AI is a chance to shift how things are done in real estate.
Data in commercial real estate (CRE) is riddled with recurrent, and often avoidable, errors. Various technological innovations are being introduced in an effort to address these issues.
According to JLL’s 2023 Global Real Estate Technology Survey, over 80% of real estate occupiers, investors, and developers are planning on increasing their real estate technology budget over the next three years.[1] But, these solutions run the risk of simply masking and entrenching the problems, rather than solving them.
Digitisation signals a new wave of optimism for the industry, but just digitising traditional practices is not a solution in itself to the challenges real estate faces. The worst mistake the CRE industry could make is falling under the false pretence that the industry is working fine, and all we have to do is ‘digitise’ it.
It is imperative to scrutinise the nature of the problems tech solutions are fixing, as well as the Artificial Intelligence (AI) applications in real estate themselves. Understanding the pitfalls of CRE, and how AI can help us progress beyond them, is imperative to developing proptech solutions that actually improve CRE.
CRE’s foundational flaw: dirty data.
Within real estate, there has been an overreliance on outdated, and often unclean, data.
Currently, data circulated to enact liquidity processes and instigate informed decision-making includes historical data, which is often littered with errors, tricky to access, and duplicated across data fields. Relying on this information, particularly for situations such as property and portfolio valuation, leads to costly inaccuracies.
With an influx of digitisation, algorithms and machine learning have been used to increase the speed of these analyses. The problem? If the information is flawed to begin with, predictive models and algorithms will only serve to perpetuate those inaccuracies. Although the answers will be delivered more efficiently, the same errors will be carried over.
Addressing these challenges upfront and unlocking the genuinely transformative potential of AI in real estate practices is pivotal to creating long-term industry improvement.
A complex alternative, not a simple solution.
Key issues in commercial real estate, such as data fragmentation and illiquidity, are so prevalent because the real estate industry lags when adopting innovative trends. Manual practices are deeply ingrained, so pain points have become increasingly sore, no longer an itch, but of genuine concern and in need of immediate attention.
Digitising past processes won’t fix these. Instead, asset managers need complex solutions that redefine processes.
Avoiding data silos
Data in itself is not a solution. Many asset managers have access to significant data storage, as buildings produce copious amounts of information. This data is not as valuable when viewed in a vacuum, it must be stored in a way that allows for cross-checking against historical and current data points.
Digitising this information through legacy platforms does not create instantaneous value for asset managers. Instead, utilising systems such as Stonal’s data lake allows asset managers access to a centralised storage of information. Allowing real estate asset managers to transform raw data into structured data through analytics, supported by AI.
With AI systems rapidly advancing and improving, when implementing systems that rely on proprietary software, asset managers run the risk of simply recreating the same mistakes – just in digital format. Adopting a solution like a data lake allows flexible information, meaning AI systems are able to operate seamlessly within it.
Solving the liquidity problem
Real estate is an inherently illiquid asset. This is because it is difficult to buy and sell commercial real estate quickly; one of the key reasons for this is lack of updated and accurate information.
Digitisation of this information will not solve real estate’s liquidity problem. Instead, asset managers need to look at integrating AI solutions, such as Stonal’s, that utilise AI-systems to produce high quality data by automatically verifying the authenticity of data before it is integrated into the decision-making process.
This means that real estate asset managers and owners are able to base their decisions on accurate information and secure optimal outcomes each time.[2] This allows asset managers to make data-driven decisions that are accurate and enhance the buying process of CRE.
A long-term solution
There is a clear requirement to ensure that technological solutions come as part of a broader, more comprehensive strategy to address the root causes of the industry’s problems. Once the immediate issues have been identified and triaged, more developed technologies, like Stonal’s AI solution, can be administered.
