The Approaching Wave

There is a wave of technological innovation approaching the shores of every business, including real estate. It is going to hit with the force of a tsunami. Consider this your warning to take up residence on higher ground. I will explain here in a moment.

This wave is an artificial intelligence (AI), deep- and machine-learning surge, and it will be fantastic to witness its crash against some of the firmly held beaches of belief about what computers can and can’t do in any industry. We have no idea how many beaches the surge is going to hit and how much impact it will have, but I can assure you of one thing: this is not a false alarm.

If you’re in the real estate industry and you’re reading this, you have a couple of choices. You can say that the tsunami sirens sound too often. Each time you’ve received the warning, the waves have fallen gently on the beach with little or no damage. If that is you, you can dismiss everything I’m about to say as the ramblings of a technophile. I won’t be offended.

Your other option is to read what I’m saying very carefully and prepare yourself. That’s what I’m suggesting. Because the only real estate agents in danger from this AI tsunami are those who choose to ignore the warning and continue to take up residence in the low ground, tied to the tasks they believe are too valuable to leave behind.

The First Swell

Sitting in a bar in Vancouver, Darin Dawson, the COO of BombBomb, began to tell me the story of “one of the best decisions” his company had recently made. It was the story of an AI assistant named after his wife. Darin and co-founder Conor McCluskey flipped a coin to see whose spouse would get the honor. Darin won. A company called Conversica (conversica.com) produced the software, and it had suggested that Darin and Conor give the AI a female name.

Darin was animated. It was as if he was talking about an invaluable new human employee. This piece of natural language email marketing and customer service software, according to Darin, was so good at engaging in natural language conversation that when people who had interacted with “her” came to visit their office, often “she” was the first “person” they wanted to meet. Think about that for a second. She is a piece of software code.

She is also tangible evidence of the first wave of functional AI technology operating in the wild, taking over a task previously handled best by humans. And just like an excellent human assistant would, her job takes away the redundant and mundane tasks that don’t require specialized skills and also frees higher-level customer service and sales staff to do what they do best.

Amelia (www.ipsoft.com/amelia) is an even more advanced piece of AI software, and she’s narrowing the gap between what software is capable of and what requires human action.

“Created by IPsoft over the past 16 years, Amelia has learned how to perform the work of call center employees. She can learn in seconds what takes us months, and she can do it in 20 languages. Because she’s able to learn, she’s able to do more over time. In one company putting her through the paces, she successfully handled one of every ten calls in the first week, and by the end of the second month, she could resolve six of ten calls. Because of this, it’s been estimated that she can put 250 million people out of a job worldwide.” That is not a typo. (medium.com/basic-income/deep-learning-is-going-to-teach-us-all-the-lesson-of-our-lives-jobs-are-for-machines-7c6442e37a49.)

The key phrase here is “able to learn.” To date, we have been limited by what we can program software to do, depending on complex commands to respond to various inputs. When an undefined input came along, the software would need to be updated to deal with the new data. These limitations do not exist with machine- and deep learning-powered algorithms. And increasingly more powerful chip technologies and sophisticated neural networks now enable real learning at a pace previously deemed improbable. It is impossible to understand the potential of artificial intelligence entirely.

DeepMind, a Google-owned British company, celebrated something unthinkable in 2016. Its AlphaGo program, an advanced system based on deep neural networks and machine learning, defeated “a professional 9-dan player of Go. Go is the ancient Chinese board game long considered impossible for computers to play at a world-class level due to the presumed level of intuition required; Go’s rules are simple, but it has more possible positions than there are atoms in the universe.” (www.theverge.com/2016/3/15/11213518/alphago-deepmind-go-match-5-result) One of the moves AlphaGo played had only a one in 10,000 chance of being successful. A less “intuitive” piece of software would have chosen a move with better odds. No human player would have made a move like that move, but the move ended up being the key turning point in the match. The victory was a monumental leap forward in AI development. (www.theverge.com/2016/3/9/11185030/google-deepmind-alphago-go-artificial-intelligence-impact)

This achievement was just the beginning. Most of the tasks we perform are not as complicated as the ancient Chinese game of Go. Most of the functions we engage in are not even close.

Real estate’s AI seeds are planted already in North America. In Canada, Stephen Jagger and his team in Vancouver have been working on a chatbot to handle inquiries from buyers as they sit in front of houses, but it is not true AI. Ylopo, based in southern California, has developed what it considers the first natural language processing bot for real estate. The basic notions of engaging in a conversation as quickly and efficiently as possible, with no human involvement, are already here.

