How to think about AI in Real Estate


AI, whether we realise it or not, is impacting on all our lives in significant ways, today. From monitoring our credit card usage for fraud, to filtering our email for spam, to recommending what to watch on Netflix, to recognising our friends in photographs on Facebook, to flying our planes for 95% of the time, to enabling self driving cars. For many day to day processes it is becoming pervasive, behind the scenes. 

AI will become pervasive within real estate as well. The extraordinary new capabilities of computers to understand the world around them, to see, hear and read as well as humans, are sure to provide the foundational tools that allow us to build a better built environment.

But how do you need to think about AI in Real Estate? How do you approach a topic which can be (because it is) somewhat overwhelming?

You need to think about AI in Real Estate via a process;

  • First you need to understand what AI is good for, and just as importantly what it is not.
  • Secondly you need to analyse your workflows and business processes to see where you can leverage what AI is good at.
  • Thirdly, you need to consider which of these use cases is commonplace and repeatable within your own business and/or applicable to many of your customers.
  • Fourthly, you need to look for use cases where you have or can obtain large quantities of data, and where there are clear metrics by which you could judge success.
  • Fifthly and lastly, if you have all of the above, is that something that will create significant value?

Let us take these in turn, starting with what is AI good for?

Over the last five years AI has developed very rapidly in three key areas: Computer Vision, Voice recognition and Natural Language Processing. Taking Computer Vision as an example, in 2013 the ImageNet Competition Winner (ImageNet runs annually and quantifies the capabilities of different systems) had an error rate of 11.3%. In 2017 that had come down to 2.2%. For reference Humans rate at 5%. Similar improvements apply to NLP and Voice recognition. In practical terms these three skills have gone from ‘Useless to Utility’ and this is why we have seen the rapid rise of driverless cars (or semi autonomous ones like Teslas) and the explosive rise of Amazon’s Alexa.

A combination of improved algorithms, vast new data sets to ‘train’ on, and massive computational power has meant that much that was foretold back in the early days of AI (the term was first coined at a conference at Dartmouth College in 1956) is now possible. And critically, because of the way AI works (essentially recursively - the more you know, the more you can know and the faster you go the faster you’ll be able to go) over the last five years in particular the pace of development has actually got faster. 

Which means that, today, AI is very good at:

  • Understanding what is happening in pictures and videos
  • Understanding people using language
  • Creating content (auto generated commentary, extracting data from reports, news etc)
  • Automating processes
  • Optimising complex systems
  • Making predictions

Essentially, anything that is ‘Structured, Repeatable or Predictable’ can (and most probably will) be automated.

Think of all of this as pattern recognition and you’ll get to grips with what is possible. 

In terms of what AI cannot do, the key point to understand is that computers operate within very specific boundaries. Google’s Alpha Go, that beat grandmaster Lee Seedol at the famously complex and complicated Chinese board game Go, would be completely useless if you used it to play chess.

It is true that Machine and Deep Learning, both of which are subsets of AI, and are differentiated by being systems that are not explicitly programmed to do A then B then C or D if X = Y, can to an extent ‘think for themselves’, but they can only do this within very narrow boundaries.

Computers are great at optimising complex systems because that plays entirely to their strengths but ask a computer to create something completely new that turns out to be complex and it will fail.

Even in an ‘AI first’ world, as Google boss Sundar Pichai said we were entering last year, a human ‘augmented’ by a computer will trump any computer on its own. By the same token a human/computer pairing will also trump a human on their own.

To make the most of AI you need to think in terms of what computers are good at and what human skills can be used to leverage those capabilities. 

We need each other, to be the best we can be, at what we are good at.

Once your thinking is clear about what AI is good at you need to look for use cases. What tasks do you or your company perform that are ‘Structured, Repeatable or Predictable’? Last year the RICS released a report saying that 88% of the tasks surveyors perform are vulnerable to being automated within 10 years. In 2016 McKinsey said that 49% of ALL tasks people are paid to perform globally are capable of being automated by ‘currently demonstrable technology’. So the answer is probably ‘quite a few’.

