Karen Burns is the Co-founder and CEO of Fyma where they help build better places with data. Fyma partners with commercial real estate developers and asset managers to help them make sense of their built space: from footfall to all kinds of transport, accessibility and dwell time analytics. Ms Burns has more than 17 years of prior experience in ICT and Business Development roles, is a regular speaker on AI, management and business development topics and an advocate for getting more women into STEM.

In her presentation, “How AI is Disrupting Commercial Real Estate” Karen focused on the changes AI has brought to the field of commercial real estate and brought examples of how some technical solutions have already been used. She started with stating that this is the largest asset class in the world, which has always taken slowly to changes but is, now, finally starting to embrace the opportunities that computerisation and AI systems are offering. The presenter argues that in this case, AI should be seen as an asset, an opportunity, not as a threat.

To begin with the examples, Ms Burns explained that, in the planning and development field, machine learning has been used for traffic pattern simulations, but it has to go hand-in-hand with human beings, because poor data inserted will provide poor results. A next field in the value chain where AI is being used is construction. There, the help of AI is mostly used for occupational health and safety purposes, to help the management monitor the wellbeing of workers on sites; data being retrieved from different cameras and sensors.

Going forward, in asset or property management, the presenter states, different smart building / office solutions have been in use and development for quite a while. These solutions would provide info about a single object, a building; the energy consumption, HVAC, waste management and their optimisation. In the demolition and recycling field, both robotics and computer vision are used to sort waste.

To come back to the planning sector, urban planning is one of the areas where AI could provide much help in better analytics and investment decisions, however this is very dependent on the quality of the data provided. As of now urban planning is a very emotional field, were gut feelings war against data. Urban planning is also affected by the large trends going on around us, like gig economy, reduction in location-specific jobs, etc. This sector has a lot of potential to benefit from AI once the reliance moves away from gut feeling towards data.

The next question presented by the speaker was what ties these components of the value chain together. She responded that it’s the fact that data usage is still very much in its infancy in all these areas. They generate great amounts of data, but it’s not properly use. Ms Burns also stopped briefly on ChatGPT and stated that it could provide rather good output on, for example, briefs to an interior designer, when given a good prompt.

Moving onward, the presenter introduced her company, Fyma. Fyma applies digital sensors to cameras that are already there and collects data in that manner. For example, Fyma is used to map the usage of car parks to help reduce wayfinding - therefore lessen the CO₂ emissions - and to simplify finding a parking space. The benefits from systems like this are, e.g., real time overviews, CAPEX reduction, and more data for planning purposes. Fyma has also carried out similar projects in other cities.

To exemplify, the speaker compiled the benefit points of such projects. Regarding large areas in cities, there will be more data to better plan the locations of bike lanes, pedestrian ways. It gives insight on how to reduce the number of vehicles on the streets and increase pedestrian traffic. When focusing on a single building, using cameras and sensors will allow the companies to provide info to their tenants. For example, when to go down, when the waiting time for elevators is too long, etc., to pace and space out people across the entire day.

To close the presentation, Ms Burns named ChatGPT, DALL-E, specific applications for architects and builders… as the largest disruptors of the commercial real-estate field. And she also noted what is lacking the most: a knowledge base, education related to that knowledge base, people to connect AI and the data there is, and most of all – imagination.

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