For centuries, the distribution of roles was clear: humans are the brains, machines are the muscles. But the relationship between machine and man is about to change forever. We are at the dawn of understanding Artificial Intelligence (AI). All over the world, humans are experimenting with AI and are developing ideas, which will be changing every area of our lives: mobility, medicine, finance, but also real estate and construction. Think about building your house. Nowadays, you hire an architect, a structural engineer, and a construction company. In the very near future, your architect and structural engineer will be artificial intelligence.

To understand how building a house in the future, with the help of artificial intelligence might look like, let’s call the AI Otto and let’s imagine the kind of conversation we would have with him:

YOU: Hello, Otto, I want to build a house.

OTTO: Hello! Let’s get started. Here are some popular types of houses. Please select a few examples to give me an idea of what kind of house you would like.

YOU: Ok, Otto, I selected a few styles.

OTTO: Thank you. Now tell me how many bedrooms you would like to have?

YOU: Four.

OTTO: Now tell me, the number of inhabitants and the age of each inhabitant.

YOU: We will be four: My husband (43), myself (37), my daughter Sophie (7), and my son Paul (5).

OTTO: Ensuite Bathrooms for all bedrooms: Yes or no?

YOU: yes

And so on and so on.

Not much different than the communication you would be having with an architect if you were to build a house, right?! It is vital to realise that you interact with AI in the same way you would with a human.

“Artificial intelligence is a technology that solves problems by imitating human thought.” Derek Thompson in Crazy/ Genius.

Artificial intelligence can be a simple list of rules, called an algorithm. If this, then that: If I am in Brussels, my phone will show me the weather in Brussels. But artificial intelligence can also be a very complex system. If you ask Amazon’s Alexa: “What is the capital of Belgium?” The computer has to hear, process, and speak in response. So how does that work? How do you teach a machine?

You are probably all familiar with Autocad, a mainstream computer program for designing CAD drawings, developed by Autodesk. But did you know that Autodesk is also at the forefront of machine learning? Especially in regards to architecture and AI. The company developed software, which is using generative design to plan buildings. Recently Autodesk produced the world’s first ample office space designed by artificial intelligence.

Many of you might wonder what exactly it means: “Designed by artificial intelligence?” Were there no humans involved? How does AI knows what humans want? What did the process look like?

Autodesk started with simply questioning the employees for whom they were designing the office: What kind of light do you need to work? Whom do you want to sit next to? Which areas do you want to be close to? What does a productive office look like to you?

The answers formed the base for quantifiable input and were then fed to artificial intelligence. The machine generated over 10.000 different possibilities on what this office could look like. The AI was brainstorming the blueprints by itself (Blueprints are a sort of technical drawing containing all of the information needed to build a building).

In a second step, architects at Autodesk picked through those brainstorms and combined their favourite details to produce the world’s first ample office space designed by artificial intelligence.

That is just one example of what AI can bring to architecture and real estate. But it shows the enormous potential artificial intelligence has, especially when it comes to simulating.

Artificial intelligence is a simulator on steroids, which can be used to design houses, offices, roads, quarters, yes… even entire cities.

And it doesn’t stop here. The ability of artificial intelligence to learn from a vast inflow of data will increase the efficiency of real estate agents, will help brokers and investors to act even more strategic and will make the buying and selling process more manageable and more transparent for buyers and sellers alike.

Let’s take a look at what artificial intelligence can do for each segment of the real estate and construction sector:


  • Predict appraisals and market values of a property in a target market by combining CRM and marketplace data

DEEPBLOCKS: Deepblocks’ technology combines proprietary algorithms and artificial intelligence techniques to optimise the process of real estate development from a financial perspective. The software performs a complete real-time analysis of financial and market data, in combination with local building regulations, to generate a set of optimal strategies for any real estate development project. As we compile a rich real estate database from cities around the world, the use of machine learning will provide unprecedented insights that will enable cities and developers to optimise decisions about where to build, what to build, and when to build.

Olivia Ramos, the founder of Deepblocks, graduated of Singularity University, and a participant in the DARPA Innovation House will be a speaker at the ProptTech summit EVOLVE19 hosted by Prompto and Barco on December the 4th 2019 in Belgium.

QUANTARIUM: The Seattle based company developed the Quantarium Valuation Model software for evaluating property value. It uses machine learning to run hundreds of thousands of generations of property specifics and values to understand and optimise information on micro-markets at the neighbourhood, ZIP code or county level. Providing mortgage lenders, financial institutes, housebuilders, direct marketing agencies, and real estate professionals with detailed property insights.