So list them out; What do you do that follows a pattern in some way? Either because they absolutely do involve linear processes, or because with these inputs you know you can produce those outputs. You’ll find workflows or processes from across the entire lifecycle of real estate, from planning, to design, construction, leasing, occupation and management and on to portfolio analysis and investment sales or acquisition.

What imagery or video content do you deal with, or what movements around space would be useful to track? What customers do you interact with and how much do you know about them? What reports do you have to generate and how are they put together; could these be automated? How do you handle questions from customers; do these follow a pattern? Etc, etc….

Once prepared you can move to the third stage. Take your list and give each item two scores of 1 to 10. First how common is this task in your business, and secondly how common is it outside of your business, either amongst customers or competitors. You are looking for tasks that are repeated over and over again. What are the primary ‘Jobs to be Done’ in your area of real estate? This is a proxy for market size in terms of the potential AI service that addresses each task. We’re looking to use AI to help us do tasks much faster than now, or much cheaper, or more accurately so it is sensible to look for those tasks we, or our customers, have to do a lot of.

Now we need to look at data. How much of it about each task do we have? Here you should think of the four V’s: Volume, Variety, Velocity and Veracity. How much data do we have, from how many different sources, how fast is it being generated (as per seconds, hours, days, months, years) and how accurate is it? Regarding accuracy you must be honest; we all know a lot of real estate data is, being polite, somewhat lacking in rigour. If utilised by AI inaccurate training data will lead to inaccurate results, and it is frankly better not to waste your time with it.

It is not an absolute that more data makes for better AI but in many cases, a lot of solid, accurate data is a great benefit. Also, knowing what you have and what you lack is very useful. You might be able to acquire what you need from third parties but without a good data audit you won’t know where to start. Thinking about AI involves a lot of thinking about data.

You need to think about correlation not being causation and apply that to your data. You need to think in terms of ‘with these data points I could arrive at this conclusion’. For example, if I knew exactly how occupiers of my building moved around, I could optimise the AC and lighting. Or, if I knew these characteristics of an investment I could match them against these characteristics of an investor.

Think big here. Hypothesise about being able to do something that you cannot do today. What data would I need to make that happen? Work on the assumption that if you had said data we now have the tools to analyse it deeply. ‘How could I filter out from thousands or tens of thousands of companies which ones will lease my new office development?’ 

And moving to the fifth stage, ‘where’s the money’? From all that we have looked at which areas, with what solutions, could generate the most value? This might mean saving money, or time, or it might mean creating a much larger market or more valuable products or services. Value comes in many forms.

It will sometimes be the case that ‘digitising the past’, where you simply apply new technology to existing business processes, makes sense and is worthwhile, but the real value in this field, applying AI, will be in creating products or services that did not exist before. There is little competitive advantage in doing what everyone else can do, so your thinking needs to be focussed on the mountain top beyond the horizon.

By this stage you should be a long way towards that goal.

In conclusion then, thinking about AI in Real Estate involves understanding the new technologies, looking for use cases, determining what use cases are core and ongoing or transitory, getting to grips with data, what you need and whether you have it or can get it, and then homing in on where real value lies.

There is not a shortcut through this process, though it’ll probably turn out to be not as daunting as you might imagine. Once you have a structured way to think about this new world things do tend to fall into place quicker than you imagine. Utilising AI is as much a mindset as a technology.

At all times though what must remain uppermost in your thinking is that whoever really cracks using AI in real estate will be orders of magnitude more productive, and profitable, than the non AI embracing mainstream. AI is potentially truly disruptive.

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PS. PropAI has launched today:

"PropAI are delighted to be partnering with the Oxford Foundation for Theoretical Neuroscience and Artificial Intelligence (OFTNAI). 

PropAI believe that artificial intelligence has the potential to redefine the operations of the commercial real estate industry. From how buildings are designed, to how they are built, occupied, managed and traded, AI will become part of the everyday lives of all of us.

We are looking to understand how the very latest technologies, with hitherto unseen capabilities, can be utilised to augment human skills and enable the industry to be 10X more efficient, effective and impactful."

