Revolutionising Real Estate: An In-Depth Q&A with Andrew Knight, Data Standards Director at RICS, on the Impact of AI

In the dynamic landscape of the real estate industry, the integration of Artificial Intelligence (AI) is reshaping traditional practices, ushering in a new era of efficiency and innovation. In this exclusive Q&A session with Andrew Knight, an industry expert at the forefront of AI in real estate, we delve into the current role of AI and its transformative effects on various facets of the property lifecycle.

What is the current role of AI in the real estate industry and how is it transforming traditional practices?

AI is becoming embedded in software right across the property lifecycle and is often hidden from view as part of solutions addressing automated valuation, image recognition, building operations, data conversion aggregation and analysis, and scheduling. With the recent rise of generative AI, we are seeing applications around design, marketing materials, querying of complex documents and many others! 

Andrew Knight, Data Standards Director at RICS

Can you share some examples of successful AI implementations in real estate, and the benefits they've brought to professionals and clients alike?

AI is already widely used in image recognition to interpret people and vehicle movements, optimise HVAC performance, convert unstructured lease and other datasets into structured data, and to schedule complex construction projects. This streamlines data management and accessibility, making it easier for professionals to search, analyse, and extract insights from large volumes of information.

Concerns about bias in AI algorithms have been raised in various industries. How can businesses within the real estate sector address and mitigate bias in AI applications?

It is crucial that property professionals engage with AI solutions to understand how they have been trained and developed, the data that is being used to train and operate them, and how potential bias is being avoided at both the design and operational phase. The concept of explainability is important here in that it should allow AI models to produce their output with some sense of their reasoning.

Data privacy and security are also critical concerns in the property sector. How can we ensure the responsible use of AI while safeguarding sensitive information?

Just because we can use AI for a particular purpose does not mean that we should always employ AI – particularly when the use case is high-risk. In addition to complying with GDPR and other similar regulations, senior leaders must consider the ethical implications of AI and the data that it uses as well as understanding commercial sensitivities and internal information barriers across their organisation and supply chains.


How can AI software help with sustainability and carbon emissions within the real estate industry?

AI is already delivering tremendous returns on investment with its ability to optimise the operation of HVAC and to improve predictive maintenance. AI is also being used to aggregate and manage biodiversity data so that in addition to the net zero agenda we can harness the power of AI across the full range of sustainability issues.

One key piece of advice you would offer a company looking to implement AI tools within their practice.

Engage and understand the models and data being used, focus on real business issues that will generate a return on investment, and retain your people’s professional scepticism when using AI output when making decisions that affect your organisation, your customers, and other stakeholders.