The impact of machine learning in CRE in 2019
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The Impact of Machine Learning in CRE in 2019
Now that the real estate market has recovered from the financial crisis of 2008, the focus has turned to investments in technology to better serve customers. Machine learning, utilization of cloud-based tools, automation of manual processes, and the internet-of-things (IoT) is creating efficiencies across the historically clunky real estate industry. The near-term impacts of adopting these technologies are potentially monumental for real estate and its customers. Here are a few highlights of what we can expect from the advent of new technology like machine learning in CRE in the new year.
Machine learning & predictive applications for residential real estate
The e-commerce and consumer technology powerhouses that rule the internet will likely provide the blueprint for the residential market’s predictable tech push. Just as consumers can pay a credit card bill and setup a dinner reservation without leaving their couch, residential tenants are looking for ease and convenience from their landlords and property managers when it comes to paying rent and submitting maintenance requests. As consumers grow accustomed to the on-demand, tech-based world in which we live, it will be an expectation, not a perk, that residential companies follow suit.
Machine learning & predictive maintenance for manufacturing & heavy industrial
Predictive tech has plugged into the real estate industry by demonstrating its value to the manufacturing and heavy industrial sectors. Utilizing actual trends, manufacturing expands transparency into value streams, resulting in higher levels of overall efficiency. Real estate professionals looking to leverage predictive tech should take note from the lean principle approach of these sectors and dive deeper into the previously murky waters of AI. There are three major categories of AI that have potential for near-term adoption in the real estate industry.
1. Image Recognition
Real estate is driven by images. Images are what sell properties and lease spaces. It is the first thing every client wants to see. Results from search engines like Google are derived from written descriptions of an image’s content rather than the image itself. This leads to variable descriptions, human error, and other inaccuracies.
Artificial intelligence in image recognition software has reached the stage where it can understand, process, and describe images with high accuracy. AI can identify actions, people, animals, and now even mood and emotion. Imagine your clients being equipped to find images that lead them deeper into the buying process.
2. AI in Property Management
AI now streamlines processes for the tenants and landlords across real estate sectors. Advanced machine learning helps property managers find new tenants, proactively recommend maintenance, automate manual processes, and locate cost-effective vendors. By the same token, tenants can pay rent online, report and even resolve issues through virtual assistants, or chatbots.
While only a human can lead a physical tour, virtual tours are emerging along with bots that can answer questions regarding leasing, square footage, and other topics of interest. As machine learning advances, bots will be able to answer more specific queries, leading to seamless leasing and some issue resolution for both tenants and property management.
There is a lot to look forward to in the world of real estate when it comes to machine learning. Technology will be able to match people with properties after learning their preferences. Machine learning has a lot of potential to shake the real estate industry in new and inventive ways that change how things operate – all for the better!
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