In Commercial Real Estate? Forget Blockchain and Bitcoin, AI is where you should be focussing

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The great Dotcom Bubble peaked in March 2000. Over the next 18 months trillions of dollars of investment capital evaporated. The Great Bitcoin/Blockchain bubble feels very much like it did in 1998-99. One cannot move without being accosted by someone screaming that you just have to get on board today. Of course such bubbles are tenacious things, and just as the smartest man ever, Sir Isaac Newton, eventually could not resist going all in with the South Sea Bubble (only to lose most of his money) today I am seeing very many smart people bowing down before the call of crypto.

If you are one of them you most likely will lose your money as well. Not because you are wrong per se, but just as in the Dotcom Bubble, you are probably a decade too early. Most of the ‘crazy’ ideas that raised hundreds of millions of dollars in the 90’s blew up not because they were bad ideas but because the technology did not exist to enable them to actually happen. There were very many 1990’s simulacrums of Netflix for example.

Blockchains will have huge utility, as will crypto currencies (the two by the way HAVE to go together - a Blockchain without a cryptocurrency IS NOT a Blockchain) but not for a while. There are real technical hurdles to cross before this happens. So my advice is to put no more than 5% of your wealth into the crypto market and forget about it. If you are lucky and invest in the winner you will do extremely well. But there will be many losers and no, you are not bright enough to know which will be which. No one is.

Put your real effort, and money, into AI, Artificial Intelligence, because this is an area whose time has come. A term first mentioned in 1956 at a conference at Dartmouth College, AI has already gone through two prolonged ‘Winters’ but over the last few years has advanced in leaps and bounds as a combination of improved algorithms, massive computing power and unprecedented access to vast quantities of data has enabled theory to move into practice. 

Sundar Pichai, CEO of Google sums up the current situation perfectly: “We are now witnessing a new shift in computing: the move from a mobile-first to an AI-first world”

Artificial Intelligence has had a storming half decade. In just five years it has gone from the world of science fiction to mainstream discourse. Autonomous vehicles, robots that can perform backflips, computers that now rule the roost at Poker and GO as well as the long since vanquished Chess; all around us we read of one new breakthrough after another. According to Gartner’s famed Hype Cycle, Machine Learning (a subset of AI) is now at ‘peak hype’, meaning that we can expect widespread adoption to be just 2-5 years away.

In three key areas AI has enabled computers to rapidly go from ‘Useless to Utility’. Computer Vision (face and image recognition), Voice recognition and NLP (natural language processing) have all moved from being 20-30 percent error prone a few years ago to now being on a par, or even surpassing in certain circumstances, human ability.

In effect computers can now see, hear and read as well as we can.

And in the commercial real estate industry that really matters. The ability to understand the build environment by pointing a camera at it, to read the voluminous quantities of paperwork that weaves its way around the industry, and to be able to interact with our customers (everyone who enters into any of our spaces and places) just by listening to what they have to say, is truly a transformational power we now have at our disposal.

For example, what if we could enable customers to search for space visually, by choosing images that appeal to them, instead of making them fill in forms and describe what it is they are after? Or understand the ‘mood’ of visitors to our shopping centres, or find potential new development sites by analysing drone footage? Or understand exactly how people are using our offices, or shops, the better to configure them for reality as opposed to hunch?

What if we could analyse all correspondence that goes out of or into our businesses in real time, to look for patterns, insights and ‘unknown unknowns’. Or prioritise work orders, deal flows, job applications automatically and route them appropriately. Or have reports collated, processed and presented in realtime that we can then spend time analysing rather than labouring over.

What if we could support our customers better by asking them to just talk to us? 24 hours a day, 7 days a week, 365 days a year we should be able to answer the needs of our customers in a way that suits them. We should be able to talk to our buildings, and have them understand us; it’s too hot, or cold, or bright or dark, or stuffy. Where is X, or who is Y? Just walk around the City and see how many people are talking into the ether, plugged in as they are to the microphone and headphones; Voice is the new computing interface. 

In an AI powered world the commercial real estate industry will be able to do three things, of huge importance, that it cannot do today:

First, we will be able to understand exactly how our buildings are working, at a very granular level, and in so doing we will be able to run them far more efficiently and effectively.

