AI in real estate: Game-changing innovation or just a passing trend

In a Q&A with Imre-Gustav Vellamaa, Co-Founder of R8 Technologies, CIJ explores whether AI in real estate is a game-changing innovation or just a passing trend.

Is AI truly essential for the real estate industry, or is it merely a passing trend?
I believe that Artificial Intelligence (AI) is here to stay and improve our lives. More and more companies in a wide and ever-expanding range of sectors are adopting AI to achieve greater efficiency and reach new heights of success. Even the most conservative industries - Real Estate (RE) and Construction being prime examples - are accepting AI (not too fast but steadily, step-by-step).

Why?
In real it does not matter if some results are achieved by AI or something else. Just buildings with all the technical equipment installed are more and more complex. At the same time also different requirements and regulations become harder. Human nature changes also (like always throughout the centuries) - children have always different visions compared to their parents and actually this is the only way to develop. All this means that there are needed new ideas and solutions to meet all the needs.
Industrial revolution - Industry 4.0. has brought us new technologies like Data Analysis and Vizualisation, Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning (ML). These have opened us new perspectives to set and meet the new targets.
What specific areas in real estate can AI provide the most value?
It might seem even funny but the best way to have an overview about how AI can support real estate is – to ask it from AI. AI answered my question like this:
“AI offers numerous benefits that can lead to cost savings, improved services, and competitive advantages:
- Property Valuation and Investment Analysis;
- Predictive Maintenance and Facility Management;
- Tenant Experience Enhancement;
- Market Analysis and Forecasting;
- Lease Management and Optimization;
- Space Utilization and Design;
- Transaction Management;
Where to focus; what to select from this list? Sure it depends on the needs and also a readiness to implement AI.

Does AI pose a threat to jobs in the real estate industry?
According to my experience since 2017 – the answer is “No”. Even vice versa – AI supports teams to be heroes of the real estate! The main goal of AI is to increase the efficiency and open new heights that are not reachable for humans alone.

Let’s have a simple example from RE technical operations: in the building there are 10 ventilation units, 3 heating circuits, a cooling system based on chillers. Today at 14.00 outdoor temperature will increase by 2C, electricity price will drop by 15%, predicted occupancy will increase by 20%. What settings in what HVAC equipment/circuits need adjustments, what range and when? And what to do if at the same time there are some customer complaints about broken lighting or non-functioning air curtains and at 16.00 outdoor temperature will decrease 2C, electricity price will increase by 20% and occupancy is estimated to increase 20% again? What to prioritize? AI can solve the adjustments-related task in a short moment. But AI can not fix the lightning or air curtains. Thus – AI will do that AI can do the best and technical team will do that they can do the best. AI gives a chance to (re)prioritize and then - focus better on priorities.

Another important topic – a shortage of for example (high level) technical specialists in real estate companies in many countries. AI also helps to cover this gap. It can be said that AI is the first digital and the most effective member of any technical team. AI can not support in every topic but the range of AI-supported areas is growing continuously.

How can AI help in making real estate more sustainable or in achieving ESG goals?
First of all - there is a need to start from a strategy, not from a tool. ESG/sustainability strategies lead to use of ESG/sustainability technologies. What (technologies) to use to have the best results for ESG/sustainability goals? There are different solutions for that with different impact, different life cycle and different investment need. What to select? What to start from? Naturally it is worth to start from low hanging fruits but it does not mean that nothing else can not be used parallelly. Vice versa – use as much you can afford (just usually there are limits on human resources, financials etc)! AI is definitely a low hanging fruit (no huge investment need, fast results, no hard learning curves etc).

Speaking about ESG or sustainability we mostly like to speak about reducing CO2 emissions - part of E(nvironment). I think it is beacuse of the global warming topics that are parts of our everyday discussions. And also – it is possible to measure in real numbers and specially important in business – measurable in financials. For example: 200 tons of CO2 emission was avoided (with a power of AI) – clear value to anybody. How was it achieved? Energy efficiency was increased by 22%. And – this rate of energy savings was equal to 70.000.- euros. But how to present S(ocial) and G(overnance) in real numbers? Important in business – how many euros was saved or the revenue increased?

Energy efficiency is definitely one field where AI can support strongly. At the same time – it can not be just about one KPI. It is easy to save 100% of energy – just switch everything off… and all the people escape from your buildings. The more KPIs can be followed with the same solution (AI) the more beneficial it is. Coming back to energy efficiency – still indoor comfort is a priority No.1 (after safety) and for example a longer lifespan of technical equipment needs to be followed as well. Or for example – supporting to balance the electricity grid or cutting high/low electricity peaks as well.

What are the biggest challenges faced by the real estate industry when adopting AI technologies?
Adopting AI technologies do not differ from adopting any other technologies. The biggest challenges come from… a human nature. If we do not want to be supported by AI then AI can not support us. Thus it is needed to understand the reasons behind that.

Risks. Whatever new technology you are going to launch – there are always some risks. Technical, Financial, Organizational, Legal. How to avoid these risks? Once again - launching an AI is a project like any other. It needs a strong project management and involvement of all the stakeholders.

Another challenge is a technical readiness for AI. There is always a minimum technical level needed for AI. If there is no equipment then there is nothing to connect AI with.

And naturally – data availability and quality. Just one example: buildings’ occupancy have a strong role on energy consumption and its predictions. Footfall sensors – not available always. What to do? Are there knowledge to use for example Google Analytics or elevator data or CO2 sensors data? It all helps!

Are there specific examples where AI has already transformed real estate operations or decision-making?
There are many technology companies offering AI-powered services. Naturally the level of their AI or service quality is different and like with every hot topic (AI definitely is a hot topic now) – even if there is no AI at all, still some non-AI solutions are still promoted as AI.

Just let’s focus on good AI solutions here. Like mentioned before, there are very different fields where AI can support. All these different fields have many good cases around the world.

I can speak about my main experience related to AI support for a Facility Management. An example of a 60.000m2 shopping mall where the power of AI is used to offer the required indoor climate comfort with minimum costs. For that there is an AI based analyse of all the internal and external available data to find the best settings to Heating-Ventilation-Cooling systems and also – to calculate and make the needed adjustments by AI. During the last 12 months in total 150.000 adjustments were made by AI (99,8% of all the adjustments). Main results – indoor climate level was constantly over a 90% level, air quality 100% and at the same time 32% of energy was saved (37 kWh/m2)!

How do smaller real estate companies compete with larger firms when adopting AI technologies?
Big ships are always harder to change the course than smaller ones. Smaller companies have a chance to be more flexible and faster to adopt any new technologies (that do not require any investment like AI if the minimum required technological level - that is not something special - is there). Decision making process is much easier and faster in smaller companies.

At the same time in smaller companies there might be a lack of skilled people to adopt new technologies. Once again – launching AI does not differ from launching any other new technologies.
And finally – it does not depend on a size of a RE company if we speak about any building’s ROI calculations – it is ca 15 years for both.

To summarize: it depends on people, not on company sizes. There are always innovators (minority), early adopters, early majority, late majority and laggards. Based on Roger’s bell curve, the majority counts for 68% in total. Innovators + early adopters count just ca 16%.

What role does AI play in addressing the needs of tenants or buyers in the current market landscape?
The most important – AI needs to be human centric. It means that human needs and preferences must be a goal to be achieved with a power of AI. And if needed – human has a right to interact!
The only potential bottleneck here: humans are sometimes/often not able to decide what they really want. Or there are just so many different opinions in a team and no consensus is reached. But this is another big story.