AI: How to develop an intelligent strategy

May 17, 2018 | | Insights

Exclusive minutes from Propteq Europe 2018 session on AI: How to develop an intelligent strategy.

Artificial Intelligence is self thinking, whereas Machine Learning is where a robot collects all information and then has integrated patterns.

Where can we see AI in our everyday life?

Attendee: This is just the beginning, people have and will continue to use this technology from around the world. Currently, 40% of companies are using AI but only 5% are using it on a regular basis. 90% of executives want to be using it over the next 5 years. There are two things from a business perspective, firstly, it will open the doors to new market opportunities which will lead to acquiring new customers, secondly, it can be much more cost effective, which leads to the common discussion of whether AI is going to make people lose their jobs. In Japan, it is quite prevalent and there are a number of few funds that invest in this type of technology.

Attendee: Most executives see AI as a growth tool. It is time saving and speeds up processes so the same amount of work can be done faster, which leads to more deals. AI also allows for better decisions to be made with the real estate industry.

Attendee: There are also AI startups such as Robot Lawyer LISA, which are solving problems with the traditional Real Estate industry.

Attendee: In real estate, there are two distinct tribes, the occupiers and the investors. In order to get the transparency that everybody needs, you need good data, information that is available and everybody accepts to be correct. A major characteristic of the real estate industry is the lack of liquidity which is the result of having poor and out of date information. The first step is to have high quality information and machine learning is an obvious way of receiving that.

Attendee: There is also a connection with Artificial Intelligence and big data but to have use case for artificial intelligence we will need massive amounts of data.

How can we collect great amounts of high quality data?

Attendee: Working in an image recognition company, what we do to get data is focus on which images the users are looking at. There can be thousands of property listings with the same features but the results vary on what the users want to see, and this depends on who they are. This is pattern-based machine learning.

How do you know you have the right, reliable data?

Attendee: This is a very important and difficult question. It all depends on what information is put into the platform. If I look at 10 houses all having similar features, I don’t know that I also want a swimming pool for example, as nobody is challenging me. If the system keeps showing me the same results, I will get bored of the repetitiveness. In order for this to really work, you have to challenge the machines and the questions they ask.

Attendee: We have to find a way to put tons of data in, execute a strategy around it, and then use pattern-based machine learning to assist. It’s simply a tool to help with decision making.

Attendee: The problem is not only collecting the data, that is only the first challenge. The next challenge is to find the right people who can understand what has been collected and can interpret that data. Chatbox machine learning: Customer experience in real estate

Attendee: Artificial intelligence is not always the best solution to ask a user if they want to rent or buy. Guided information is often more useful. It is better to ask users to fill data, and ask the right questions to get optimum data.

Attendee: Recent research has shown that businesses that had a chatbox on their website had much more success, as people prefer not to type and or call. It’s also easier as most people send a message via chatbox during their working hours.

 

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