Artificial intelligence is hot everywhere, but it’s more than just hot for real estate – it’s poised to reshape the entire industry. To stay relevant, Realtors, brokerages and agents need to know how to use AI to their advantage and understand how it’s empowering consumers.

So, let’s break it down. What, exactly, can AI do for real estate pros?

“AI can be a complete game changer and give you an edge against your competition,” David Conroy, director of Emerging Technology for the National Association of Realtors, said at November’s 2020 REALTORS Conference & Expo.

That competitive edge can come from using Big Data to work smarter: being more efficient + closing transactions more quickly + cutting costs + marketing more strategically = more happy clients and more money for agents.

The term “Big Data” can be intimidating to non-techies, but don’t worry. No one needs to add “data scientist” to their LinkedIn profile. But even as venture capital is pouring into proptech startups, the real estate industry as a whole still seems to be lagging.

Actual data scientist Julianne Heller of NAR says some companies think it will be too costly and take too much work. They don’t understand or trust it. There’s also a fear that AI could replace people and cut jobs.

“AI does not equate to replacement, but it supports human work and makes our lives easier,” Heller said at the National Association of Realtors’ conference. “AI can improve the buyer and seller experience.”

What AI is

To put it simply, artificial intelligence is what lets Amazon’s Alexa talk to you and cars drive themselves. Its algorithms use data to mimic human intelligence, including learning and reasoning. Then there’s machine learning, where algorithms analyze enormous amounts of data to make predictions and assist with decision making. We’re putting them both under the same AI umbrella.

What AI can do

As AI continues to learn and evolve, the benefits for real estate professionals and consumers are getting easier to see.

Access to data lets consumers feel more in control. Researching properties on sites like Zillow and Trulia lets consumers feel like they can make smarter decisions. Now marketplace sites are using AI to better understand consumer preferences to improve their search experience. On sites like HomeLight, AI lets buyers and sellers find agents with specific experience who are likely to make them or save them the most money.

More nuanced pricing is more accurate. The incredible number of data points lets agents go beyond pulling the usual three comps from MLS. By analyzing past data, AI can put a value on things like proximity to Starbucks, local Yelp reviews and what buyers with similar preferences have paid for similar properties. It’s AI that lets Zillow’s Zestimates “read” listing photos, identify features like granite countertops and adjust pricing based on the value they add.

Buyers get better matches with potential homes. AI can go beyond the usual filters and tap preferences of similar buyers to narrow potential candidates or expand the search area. Zeroing in on the closest-to-perfect properties saves time and money and lowers clients’ stress as transactions close more quickly.

Chatbots offer 24/7 communication between clients and agents. A client who just thought of a quick question before bedtime might be able to get an answer while her agent is sleeping peacefully. Consumers can also get answers to common questions about topics like property tax valuations’ relationship to market values. (Pro tip: Agents can also take advantage of useful communication and other proptech tools.)

Prospecting and connecting with past clients get more efficient. Some examples: Re/Max’s First app analyzes an agent’s contacts to predict who might be ready to sell soon, leading to well-timed “just checking in” calls. Homesnap Pro’s Likelihood to List feature predicts which homeowners might sell in the next year.

Marketing budgets work harder when they’re data driven. AI can show who’s buying, where they “live” online, including their social media, and what digital and offline marketing channels are the best way to reach them with paid ads or organic strategies.

Trends big and small stand out. Not only can AI forecast the future for cities and neighborhoods, it can predict future property values or the best time to sell for a particular house on a particular street.

What it can’t do

For all of the amazing things AI can do in real estate, there are a few things it’s not great at.

Pocket listings don’t pop up. It doesn’t have access to private listings that agents hear about through various grapevines. (Although NAR and local Realtor boards have banned them as unfair, pocket listings seem unlikely to disappear in fiercely competitive markets.)

Chatbots aren’t all that smart – yet. They can answer basic questions or get newsletter sign ups, but “Sorry, I don’t understand” can add frustration.

Bias can be baked-in. When AI output is based on data that reflects systemic housing discrimination – such as redlining and higher mortgage interest rates for minority groups – it can perpetuate those issues. (Pro tip #2: Agents, NAR’s new Fairhaven training simulations are a great way to make sure you aren’t part of the problem.)

What only humans can do

AI’s data powers can put agents in front of the right buyers and sellers at the right time, but it will always be up to humans to close deals.

There’s no substitute for personal relationships. Chatbots can’t negotiate. A C-3PO can’t show houses. Data can’t intuit anything from the look on a client’s face when she first walks into a house. Sellers and buyers want to work with agents they trust to advise them.

Only people know the stories. Agents with hyperlocal expertise know the history of the neighborhood or maybe the story behind the local mom-and-pop grocery store that’s been there for 50 years. Storytelling skills can close deals.

What’s next

As advanced as AI is, it’s still in its infancy. The amount of data will grow. Chatbots will become smarter and answer more complex questions. Projects like the IBM Policy Lab will focus on how public policy should make sure AI helps, not hinders, the common good.

Most importantly, innovation in AI will continue to sprint ahead. If real estate pros want to stay in the game, they need to bring both Big Data and personal expertise to the table.

Apple just keeps doing stuff. And more stuff. They release new M1 chips and new iPhones and a bunch of other things. One of the newer options is their HomePod Mini, which is sure to be a big seller this holiday as companies continue to push always-on Bluetooth-enabled home speakers with promises of ease of use and improved quality of life.

