Artificial intelligence is among the fastest-growing innovations in the modern world. Thousands of startups and pre-AI tech companies are investing in this technology today, hoping to gain a head start in a field that promises to remake human civilization’s essence completely. No fields are unaffected by this technology, meaning that it will transform the work of, for example, real estate experts and even teachers. In this article, our goal is to look at the developments in the real estate sector, helping our readers understand how artificial intelligence will affect experts in this sector and remake skill demands in the industry during the upcoming years.
Use case 1. Offer analysis
The first use case of artificial intelligence in real estate undoubtedly involves offer analysis. A significant part of everyday work performed by real estate experts consists of studying various customer offers. Some people may want to buy property; others seek to sell it. Finding worthwhile business deals in this massive amount of data is often tricky. Yes, the appearance of Web 2.0 led to the rise of better sorting tools for most MLS frameworks. However, many of them are too inflexible to adjust to the ever-changing nature of the real estate market. An AI real estate solutions company can solve this problem once and for all through a machine learning tool capable of analyzing vast amounts of information and presenting the experts with in-depth reasoning for their choices.
Let’s review a potential use case for this technological application on a realistic example. Imagine a real estate expert who mostly gains their income from completed deals. In normal conditions, it may be relatively easy for them to navigate the market, as it is likely to have many predictable patterns. Still, searching for those patterns may require an investment of 1 and 2 hours a day, even in the best conditions. Even with this moderate investment of time, the expert may be losing 5 to 10 hours per week, which could have been dedicated to finalizing deals. Artificial intelligence can halve these time expenditures by analyzing the market and preparing a list of perfect properties for the aforementioned expert, significantly decreasing the time they will have to spend on finding properties and freeing it up for high-quality negotiations with buyers and sellers. In short, the technology significantly reduces the average time spent per offer analysis.
Use case 2. Automated advertisements and communication
One more suboptimal time expenditure encountered by many real estate experts involves advertisement creation and preliminary communication with customers (for example, when they want to simply learn about the market without pursuing any purchases). Generative artificial intelligence offers a strong solution to this long-term problem. Firstly, an adequately configured AI with high-quality prompts can create advanced advertisements based on somewhat fragmented information instantaneously. The process can be sped up even further if organized properly into high-quality forms. As a result, the technology in question offers the first direction for optimization in this case: it is often possible to significantly reduce the time spent advertising various products.
Secondly, this technology has some additional positive effects to consider. In many cases, as mentioned before, experts do not communicate with potential customers but rather with individuals who simply want to analyze the market. Their decision to invest in real estate may come significantly later. In this light, many real estate experts may be spending time on communication that is unlikely to yield them any long-term benefits. Artificial intelligence offers a high-quality solution to this problem by allowing the automation of many types of communication. For example, an AI can easily find information on the existing price structure of the market and present all this data to a customer. Common questions about the widespread procedures for purchasing real estate are also easy to answer based on the preceding information. As a result, AI can filter many conversations that are unlikely to end up in purchases without upsetting the users by the absence of a response. Using this technology, real estate experts can optimize their communication, cutting out the conversations that are not feasible from an economic standpoint.
Use case 3. Data analytics
Lastly, AI allows for data analytics automation in the current market. Many real estate experts do not engage in an in-depth analysis of their activities. Some do not see any reason to do this; others simply do not have any resources to implement such practices). In our opinion, improper analytics may often result in adverse long-term outcomes. For example, the signs of an inefficient sales or communication strategy may be invisible at first due to the slow evolution of the market toward new requirements. A specialist who does not analyze those factors may eventually find a surprising change of circumstances, which would have been evident if data analytics frameworks were used.
Analyzing one’s performance through analytics is an early warning system for most experts. Artificial intelligence is a technology that allows one to automate those processes fully. Once you create a high-quality framework for data collection, it can analyze all the requisite data more or less automatically from that point on. With the help of this method, a real estate expert can receive vital data necessary for changing their strategy without making any prolonged time investments.
Conclusions
To summarize, AI in real estate will become essential for the long-term evolution and development of the field. The earlier one invests in this field, the better because companies and individuals using artificial intelligence will likely gain an overwhelming advantage in the upcoming years. If you want to develop your AI solution for real estate, the best option is to communicate and cooperate with real experts. We recommend looking into companies with advanced experience in the real estate and software development markets, such as Keenethics.
