How Technology is Changing the Commercial Real Estate Industry
The CRE industry is experiencing a tech-driven transformation that’s changing everything from how deals are sourced to how properties are managed.
Commercial real estate has traditionally had a reputation for its slow adoption of new technologies – but the landscape is changing quickly. According to Deloitte’s 2025 CRE Outlook, 81% of leaders surveyed identified data and technology as the area where they are most likely to focus spending for the coming year.
Here’s what you need to know:
- The Human Factor: Human analysts remain essential for interpreting complex data, navigating relationships, and applying strategic judgment that technology alone can’t replicate.
- Enhanced Property Performance: Smart building technologies are optimizing energy usage, reducing operational costs, and more – directly increasing asset value and long-term investment returns.
- Data-Driven Decision Making: Technology enables CRE investors to leverage big data and AI analytics for more accurate property valuations, market forecasting, and risk assessment.
Human Analysts Are Vital
While AI and other tools are revolutionizing CRE investing, human analysts remain indispensable. AI excels at processing vast datasets, identifying patterns, and predicting trends – but it lacks the nuanced understanding of human behavior and market sentiment that often drive real estate decisions.
The role of human analysts is to interpret AI-generated insights, in coordination with their own experience and intuition. For instance, an AI model might flag a market for potential growth based on data, but a human analyst can assess whether that growth is actually sustainable based on firsthand knowledge of local developments.
To fully capitalize on AI’s capabilities in commercial real estate, CRE teams recognize that a robust technological foundation is essential. Data architects and engineers are now key players, designing and maintaining the infrastructures that collect, secure, and process vast amounts of market data. Their technical expertise ensures that cloud analytics and language models operate seamlessly, turning raw data into actionable insights that human analysts can interpret alongside their market experience. By bridging the gap between sophisticated algorithms and practical decision-making, these professionals help CRE teams scale their technology and adapt to evolving market demands.
Human analysts also play a crucial role in relationship management, areas where AI has clear limitations. CRE investing is very much an industry of personal connections, building trust with stakeholders, and understanding the motivations of buyers and sellers.
PropTech
The pandemic prompted what’s now known as the “PropTech boom”, with the global PropTech market now expected to grow to more than $130 billion by 2033 (at a rate of 16% a year).
At a baseline level, PropTech automates time-consuming processes like paperwork, tenant screening, and property management. But it’s also creating smarter, more efficient real estate experiences in some interesting ways:
- Smart sensors that help optimize office space and energy usage, especially in hybrid work environments.
- Drones that provide high-resolution imagery for property inspections, site surveys, and marketing.
- AI-driven platforms that adjust rental prices dynamically based on demand, competition, and seasonality.
- Tokenization of real estate will allow for fractional ownership, making property investment more accessible.
Tech adoption has translated to greater buyer and renter interest in properties. Compass, for example, achieved a 153% increase in homepage click-through rates and a 107% boost in engagement by implementing AI-powered recommendations and similar home features in its search engine.
For CRE investors, these innovations lead to higher tenant satisfaction, lower vacancy rates, and better long-term returns on investment.
Data-Driven Decision Making
One of the most profound impacts of technology in CRE investment is the ability to leverage vast amounts of data to improve decision-making. Almost 70% of CRE business leaders say they have an AI strategy in place and are piloting use cases.
Advanced analytics platforms can aggregate information (real-time and historical) from multiple sources – like market trends, demographic data, and property performance metrics – to provide a comprehensive view of potential investments. This helps human investors anticipate risks, create more accurate property valuations, and predict emerging “hot spots” – before these trends are obvious to the general market.
AI tools like ChatGPT, Claude, and CoPilot are streamlining decision-making by quickly parsing lengthy reports and drafting detailed investment analyses. These large language models transform complex, unstructured data into clear insights, empowering teams to focus on strategic planning.
Meanwhile, cloud platforms such as Azure, AWS, and GCP integrate vast amounts of data into interactive dashboards. Azure’s advanced ML capabilities help build predictive models to spot potential “hot spots,” while reporting platforms like Power BI and Tableau convert raw data into real-time visualizations that support agile decision-making.
By combining these advanced technologies CRE professionals can transition from reactive strategies to proactive, data-driven investments—refining property valuations and staying ahead in a competitive market.
Property Valuation
Traditional property appraisals rely on comparable sales, manual assessments, and static metrics. But AI-driven Automated Valuation Models (AVMs) improve on this by considering data-based factors like school ratings, crime statistics, walkability scores, environmental risks, and even social media sentiment about neighborhoods. AI can even evaluate micro-markets down to specific streets or building types.
The adoption of machine learning in property valuation could improve accuracy by up to 40%, according to the Journal of Property Investment & Finance.
Machine learning algorithms can forecast future property performance by identifying trends in rental income, occupancy rates, and market fluctuations. This predictive capability helps investors anticipate changes in property value and optimize their investment strategies accordingly.
Emerging tools are further refining property valuation in the CRE space. Platforms like Reonomy and CompStak are integrating machine learning with extensive commercial data to deliver real-time, data-driven valuations. Similarly, solutions from Altus Group and Clear Capital are designed specifically for CRE, offering sophisticated AVM capabilities and risk assessment models. Additionally, tools like Argus Enterprise are evolving with AI enhancements to provide detailed scenario analyses and forward-looking projections that support more informed investment decisions.
By leveraging these advanced and emerging tools, CRE professionals can achieve more precise valuations and forecasts, ultimately gaining a competitive edge in an increasingly dynamic market.
Risk Assessment
Technology is also helping investors assess risk exposure across different regions, property types, or economic conditions.
For example, AI tools can detect anomalies or red flags in property data, such as inconsistent cash flows, market volatility, or potential legal issues. They can also flag inconsistencies in transaction histories, ownership records, or tenant information, reducing the risk of fraudulent activities.
Geospatial Analysis tools can highlight some of these risks. Real-time data on crime rates, environmental hazards, climate risks, and infrastructure developments can be overlaid on property maps to assess the long-term viability of an investment – like properties susceptible to flooding or which property values will be impacted by a nearby infrastructure project.
Esri’s ArcGIS platform offers robust geospatial analytics that allow investors to overlay diverse datasets—ranging from environmental hazards to infrastructure developments—directly onto property maps, yielding actionable insights on localized risks.
Additionally, Deloitte’s 2025 CRE Outlook warns that CRE technology investment should focus on cybersecurity. Because CRE deals with a vast amount of sensitive data, it is becoming an increasing target for hackers.
One of AI’s “most promising applications” in cybersecurity is proactive threat hunting. AI-driven solutions like Darktrace and Splunk are increasingly being deployed for proactive threat hunting. These tools continuously monitor network activity, flag irregularities, and identify vulnerabilities such as weak passwords or unauthorized access points, thereby mitigating potential breaches before they escalate. Integrating these specific technologies not only refines the risk assessment process but also strengthens the overall security framework for CRE investments.
The Future
As technologies continue to evolve, their role in real estate will grow in fascinating ways.
- The growing use of digital twins – virtual replicas of physical properties – will allow investors to model the financial performance of a building under different conditions, like shifts in tenant occupancy, energy costs, or regulatory changes, before committing capital.
- Augmented reality (AR) and virtual reality (VR) will go beyond property tours to offer fully immersive environments in hyper-realistic detail.
- Using blockchain and smart contracts, CRE deals could be executed in minutes via decentralized platforms that automatically verify ownership and streamline compliance.
Today and in the future, investors who effectively combine data-driven insights with human expertise will unlock new opportunities and drive smarter, more strategic growth in an evolving market.
