AI (artificial intelligence) & Commercial Real Estate


Artificial intelligence (AI), if used strategically, could significantly improve the commercial property sector for investors and owners. Asset managers, too, would benefit.

AI will profoundly impact commercial real estate as data availability and transparency increase. This will encourage industry participants to adopt data-driven decision-making. The stakeholders who can grasp this massive shift will have an advantage over their peers.


How AI is transforming the real estate industry

AI can aggregate and analyze historical property values, market trends, and economic indicators to provide more accurate valuations. This allows investors to make better decisions by predicting the market's future performance.


AI is being integrated into many real estate firms. Industry peers, for example, are using AI to enhance the user experience by automating property valuations, offering AI-powered insights and market trend analyses. We are still beginning to realize AI's potential in commercial property.


How AI Can Be Applied To Commercial Real Estate

Commercial real estate has historically needed to be faster to adopt new technology. This presents an excellent opportunity for investors and entrepreneurs to use technology to enhance their results. AI has many opportunities to disrupt the commercial real estate sector, including:


Improved data analysis for better investment potential

AI is an effective gateway for data collection. AI can identify value-added targets in a market by analyzing large and fragmented datasets. This includes, for example, identifying markets that have the potential to grow at a high rate in the future or sourcing properties that could be better managed or energy-inefficient.


Streamlined Property management

AI can automate routine tasks in property management, such as tenant communication and maintenance requests. It also performs predictive maintenance that saves property managers' time and improves their properties' overall efficiency and value. AI can use historical data to identify areas underutilized in commercial buildings. It then recommends the best space configurations for these areas, creating more efficient real-estate spaces.


The Experience Has Been Improved With A More Tailored And Personalized Experience

AI can enhance overall investor personalization by providing recommendations to tenants and investors according to their preferences, budgets, and location requirements. The use of generative AI is also a great way to help. It can offer a chat experience that allows individuals to have an informed discussion and make more confident decisions.


Better Risk Mitigation

AI can predict equipment failures and identify environmental risks by analyzing building sensor data. It allows property owners to develop proactive maintenance strategies that reduce downtime, minimize costly repairs, and protect assets from unexpected damage. AI can protect against climate-related disasters by providing proactive protection from difficult-to-expect risks.


Leveraging AI

For a better user experience, companies combine machine learning with generative AI. They use predictive analytics and historical data to determine the best balance between investment returns, downside risk, and market volatility. AI also improves the efficiency of their workflow and transaction management. They use AI for tasks like lease data extraction and legal document generation, IRR forecasting, and automated comps generation.


They use AI to gain insights into mortgage origination, debt maturity, and the overall leverage of an owner to determine how likely they are to sell.

AI is not only used to improve the quality of our decisions but also to save time and money in real estate investment. The best path forward for commercial real estate is to embrace a human-AI collaboration, where human expertise and the intelligence of AI are combined.


The Future of Industry Leaders

AI implementation can also bring about some common roadblocks for organizations. Contextual understanding is a significant challenge. AI will not be able to understand or process all aspects of real estate investing decision-making. The human brain can use its intuition and experience, which gives it a distinct advantage when investing in real estate. Humans can also understand the neighborhood dynamics in a particular property market, which may not be apparent from real estate data. AI, on the other hand, may not be able to fully understand local market conditions, neighborhood dynamics, zoning laws, or specific property features, which can have a significant impact on overall investment decisions.


Data validation problems are another roadblock. AI alone cannot interpret all real estate data. Humans can evaluate and validate data used by AI to ensure accuracy and relevance. They can detect data gaps, correct biases, and assess the reliability of information. This reduces the risk of making flawed decisions based on AI outputs.


Last but not least, there is the issue of needing to be more reliant on historical data. AI and machine learning use historical data to predict the future. Humans can still analyze changes in policy, economic conditions, or unanticipated events to predict future real estate markets.


Final Thoughts

The commercial real estate sector will undergo a transformation in the next five to ten years. Some observers are concerned that AI could lead to mass unemployment in the commercial real estate industry. However, I see AI as a complementary tool, not as a substitute, for human creativity. 


Humans and AI working together is the best way to improve efficiency, speed, and scale while also reducing costs and time. The next generation of winners will be companies that embrace AI but also combine machine learning, human expertise, and generative AI in order to unlock the untapped market potential.



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