Plan and Build

  • Use of generative design to design buildings. Generative design is a new process using artificial intelligence and cloud services to enable engineers and architects to create a huge amount of design options. The options are based on basic parameters such as height, weight it must support, strength, and material options, with which the artificial intelligence has been fed.
  • Remote operation of construction machinery: Meaning that humans don’t have to be next to the machine anymore in order to operate it. The machinery can be operated for instance from 1000 kilometers away or from overground if the machine is underground.
  • Prevent cost overage by predicting cost and potential overruns throughout the planning and construction phase based on factors such as project size, contract type, and the competence level of project managers.
  • Recognise late and over-budget construction projects in time by capturing 3D scans of construction sites and feeding the data to AI, which detects anomalies and sets off an alarm.
  • Risk mitigation through monitoring and prioritizing: construction projects are highly risky in regards to the safety of the workers, time and costs spend on the projects as well as the quality of material and lately the final result. AI can help for example by rating subcontractors based on a risk score. So that construction managers can keep an extra eye on them or enforce their team.
  • Use of self-driving construction machinery to perform repetitive tasks.
  • Analysis of photos from construction sites. Scanning them for safety hazards and setting off an alarm in case of dangerous behavior.

KWANT: Kwant uses artificial intelligence and predictive analytics to predict duration, delays and cost overages in projects based on historical data of a company before and throughout construction.

NUCON: Nucon is an AI engine that automates expert analysis of inspection reports, at scale to enable construction companies learn from their mistakes during and before construction. If you build for example a multi-story building, mistakes on the first floors provide insight, so that they won’t be repeated on the next floors.


  • Improve the home search for clients by generating property recommendations tailored to each client’s taste. Therefore guaranteeing fewer, but higher-quality property search results.
  • Identify strong client leads for agents by pre-selecting potential buyers and by allowing agents to connect with clients in a more personal, meaningful way. Take a look at Prompto for example, where artificial intelligence can help decorating apartments automatically that matches the clients taste and style.
  • Refine the transaction process by providing faster closing times, robust compliance checks, and auto-fillable data that cuts down on manual data entry and errors saving real estate agents time and money.
  • Increase efficiency and reduce costs in real estate operations and transactions. Houses can, for example, be shown by artificial intelligence-powered robots, who know all the relevant information regarding a house and can be asked questions. Another example is in transactions, which can be done with the help of artificial intelligence minimising the manual input and reducing mistakes.

TRACKUITY: Trackuity provides data-driven discovery for online marketplaces and real estate websites. Saying, that once a visitor has shown interest in a property, smart algorithms get a first idea of what the user might be looking for exactly. Then, the customer is prompted with relevant properties, which leads to further user interaction that the algorithms can then use to make even better suggestions. The technology surfaces the properties of interest automatically, allowing visitors to easily discover them without having to do tedious manual searching.

LOCALIZE.CITY: allows anyone to search for any address in New York City and receive an easy-to-understand view of what it’s like to live there today and learn about future changes. Localize is powered by an Insight Engine: AI that analyses thousands of complex data-sets in real-time.

Manage and Operate

  • Leverage data to improve occupant experience, increase operational efficiency, and optimise space and asset use.

WATSON by IBM: The Watson IoT platform helps to improve energy efficiency in buildings and make them personalised/user-friendly using data analytics. The platform collects data from devices and sensors embedded in doors, windows, etc. It analyses the data and learns the most optimised and user-friendly working conditions. Its knowledge is then passed on to the facility manager, who can react accordingly.

THE EDGE in Amsterdam: The Edge is considered to be one of the most advanced and greenest buildings in the world. 30,000 sensors embedded in the building collect data about the building’s operations and how occupants interact with it. The data is used to constantly improve the working environment.

source: The Edge

Smart City & Live

  • Use of voice-activated home systems that self-set alarms and thermostats.
  • Use of generative design for roads, quarters, and cities.

JOSH: Josh is a voice-controlled home automation system. Like Siri or Google Now, the Josh programming language is built to support natural language voice commands. This includes greetings, questions, instructions, and more. Further, Josh is built to control and connect any “smart” device, from any device. For example, with Josh you can turn on your speakers from your watch, change the temperature from your phone, shut off the lights from your desktop, etc.

LEXSET: LexSet is working on a platform where people can quickly find and select items they want and see how they look in their actual home. The technology is based on artificial intelligence.

Work with instead of against artificial intelligence.

There is no question that AI will radically change all aspects of our lives in the coming years. Progress is unstoppable. If you want to remain relevant and successful, you must jump on the bandwagon now because early adopters will have a market advantage. As machine learning is one of the main components of artificial intelligence, the key for construction and real estate companies alike, therefore, is banking as much data as possible when it comes to buying behavior, customer behavior, risk and costs monitoring, etc.

Read more about how new technologies are shaping the real estate sector and how growth hacking can be used to lead your company to success on our blog Prompto and follow us on LinkedIn and Facebook.

All the best,

Karolin on behalf of the entire Prompto-team.