It’s an easy sell for Apple, especially if you’re living in their product ecosystem of mobile devices, messaging apps, smart watches, and all the other bits of technology that can easily communicate with each other in a seamless fashion.

It’s a beautiful thing from a consumer perspective – the ability for your photos to be instantly accessible and easily shared across multiple domains and devices, to stop a podcast in your car and immediately resume it at your work desk, and knowing that your data is always backed up and retrievable.

At $99, the HomePod Mini further tightens this web of accessibility – it brings Siri access into the comfort of your home, you can pair two of them together to provide stereo sound with your AppleTV, and it can hook into your iMessages contact list to let you dictate texts quickly. While other devices can do this as well, the AppleTV carries more versatility by offering access to more streaming services than Amazon’s Fire devices (though in the world of streaming, this most likely gets evened out over time).

And all of that is great on the surface – the device is delivering on its promises and consistent use would easily justify a purchase. There is no question on utility and whether or not it is delivering and performing as desired from a consumer’s perspective. To suggest otherwise would be unfair and suggest that someone has an axe to grind – anecdotal evidence or other similarly unfounded premises stretched far and painted with broad strokes. I had an iPhone that broke years ago and in my frustration, I switched to Android. Still, that’s not much of a reason to
denigrate a new speaker from Apple. Reviews are glowing and rightfully so.

Perhaps the only true thing that should be questioned relates to user privacy. Apple has gone on record and stated on numerous occasions that they are committed to user privacy – that their devices do not record everything that is said, nor that audio data is stored forever to be mined for monetary purposes. CEO Tim Cook even stated strong convictions about privacy as a fundamental human right.

Go to their site and you’ll find a really snazzy page that tells you how your data is protected – that messages are encrypted end-to-end during transmission, identifying information is not included in the transmissions to Apple’s servers, and their Apple Pay system means you never divulge credit card information. Let’s be clear – these are excellent, wonderful things, and Apple should be applauded for doing what it has done. Such actions are at least a step above other tech giants in this realm.

Consumers should know, however, that despite these claims, Apple has been caught listening in on personal matters, and that privacy controls may not be enabled by default (and could be difficult to track down for an average user). I found a rather intense and detailed breakdown of such issues through this wonderful post by Ian Bogost, who discusses the controversy in a clear and concise (if alarming) way. The short answer – Apple gets a lot of public support and approval for its stance on privacy, but should be admonished for still providing several avenues of intrusion and for working with companies that may be actively violating privacy.

Where does that leave us with the HomePod Mini? It is a fantastic device, sure, but as with anything that is always-on and always listening, consumers may want to first consider how much utility is gained for potential privacy sacrificed. Although, the pessimist says we’re all being tracked anyway, but I want to end this on a positive note.

It is tricky to grasp the distinction between no-code and low-code. The two terms are often lumped together, but considering the disrupting influence these ideas have had in the tech world, the modern marketing professional ought to understand the difference if they want to explore this movement for themselves.

Both styles of programming are about expediting the app creation process, and enable the creation of surprisingly sophisticated code for your business without requiring any coding expertise.

Rather than focus on what these two styles are, they are more clearly distinguished by who they are for.

Jason Bloomberg of Forbes put it succinctly: “In the No-Code corner are the ‘citizen developers’ – business users who can build functional but generally limited apps without having to write a line of code. The Low-Code corner, in contrast, centers on professional developers, streamlining and simplifying their work – delivering enterprise-class applications with little or no hand-coding.”

Low-code refers to more complex tools that rely on the user having some understanding of programming to utilize. Stripe, a payment software, is an example of a low-code program, and seamlessly integrates with third party tools. Excel could even be considered low-code, considering how certain actions can be easily automated with some coding and math knowledge. But getting the most out of these programs is a challenge for programming outsiders and newcomers.

Enter no-code – much like Google Translate can help you communicate in a foreign language, the no-code movement is bridging the gap for innovators who have ideas but little to no coding experience.

As the name suggests, no-coders don’t have to learn a language in order to get started building automated processes. With tools like Zapier, creating a program relies on a simple graphic interface rather than written lines of text (which means no typing!)

That simplicity comes with tradeoffs, though. No-code expedites the process of writing more basic apps, and its offerings are fairly industry-specific.

(And just to add another layer of confusion, there are also “hybrids” like that sit somewhere in the middle between no- and low-code.)

You aren’t going to instantly turn into an expert hacker or anything, but if you want to build simple functions, like automated sequences based on incoming emails, no-code is a perfect choice.

All this to say, there are plentiful options in the codeless world for curious people of all skill levels. Yet ironically professional developers may stand to benefit the most from the no-code movement. Having these tools be widely available means potential clients are also able to explore, on their own, how their ideas translate to the app environment.

Or, as creator of MakerPad, Ben Tossell, puts it: “[No-code means that developers] won’t be wasting their time on projects that don’t work. People should have more conviction around the thing they’re trying to build before they speak to the developer.”

The potential for this technology still has yet to be fully unlocked but as it matures and becomes more well known, it’s sure to keep changing the tech game. If you’ve ever been curious about the power of code but are hesitant to spend months studying a programming language, there has never been a better time to dive in.