Zillow, OpenDoor and others are engaged in a battle to use data to improve home valuation models. This battle will wage well into the next decade. You should know that the brightest minds in real estate technology scoff when they hear the real estate community claim that only a REALTOR^® can get that right.

Here’s the problem I’d like you to consider, a deep-learning algorithm already does as well as dermatologists in identifying skin cancer. And deep learning algorithms are also already better at identifying other forms of cancer. Other areas of medicine and business are seeing similar results.

If a deep-learning algorithm can do all of that, I’m reasonably confident one will be able to learn how to put a projected selling price on a house. It will even be able to advise on financial options and help suggest the best neighborhoods, all by gaining access to our private financial data and to the increasing amount of personal data we already share about our lives on social media. And the key to this wave — super-fast computer chips and all of the world’s data available online.  

And we are only at the beginning. We have yet to see the flood, but it’s coming.

The Inevitable Flood

“An analysis of the history of technology shows that technological change is exponential, contrary to the common-sense ‘intuitive linear’ view,” writes Ray Kurzweil, Google’s Chief Futurist. “So we won’t experience 100 years of progress in the 21st century — it will be more like 20,000 years of progress (at today’s rate).” (www.kurzweilai.net/the-law-of-accelerating-returns)

It is the exponential nature of its advancement that makes the coming tide of AI innovation inevitable. All previous technology advances have been linear. We have never seen technology innovation and progress like this before. And it is just one ripple of the more significant surge of technologies set to shape our future.

Stowe Boyd, working in conjunction with Traction, is attempting to create a map with Traction that will help us understand what technological advances are likely to come sooner than later. In addition to AI and machine learning, the “very important” items on the map include cybersecurity, cloud computing, data analytics, big data, and the internet of things. (medium.com/traction-report/technologies-shaping-our-future-b4779fa1f083) It’s important to note, all of these things play well together.

As more of the objects around us begin to become a part of the “internet of things” and start to communicate with each other, the power of each advancing technology will only grow stronger. The result? Both the need and the desire to give these new technologies more power will increase as well. And soon, each thing will be freed from the constraints of internet connectivity and have built-in AI capabilities. Apple’s newest iPhone uses the A13 Bionic processor, with AI neural processing built right into the phone and designed to manage everything from energy consumption to intelligent photo processing.

The High Ground

Here lies the map to the high ground. It is a treasure map of sorts; only the treasure is no myth. Here are three things I’d like you to consider today.

1. Relationships will matter more than ever

In the wake of the coming tsunami of AI-enabled programs and devices, a few pieces of software may control the intelligent automation of many tasks. It’s important to understand that certain aspects of service delivery will no longer be prone to human error and thus no longer be a point of differentiation between you and your competition. Consumers expect efficiency even now. Things like lead follow-up conversations, more intelligent CRM tools, customer service responses, notifications related to contract progress, and the very creation of the contract itself — all of these areas will certainly be taken over by AI. That truth will result in a higher premium on the quality of your relationships.

2. Reputation, honesty and trustworthiness

Every survey conducted by the National Association of REALTORS^® over the past decade indicates that the traits consumers look for in a real estate professional have not shifted as technology has advanced. The most important factor for consumers in choosing an agent was reputation, followed by honesty and trustworthiness. These are emotions uniquely tied to human relationships and will be long after the AI surge hits the shore.

3. Focus on customer experience

Yes, relationships will matter more than ever, and trust, honesty and reputation will still be the essential intangibles. To prepare yourself, look at all of the activities you engage in today. Many of these tasks either are, could be, or should be assigned to an assistant right now. These are the tasks that will be immediately impacted by AI and deep learning. They are typically repetitive tasks that, when done by you, actually distract from your ability to add your unique value to the customer experience. Move those tasks out of the way immediately.

Take the time now to pay attention to what matters most to your clients, to what value you uniquely bring in each transaction, and focus directly on those things. The high ground is waiting for you. It is available to you today. Lay the foundation immediately. Don’t wait for the impending AI tidal wave to build your home there.

Jeff Turner specializes in helping technology startups understand and navigate the complexities of the North American real estate market. He is also an internationally recognized speaker on topics at the intersection of technology trends and human behavior.

Currently, Jeff is in the midst of launching a new Real Estate Association Management platform called Tangilla, and is Entrepreneur In Residence for Second Century Ventures, leads strategy at immoviewer, and is an advisor to multiple real estate technology startups.