AI is Making Your Home Cheaper (and Your Office)

Praful Krishna
6 min readNov 8, 2020

The world of real estate is often thought to be a slow adopter of technology, relying more on handshakes and glib negotiations. Increasingly, this view is turning out to be a myth. Artificial intelligence is making the world of real estate to be more nimble and more efficient. Consider these five applications below:

1. Lower Vacancies and Costs

Netflix uses AI to suggest what you should watch next. It predicts your tastes and lines up a collection that it thinks you will like. Amazon uses similar technology, called a recommendation engine, to suggest that you may like to buy an ottoman after you bought a couch. Recommendation engines are one of the oldest applications of AI. They rank order the available choices as per some metric and then display the top ones.

AI companies are now applying similar recommendation engines to all parts of the real estate value chain. They rate tenants in terms of propensity to default or to leave quickly. They rate real estate agents on their ability to get new deals. They have begun to predict the price or rent you should pay/ charge for your property, not only to maximize the dollars you get, but also for how long.

There is a whole set of futuristic technologies that add further value. For example a combination of artificial intelligence and sensors (Internet of Things) lets technology manager office spaces and communities much better. The technology analyzes various usage patterns and optimizes the various costs like HVAC, lighting, etc. It also makes the usage patterns more available to real estate agents so that they can plan capacity better.

Net result of these efforts has been to make real estate projects more viable, and hence their prices lower.

2. Efficient Securitization and Modelling

If you have ever shopped for a mortgage you may have wondered why ‘conforming’ mortgages are cheaper than others. It varies from state to state in the US, but generally conforming mortgages stipulate certain loan-to-value ratio, certain conditions e.g. single family homes or made after 19xx, and/ or certain restrictions e.g. no litigation, clear titles, etc. The reason they are so prescriptive is because if there are many mortgages that are similar in nature, someone can pool them and sell them to financial institutions who can invest billions of dollars in a set of similar loans. This process is called securitization, or converting your mortgage into a security.

Securitization reduces your cost to borrow for your home. However, traditionally it has come with a lot of strings attached. If your needs do not conform, you have had no choice but to get more expensive non-securitized mortgages.

This is changing fast with AI. AI can now assess the risk of every loan individually, and pool them together such that each of the loans in a pool is similar in risk irrespective of loan-to-value, litigation status, construction date or any other criteria. AI also helps with automatic appraisals and modelling. All this results in lower cost of borrowing.

3. Agent-less Transactions

Imagine yourself thinking about buying some piece of real estate, let’s say some commercial property for investment. The first step usually is to find out what you can afford. Part of this is to get the best mortgage rates. Then you would look at various listings to decide which ones you would like to explore further. Next, you would perhaps visit the property, learn more about it. You will negotiate. You will go through all the documents and will close the deal.

It gets even more complicated if you are selling instead of buying. Typically you would hire a real estate agent to do all this. Typically, you will pay them between three and 10% of the sale price, depending on various conditions.

AI can now automate each step of the workflow detailed above — financing pre-approvals, listing recommendations, natural language chat, 3D virtual tours, pricing benchmarks, automated discovery, etc. As the world moves towards agentless transactions, even now a single real estate agent can handle many more clients and a lot more volume. All of this makes real estate cheaper for you.

4. Marketing and Lead Generation

Often when you visit a five star beach resort, say, in Virgin Islands, you and your family are invited to a courtesy lunch by the general manager of the property. Delighted, you graciously accept. What starts at the lunch is a very high-touch, very seductive process to sell your a slice of some time-share property. You are taken through the dreams of not only owning a piece of the paradise, but also the ability to trade it for other pieces of paradise the world over.

Historically, cost of sales has been up to 70% of the price of such time shares. Marketing and lead generation is a significant cost for any real estate project, esp. if it’s a first time sale.

AI comes to the rescue of developers here. Marketing has been a core use case for AI in all sectors. Real estate is no different. AI can help developers find better leads, advise them through the customer journey (when to offer a lunch, vs. a personalized holiday card), predict the right product or bundle, suggest pricing, and create a lot of personalized collateral.

In the new world of marketing, the value of customer advocacy after a sale is sometimes as much as the value of the sale, often more. Again, AI helps with long-term relationship management and supporting customer advocacy.

AI’s prowess is being proven to make products more differentiated, competitive and cheap.

5. Better Back Office Processes

A few years ago, areal estate developer in UK signed up for a very involved and complex infrastructure project. There was a plan to begin with, for sure, but as the project progressed there were multiple occasions when either the client or the developer made some changes to the plan. They agreed on piecemeal changes in airconditioned board rooms, and relayed to the execution team through several ranks and several channels. Later on, when the client showed up for inspection, they were surprised at what was eventually built.

This may sound like a joke, but people at large real estate developers will tell you that it’s not funny. Add to this budget-overruns, delays, disputes about payments, unclear accountability, division of labor, etc. For large real estate projects, the complexity of the paperwork involved is just enormous. So much so that keeping track of all the moving pieces becomes real impossible. With this challenge comes real costs, which often are the entire profit margin for a developer.

AI is just the right solution for such back office processes. Contract management, design compliance, version control, automated legal review, etc. — there are a lot of AI applications that save waste and increase efficiency in such involved scenarios.

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AI is helping almost every aspect of the world. Why should real estate be different?

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