AI is driving efficiency in real estate: don’t get left behind
Artificial intelligence (AI), whilst still in a growth stage, is a rapidly improving technology that has the potential to transform industries and engender significant improvements in efficiency. AI has already had an impact on real estate, and we are likely to see further growth and maturity over the next decade.
A key process where AI has led to significant improvements in the real estate industry is the automation of data collection. Real estate data impacts buying, selling, managing, and investing in properties, serving as the foundation upon which decisions are made. Integrating automation reduces the risk of unclean data as data authenticity can be verified before even entering the platform.
Despite the buzz surrounding AI’s potential, we primarily hear about concerns regarding cybersecurity, job displacement, and overreliance on AI solutions. But, there is another side to the discussion.
What are the consequences of not embracing digital transformation in real estate?
The risks of not embracing AI-integration within asset management are far more significant. Amid preoccupation with the potential downfalls of AI, it is critical that we do not overlook the dangers of not integrating automated solutions.
Don’t fall into the cycle of neglecting your data
Data is not just an asset. With clean and reliable real estate data, good investments are made, liquidity is maintained, and profitability is optimised. When this is compromised, the consequences are far reaching.
Dirty data becomes a problem when asset managers rely on manual processes for collection. When an organisation or individual fails to properly collect, manage, maintain, or utilise data, they compromise the quality of their decision-making.
Inaccurate property valuations and pricing are key results of this, impacting a company’s bottom line and eroding investor confidence.
Automation’s role in mitigating these consequences in real estate is paramount. To avoid data neglect and dirty data, real estate asset managers and organisations must prioritise proper data management practices.
Stonal’s management solutions automate data collection for owners and managers, encouraging higher quality data for the appropriate level of decision-making.
Narrowing the digital divide
Even in 2019, results from the Altus Group CRE Innovation Report found that 49% of commercial real estate executives acknowledged the fact that AI can produce operational efficiencies and massive budget savings.
Today’s market requires the evidential value of outcomes. Companies that resist digitisation risk becoming victims of slow-moving processes compared to their reactive, automated counterparts.
We already know that AI streamlines administrative tasks, reduces workloads, and enhances operational efficiencies. Through the right AI platform, your organisation is also able to analyse data faster and with greater precision. Stonal’s AI-powered platform creates quicker decision-making by extracting relevant data from complex documents like leases, appraisals, and loan documents.
Automation enables asset managers to make informed decisions regarding property acquisitions, pricing strategies, and market entry points.
Why risk being left behind?
The price of inaction is steep. The consequences of unclean data and resistance to digitisation in real estate are not just threats but genuine obstacles to asset managers’ success.
By enabling asset managers to collect and process clean data efficiently, Stonal enhances asset managers decision-making.
The true risk surrounding AI in real estate is ignoring the inevitable shift to more automated practices. When competitors are able to adopt means of increasing efficiency and accuracy in decision-making, those who do not will fail to stay competitive.
AI integration is no longer an optional endeavour for those who want to remain competitive in the asset management landscape. Embracing AI means better and more efficient decision-making. Those who do not turn to automation to improve operations will inevitably be left behind.
