation technology (IDVT)
Already promoted by the Government, IDVT software with built-in fraud detection allows landlords and letting agents to validate global identity documents, such as passports, ID cards and driving licences, in seconds so they meet Right to Rent obligations. The details can also be extracted into a PDF or spreadsheet.
Open Banking
This allows for a quicker and more transparent snapshot of someone’s finances using a one-time access authorisation. Tenants and homebuyers can use Open Banking to electronically share financial records dating back 12 months with an agent, so the professionals can check a source of deposit fund or confirm an income as part of affordability checks. This leads to speedier decisions and quicker referencing.
Chatbots
Chatbots exist for both home movers and industry professionals. Although their use is in no way replacing humans, they are helpful out of hours and when people can’t speak on the telephone. As well as answering questions, chatbots are capable of booking viewings and valuations, and can even send out property alerts. On the business-to-business side, Reapit has recently launched Fi – designed to instantly answer questions fielded by its users. Soon, progress in natural language processing (NLP) will allow chatbots to engage in more conversational, meaningful dialogue.
Property description tools
Reapit has recently launched an AI-powered property description tool that automatically generates property descriptions. The base copy is thought to save agents approximately 10 minutes per property description, although the text is customisable. This joins Street.co.uk’s AI offering – a custom feature that creates agent-specific content, including property descriptions, emails and photo enhancements.
ChatGPT
ONP Group, which incorporates O’Neill Patient Solicitors, Grindeys and Cavendish Legal Group, has recently integrated with ChatGPT to automate document analysis in the conveyancing and remortgage process. Necessary information will be extracted automatically, resulting in a significant reduction in time that will allow conveyancers to deliver a more personalised service to clients. Search Acumen, the data provider for conveyancers, is also trialling the integration of ChatGPT into its existing data-led portal for lawyers.
Data analysis
One of the biggest advantages of AI is being able to handle, and then analyse, huge volumes of current and historical data looking for patterns and behavioural trends. The results help agents target their services and understand their customers’ needs. For example, mining data held in an agent’s CRM system can predict the people most likely to move home soon or switch estate agents. Spectre AI and TwentyEA’s Forecast tool are already yielding AI-generated instructions for agents – all possible through tracking, data algorithms and machine learning.
Property valuations
The number crunching of big data by AI is now behind some of the most accurate property valuations and market insights. PriceHubble is one of the market-leading suppliers, with its Property Analyser tool providing detailed analysis, year-on-year price comparisons, historic value trends and average price per sqm. Its valuations can be wrapped up in a white labelled report with persuasive market insights.
While there are already smaller conversations happening in relation to the specific uses of AI in agency, the bigger conversation is whether proptech will replace humans. The general consensus is no. AI is designed to liberate professionals of repetitive admin tasks so they can spend more time delivering exceptional customer service and generating revenue. AI is also there to reduce the margin for error when checking documents and analysing datasets in a way humans can’t.
We’ve seen this reported time and time again and there is some truth in the phrase ‘AI won’t replace agents but agents who don’t use AI will be replaced’. Where do you stand on the matter?
I can definitely see a lot of potential in using LLMs like a templating service. The entire point of an LLM is to generate something that, on a surface level, looks correct, which is basically what a template is.
This is pretty much the only way that I use AI. It can brainstorm 50 ideas faster than I can and format them in a way that I can actually get started on projects rather than planning out each step.
AI is pretty strong at what I have been calling “permanent facts”. Using any song as an example, it will always have the same key, tempo, scales, etc. As such, when asking for details about a song, listing out the key, scales, tempo, and asking it to show unconventional scales that will play over it. Another example of a permanent fact would be the death date of someone, as that isn’t really going to be changing.
On the other hand, temporary facts are where hallucination and other inaccuracies come in. There’s no way for LLM’s to get new information, so it doesn’t know about career changes, current ages or net worth. You can utilize permanent facts to get accurate information about temporary facts, but that’s not nearly as useful. I think one of the major issues people have with LLM’s (model creation aside) is that our society really values temporary facts, and so when it gets it wrong people like to point at that as a fault. Which it certainly is, but to me it’s kind of like pointing at Photoshop and laughing that it can’t even be used to write a book - like, OK but that’s not really it’s purpose?
I think another example of LLM’s definitely being useful was all of those privacy nightmare Excel/Sheets plugins. Privacy aside, that’s basically the ideal use-case for LLM’s as you are pointing out Permanent Facts (the data in cells A-Z) and having it sort them in some fashion. I’ve seen a lot of LLM hallucinations for sure, but I’ve also seen a lot of consistency when actually using it as intended. I’ve yet to have it be “wrong” when I was testing my music information template or when sorting out data in excel.
Much outside of that though, no. It’s only useful as getting mass amounts of theory in a short session, not so much for being reliable in that information. That might sound like a bad tool, but as mentioned it has plenty of use-cases, people are just using it as a tool very, very poorly. (It can also be used maliciously more easily than most other tools, which definitely prohibits its status as a “good” tool.)