Secondly we will be able to understand exactly how everyone who uses our buildings, spaces and places really does use them. Where do they go, what do they use, when do they use it; all this will enable us to define, refine and curate the UX, the user experience, of all our customers in a way we simply cannot do now. This will be a true #SpaceAsAService world where we will be able to provide exactly the spaces and services that people need, wherever and whenever they need them.

And thirdly, we will be able to understand exactly who our customers are, what they need, desire and are pleased by in a way we’ve not been able to to date. 

As we understand how our buildings operate, how they are used, and the needs and requirements of those who use them better, we will be able to build a better built environment for them. Today, research tells us that roughly 50% of office occupiers do not find their offices help them be productive, and roughly 50% of the time these spaces are not in use anyway. With wise use of Artificial intelligence, coupled with the very best human skills we should be able to do much better than this. 

So forget about Blockchain and Bitcoin for now; concentrate on learning how AI can, and will, radically and rapidly transform what it means to be in the real estate industry.

In brief: How #PropTech will change in 2018 compared to 2017

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During 2017 the real estate industry became increasingly involved with ‘PropTech’; in 2018 it will become committed. The difference being that in 2017 many people learnt the vocabulary of PropTech and became good at saying all the right things, whilst actually doing very little about putting any of it into practice. 

In 2018, the innovators will start to steal a very considerable march on the laggards by rethinking their business models, investing in technology and digitally enabling their employees. They will grasp that, yes, they (like every other business) are in the technology business, and that the real estate industry is no longer about real estate. Real estate is moving inexorably from being a product to a service industry. And that changes everything.

The most successful real estate companies will develop three areas of their business in particular, largely with the aid of technology, but also in combination with enhanced human skills and capabilities:

First they will understand exactly how their properties are operating, at a very granular level, and in real time. Through sensors and the IoT they will enable their properties to ‘talk’ and in doing so will enable them to be run much more efficiently and effectively.

Secondly they will understand, again with the help of technology, how people are really using the spaces and places around them, as opposed to guessing and working on hunches. This will enable them to configure their properties for maximum utility and thus raise occupancy and occupier satisfaction levels.

And thirdly, they will learn exactly who is occupying their properties. As opposed to only knowing the person who pays the rent very well, they will begin to treat every single person who enters their property as a customer. In an increasingly #SpaceAsAService industry, providing a great UX, user experience, is what will define an owners Brand, and it is through a great Brand that the greatest Value will be created. To build a great UX though you need to truly understand your customer.

All of this will be hard, and a challenge for the real estate industry. But the companies that are committed to making it happen will be handsomely rewarded. The gap between the best and the rest is set to grow.

So.. did my dreams come true?


In December last year I wrote a post entitled ‘#PropTech resolutions for 2017’. With the year almost over I thought I’d revisit it to see if my dreams came true:)

So here we go:

1. Stop talking of #PropTech; technology is not a bolt on to ‘Property’. If you are in business, you are in the technology business.

I’d say I lost the battle but won the war here. #PropTech has never been talked about so much as it has been over the last year, and my preferences aside, the term has proved very useful in marketing terms and as a tent peg off which a whole host of ideas and conversations have hung. Against that I think we are ending the year as an industry that has realised that talk of #PropTech does mean that many still place the ‘Tech’ bit in a silo and that much work is still required to emphasise the ‘If you are in business, you are in the technology business’ bit.

2. Don’t know much about technology? Get someone in to brief you. Keeping up with tech is not your job, but it is your job to exploit what is possible. Find out.

A score draw? Perhaps, but perhaps a narrow defeat. I’ve not stopped talking tech to people in the industry, and the number of people looking to ‘find out’ has grown dramatically, but I feel there is still a lot of lip service paid to technology, with not nearly enough follow through. Real Estate is still largely an analogue industry.

3. After doing No 2 you will know that near as damn it, you should be able to run your business from a phone or tablet (Marc Benioff of Salesforce tries to).

Total #Fail here: Running a real estate business by pdf is more likely than from a tablet:)

4. With No 3 sorted, feel free to laugh at competitors not fully mobile enabled. They will not be competitors for long.

The #Fail gets bigger: until a fully digital real estate company emerges no one will be laughing at those left behind….

