The Future of AI in Property

From chatbots to online listings and virtual tours, AI-powered technology has already found its way into many facets of UK Estate Agency. It should not be ignored because, in our opinion, while AI will never match human capabilities, it is a phenomenal tool in the hands of a tech-savvy human Virtual Assistant. We predict that while AI will never replace human estate agent teams, those who do not use AI tools will be replaced by those who do.

AI – what’s the big deal?

The Third Industrial Revolution – starting in the late 20^th century – has been a period of radical technological advancement. It has totally transformed many industries, including manufacturing, transportation, retail and healthcare. The most profound catalyst of change has been the electronics industry. Through advances in electronics, the first industrial automation devices were developed and so were personal computers. Today, at the sharp end of the Third Industrial Revolution, the rise of AI is the next profound catalyst for advancement.

Here is a selection of advanced AI applications that are already a reality*:

Natural language processing (NLP)

Natural language processing (NLP) is a sub-category of AI designed to bridge the gap between human and computer communication. For example:

• Chatbots are computer programmes that are already commonly used to interact with customers by text or audio. Next level NLP already has vastly enhanced capabilities. In cognitive retail, human capabilities can be integrated with automated customer relationship management (CRM) products to provide “human” levels of service via online platforms. This AI application uses machine learning to make informed product recommendations based on customer history, location and other data.
• New language-based technological advancements in AI will vastly improve people’s voice activated web navigation and searching experience. This type of hands-free internet interaction – facilitating generative voice to type and type to voice interaction – will improve information accessibility for individuals with a disability or nominal technological expertise. Earlier in the year, Elon Musk’s brain-chip startup Neuralink livestreamed its first patient, Nolan Arbaugh, who is paralysed below the shoulders and who is now implanted with a chip, playing online chess and moving his laptop cursor by thought.

Machine learning

Machine learning is an application of AI that allows systems to process data and then “learn” to improve the performance of a specific task without interim programming. Deep learning is an advanced form of machine learning that can simulate human learning patterns. This allows the AI to gain an understanding of unstructured data. It can also formulate intelligent decisions based on data analysis. For example:

• In the field of bioinformatics, scientists use deep learning AI-software to identify patterns in massive data sets, such as sequenced genomes. This analysis can help in the development of new drugs to treat diseases by determining which proteins are encoded by a certain gene.
• Emotional detection systems powered by deep learning AI can detect human emotions without any visual input. Researchers at MIT have developed a system that learns to identify human emotions based on heartbeat data collected by wireless signals. This technology could one day be used by law enforcement as lie detectors or within smart homes to detect if an occupant is experiencing a heart attack.
• While NLP allows Chatbots to interact easily with customers, deep learning allows them to locate and provide the requested information beyond scripting.

Machine perception

Machine perception is the ability of a system to simulate the human perception of the world. AI uses machine perception to extract information from different data sources. For example:

• In autonomous delivery, companies are increasingly using AI for commercial navigation purposes. For example: Amazon Scout is a small, autonomous delivery robot that can handle “last mile” deliveries. The robot uses sensors to navigate sidewalks and avoid obstacles and pedestrians. Amazon has been testing Scout in selected areas in the United States.
• Geospatial analytics leverages geographic information, spatial data, location data, and increasingly, high-resolution imagery, computer vision, and other forms of machine perception AI to extract structured data that can be used for specific applications and industries. Today, AI-powered satellites can track economic trends from space. For example, the company, Orbital Insight, can predict retail sales based on satellite images of retail store parking lots.