How AI is Revolutionizing Real Estate Investment Due Diligence
Amarantos Capital Research Team
Mar 23, 2025
8 min read
The commercial real estate industry, traditionally known for its reliance on human expertise and gut instinct, is experiencing a seismic transformation. Artificial intelligence has enormous potential to reshape real estate, with near and long-term impacts ranging from the emergence of new markets and asset types to innovations in investment and revenue models, according to JLL's latest research. For institutional investors, this technological revolution represents an opportunity to gain competitive advantages through AI-powered due diligence processes.
The Current State of AI in Real Estate Due Diligence
The real estate industry is poised to reap as much as $34 billion in efficiency gains over the next five years from the use of AI to automate tasks, according to Morgan Stanley Research. This transformation is particularly evident in due diligence processes, where AI is streamlining everything from document analysis to market forecasting.
AI-driven platforms address the growing complexity of modern deal-making by enhancing efficiency, accuracy, and risk management. Companies like Drooms and Imprima are leading this charge with AI-powered data rooms that automate document indexing, translation, and anomaly detection—tasks that traditionally required countless hours of manual review.
Automated Valuation Models (AVMs) Lead the Way
One of the most mature applications of AI in real estate due diligence is automated property valuation. ML-powered Automated Valuation Models (AVM) can assess the value of an asset with an absolute error of less than 4% for homes and under 6% for commercial properties, offering accurate insights for better investment decisions.
A study by the Journal of Real Estate Research found that ML-based automated valuation models reduced absolute percentage error by 18.4% compared to traditional hedonic regression methods. This improvement translates directly to more accurate valuations and better-informed investment decisions.
Machine Learning Algorithms Transforming Investment Analysis
The sophistication of modern AI systems lies in their ability to process multiple data streams simultaneously. In real estate, several types of ML algorithms have proven particularly valuable: Regression Algorithms: These predict continuous values, making them ideal for property price estimation.
Leading platforms like Skyline AI exemplify this approach. Skyline AI uses a proprietary AI platform to analyze vast amounts of real estate data, including transaction history, demographic information, and economic indicators, to predict property performance and identify undervalued assets.
Beyond Traditional Metrics
What sets AI-powered due diligence apart is its ability to incorporate non-traditional data sources. Machine Learning models have been criticized for disregarding key features. For example, the construction quality might not be relevant to an algorithm, but it surely is for a human. However, advanced systems are now incorporating visual data, social media sentiment, and even satellite imagery to provide more comprehensive property assessments.
The power of these algorithms lies in their ability to simultaneously process hundreds of variables affecting property values—from obvious factors like square footage and location to subtle influences like proximity to coffee shops or changing neighborhood demographics.
Real-World Applications and Success Stories
Market Prediction and Trend Analysis
By using ML algorithms, researchers can analyze enormous datasets, uncover hidden relationships, and make far more accurate predictions than traditional tools. Recent research from the University of Florida demonstrates that machine learning models can reduce forecasting errors by 68% compared to simple regression models when predicting commercial real estate returns.
ML algorithms analyzing changes in business licenses, building permits, social media sentiment, and demographic shifts can identify neighborhoods poised for appreciation before traditional indicators become evident.
Document Processing and Risk Assessment
AI-powered due diligence platforms are revolutionizing document review processes. Imprima Smart Summaries can automatically extract accurate summaries of the key information from any real estate lease: start and end dates, values, important provisions and more. This capability allows investment teams to process vast amounts of legal documentation in minutes rather than days.
Tasks like document indexing, translation, and anomaly detection are seamless and immediate with modern AI systems, enabling due diligence teams to focus on strategic analysis rather than administrative tasks.
The Competitive Advantage of AI-Powered Due Diligence
Speed and Scale
With a gen AI tool that's fine-tuned using internal and third-party data, an investor can simply ask, "What are the top 25 warehouse properties up for sale that I should invest in?" or, "Which malls are most likely to thrive in the future?" This capability represents a fundamental shift from traditional research methods.
Built AI has been a game-changer for Tuatara Real Estate, revolutionising the way we analyse deals for our clients. Its rapid data analysis has significantly expedited our decision-making processes, ensuring swift responses to market dynamics.
Enhanced Accuracy and Risk Management
The precision offered by AI systems extends beyond simple valuations. The three performance metrics including mean squared error (MSE), root mean squared error (RMSE) and mean absolute percentage error (MAPE) associated with these two algorithms also unambiguously outperform those of SVM, demonstrating consistent improvements across multiple measurement criteria.
Implementation Challenges and Considerations
Despite the clear benefits, implementing AI in due diligence processes requires careful consideration. Organizations will need to consider how they can harness AI strategically and ethically, piloting applications before scaling to deliver value.
Ensure regulatory compliance: Partner with vendors who prioritise data security and align with legal frameworks like the GDPR. This is particularly crucial for institutional investors handling sensitive financial and property data.
The Future of AI-Powered Real Estate Investment
Based on work by the McKinsey Global Institute (MGI), we believe that gen AI could generate $110 billion to $180 billion or more in value for the real estate industry. This value creation will primarily come from enhanced decision-making capabilities and operational efficiencies.
More than nine in ten C-suite leaders believe AI will change the way the workforce operates over the next five years. A similar proportion plans to accelerate investment in AI over that period.
Key Recommendations for Institutional Investors
Start with Pilot Programs: Begin with specific use cases like automated document review or market analysis before scaling to comprehensive AI integration.
Invest in Data Quality: AI systems are only as good as the data they process. Ensure clean, comprehensive datasets for optimal results.
Maintain Human Oversight: Ensuring AI solutions are ethical, lawful, and robust, prioritising data privacy and governance while maintaining human oversight to verify AI suggestions should be of utmost importance.
Partner with Specialized Platforms: Work with established AI providers like Drooms, Imprima, or Built AI that offer real estate-specific solutions.
Conclusion
The integration of AI into real estate due diligence represents more than a technological upgrade—it's a fundamental shift toward data-driven investment strategies. Artificial intelligence is rapidly becoming an integral part of how work gets done in commercial real estate, and firms that embrace these technologies today will have significant competitive advantages tomorrow.
For institutional investors, the question is no longer whether to adopt AI-powered due diligence, but how quickly and effectively they can implement these transformative technologies. As the industry continues to evolve, those who leverage AI's capabilities for faster, more accurate investment decisions will be best positioned to deliver superior risk-adjusted returns in an increasingly competitive marketplace.
About Amarantos Capital: As a leading institutional investment firm, Amarantos Capital utilizes proprietary machine learning and AI algorithms for deal sourcing, underwriting, and valuation across our real estate, technology, and biotechnology portfolios. Our data-driven approach delivers superior risk-adjusted returns for institutional investors and family offices.
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