AI can help define the best real estate investments

Facility and property managers are paying more and more attention to data collection and analysis as they can offer better services based on the extracted information. On the investor side, decision prep in the real estate market is also unthinkable without the context gained from intelligent systems.

Data-driven investment prediction

Data collection is a long-established methodology. But the emergence of cloud computing and IoT systems in recent years have already taken data analytics to a new level. Commercial real estate firms have increasing access to market data and can leverage technology to increase asset efficiency and reduce risk. Ultimately, these can also provide opportunities to optimise investment and portfolio performance, says

In commercial real estate, machine learning and artificial intelligence allow investment companies and fund managers to analyse properties in simulations based on specific criteria. They can gather information based on market conditions, operations, tenant interest and the socio-economic challenges ahead. With all this information, they can now easily determine which will be the best investments for the coming years.

The human factor

The integration of data for a more thorough mapping of trends is an advantage for a consulting company. Of course, the digitized real estate market still has a long way to go – this sector is not the main target for AI innovation – but change will be inevitable here as well. Professional companies can already create analysis models based on technologies and financial expectations, but the biggest challenge is still human nature, which can override all artificial calculations.

Challenges to overcome

There are also challenges in setting up data divisions for companies in the real estate sector. On the one hand, it is a major expense to install IT systems, and on the other hand, attracting specialists is not an easy task, as the really big players are taken by global tech multinationals, which are difficult to compete with.

In any case, the amount of venture capital flowing into the prop-tech sector is increasingly improving data platforms and adapting tools for the commercial real estate market. Ultimately, in the real estate market, firm decisions are made on whether or not to buy a property, while many variables need to be taken into account. Machines don’t make these binary decisions for humans; at most they help human intelligence with better tools to make better decisions.


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