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HOW TO THINK – Continued from page 21

it being generated (as per seconds, hours, days, months, There is not a shortcut through this process, though it’ll
years) and how accurate is it? Regarding accuracy you probably turn out to be not as daunting as you might imag-
must be honest; we all know a lot of real estate data is, ine. Once you have a structured way to think about this new
being polite, somewhat lacking in rigor. If utilized by AI, world, things do tend to fall into place more quickly than you
inaccurate training data will lead to inaccurate results, and imagine. Utilizing AI is as much a mindset as a technology.
it is frankly better not to waste your time with it.
At all times though, what must remain uppermost in your
It is not an absolute that more data makes for better AI but thinking is that whoever really cracks using AI in real estate
in many cases, a lot of solid, accurate data is a great benefit. will be orders of magnitude more productive, and profit-
Also, knowing what you have and what you lack is very useful. able, than the non AI embracing mainstream. AI is poten-
You might be able to acquire what you need from third parties tially truly disruptive.
but without a good data audit you won’t know where to start.
Thinking about AI involves a lot of thinking about data. Antony Slumbers has over 20 years’ experience
developing and running online technology
You need to think about correlation not being causation companies, primarily within the commercial office
and apply that to your data. You need to think in terms of and property management sectors. He has
‘with these data points I could arrive at this conclusion’. recently co-founded PropAI (www.propai.co.uk), a
For example, if I knew exactly how occupiers of my build- company dedicated to the advancement of AI in the real estate
ing moved around, I could optimize the AC and lighting. industry in partnership with OFTNAI, the Oxford Foundation for
Or, if I knew these characteristics of an investment, I could Theoretical Neuroscience and Artificial Intelligence, headed by
match them against these characteristics of an investor. Oxford University’s Dr. Simon Stringer. He blogs regularly at
antonyslumbers.com.
Think big here. Hypothesize 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 analyze it deeply. ‘How could I Y O U R T RU S T E D D I GITA L
filter out from thousands or tens of thousands of companies T RAN S F O RM AT I O N P A RTN ER
which ones will lease my new office development?’

And moving to the fifth stage, ‘where’s the money’? From Automate and digitize your real estate and property
all that we have looked at which areas, with what solu- management processes with purpose-built, next
tions, could generate the most value? This might mean generation solutions that leverage the powerful
saving money, or time, or it might mean creating a much capabilities of the Microsoft technology platform
larger market or more valuable products or services. Value
comes in many forms.

It will sometimes be the case that ‘digitizing the past’, where
you simply apply new technology to existing business pro-
cesses, 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 focused on the mountaintop beyond the horizon.

By this stage you should be a long way towards that goal. DEAL PRO CESSI NG FEE B I LLI NG S M ART B U IL DING S
FACI LI TY MANAGEMENT UTI LI TY M ANAG E M E NT
In conclusion then, thinking about AI in Real Estate
involves understanding the new technologies; looking for WO RKO RDER STREAMLI NE ADVANCE D CONT RACT S
use cases and determining what use cases are core and
ongoing or transitory; getting to grips with data, what you +1.425.578.1918
need and whether you have it or can get it; and then hom- www.domain6inc.com
ing in on where real value lies.

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