Hogan Lovells 2024-2025 AI Trends Guide - Flipbook - Page 38
Real Estate
AI applications for investor
decision-making
AI technologies have the potential to enhance various
aspects of commercial real estate through data analysis and
predictive modelling. By incorporating AI applications into
their operations, commercial real estate companies can
improve decision-making processes, and ultimately drive
better business outcomes. Here we look at some examples of
current, and potential, applications of AI technologies in the
investor decision-making process.
Property valuations
AI algorithms can analyse vast amounts of data, including
market trends, property features, and historical sales data to
provide accurate property valuations.
Predictive analytics and market analysis
Machine learning AI technologies can forecast future
market conditions, rental prices, and occupancy rates based
on historical data, helping anticipation of changes in the
market. AI technologies can be used to identify market trends
and patterns, enabling a better understanding of market
dynamics and guiding strategic investment choices.
Marketing optimization
Investors can use AI tools to simulate different investment
strategies and assess potential risks and returns based on
various scenarios. AI algorithms can analyze customer
behaviour and preferences to tailor marketing strategies for
specific properties or demographics.
The complexity, accuracy, and scaleability of AI technology
is constantly developing and the direction of travel is clear:
AI technology will be integrated into the real estate decisionmaking process. These examples are by no means exhaustive
and we’re excited to see what happens on the AI journey.
AI integration in smart buildings
Smart buildings utilize a variety of technologies to
enhance efficiency, comfort, and sustainability, and AI is
increasingly being integrated into smart buildings with
those goals in mind. By integrating AI technologies into
their infrastructure, smart buildings can achieve greater
operational efficiency. A few examples include:
AI algorithms analyse energy consumption, identify
inefficiencies and suggest optimizations of Building
Management Systems that control heating, ventilation,
air-conditioning, and lighting systems. This helps reduce
energy waste, lower utility costs, and improve operational
efficiency;
AI systems can learn from occupant preferences regarding
temperature, lighting, and other environmental factors.
They can automatically adjust settings to enhance
comfort while maintaining energy efficiency;
By using machine learning models, AI can predict when
equipment or systems are likely to fail based on historical
data and real-time monitoring. This allows for proactive
maintenance, reducing downtime and repair costs;
Advanced security technologies include biometric access
controls, surveillance cameras with facial recognition
capabilities, and smart alarms that can be monitored
remotely for enhanced safety;
AI can analyze how spaces are used within a building,
providing insights that help optimize layouts and improve
space utilization. This is particularly useful in office
buildings where space efficiency is critical; particularly
important in open-plan and hot-desking workspaces and
where car parking is at a premium; and
These examples just scratch the surface of the possibilities.
AI technology is evolving and the extent and direction of
uses in the occupier experience are yet to be seen but will no
doubt be exciting.
Authors
Dan Norris
Partner
London
Clare King
Senior Associate
London
Ed Newport
Senior Associate
London