5. ‘I will format any reports we write for mobile.’ What is it about the Real Estate industry that makes them upload print formatted documents, that are unreadable on a phone? Look around you; what are people looking at? Yes, their phone!

And again, no dreams coming true here. In fact only yesterday I heard of how shockingly inefficient much of the investment sector still is, with presentations being manually put together by inserting data stored in pdfs! 

6. Double your hardware budget. Getting your workplace ‘right’ is important but equipping your team with the best possible technology is way more so. A company with great tech could succeed in a terrible office, whereas a great office is useless without great tech.

Well… did you?

7. Sort your office out. The Stoddart Review at the end of 2016 showed only 53% of employees believe their office helps them be productive. An unproductive office is like leaving piles of cash on the table after concluding a deal. Low hanging fruit; pick it.

Low hanging fruit still hanging there, waiting to be plucked. Although with a valuation ending the year at over $20 billion it could be said that WeWork has been harvesting like mad.

8. Less is more is the perfect Life/Work balance mantra. Eat less but better. Drink less but better. Take less office space but make it better. Work less but better. And use technology to enable all of this.

A Win at last. Certainly in London at least there is much evidence that larger occupiers are downsizing their requirements 20-30% when given the opportunity by a lease break or end. This trend can only grow - Per head we all need a lot less space, at least in terms of long leasehold space.

9. Then do More, with More. Technology gives us all leverage. More (of the right) technology will allow everyone to do more with more. If you can do X in an analogue world, you need to be looking to do X times 10 in a digital one. Countless examples of this exist. It is not fantasy.

Another #Fail - Real Estate has not even started in doing more, with more. Combined Google, Apple, Facebook and Amazon have a market capitalisation equivalent to the GDP of India yet they only employ around 700,000 people, and Amazon warehouse workers form even the bulk of that. That is productivity. 

10. Buy software that makes you more efficient – BUILD software that gives you a competitive edge.

I am going to claim a Win here. Many people have argued this with me this year, saying real estate companies are not up to developing software and should always buy it in. But they are wrong, especially when it comes to the large companies. I’ve not seen any competitive advantage accruing to companies that buy in their software. And you won’t: you will see much consumer surplus generated but little competitive advantage. For that you need to Innovate!

11. Try and get rid of your IT Department. Technology needs to permeate your business, not be the butt of jokes and hidden away in the worst space in your office. Amazon does not have an IT Department; neither should you.

Think I’ve won the argument but currently a #fail - the smarter set realise they need multi functional teams with pervasive tech skills throughout their organisations but I’ve yet to see this executed on. Next year…..

12. Prepare to hear everyone tell you how their software uses AI and Machine Learning to ‘insert hyperbolic phrase here’! Mostly, they will be clueless as to what that means.

An outstanding Win: 100% correct on both counts.

13. BUT AI and Machine Learning ARE the most important technologies out there and WILL change your world. My No 1 resolution would be to learn why and how.

And another Win: next year this really will be BIG. 

14. Start by hiring Amy, an AI Digital assistant (, to organise all your meetings.

A Win, though more for Alexa than Amy. 2017 was the year the idea of talking to your computer went mainstream. Kudos to Amazon.

15. Technology is changing the world to being ‘on-demand’, and our industry is not immune. In fact, ‘The Real Estate Industry is no longer about Real Estate’. Make 2017 the year you think about the Service you provide, rather than the Product you sell.

Biggest Win of the year: #SpaceAsAService is now ‘a thing’ - big and getting bigger. This is the juggernaut coming to change real estate. Follow my ‘twin’ @spaceasaservice to keep up with everything going on in this area.

16. Finally, realise that whilst you probably aren’t that knowledgeable about tech, most #PropTech people know very little about Real Estate. The two sides need to converge. Let’s kill off #PropTech by 2018.

Let’s just roll this one forward. Tech meet real estate, real estate meet tech: you need each other:)

Overall then, did my dreams come true? Of course not, but then dreams aren't supposed to, are they?