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Home - How artificial intelligence will transform the future of commercial real estate
AI-Machine-LearningIn-Building Tech

How artificial intelligence will transform the future of commercial real estate

by urvashi January 10, 2019
written by urvashi January 10, 2019 Share
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A new report released by PwC and the Urban Land Institute finds that artificial intelligence is poised to become one of the most transformative technologies in coming years, as the real estate market undergoes sustained maturation.

The report reveals that despite skepticism about AI’s potential to disrupt the existing marketplace, big data and predictive analytics have become an integral part of the business and will expand over time.

Artificial intelligence will play an especially critical role in the search for information and the control of building systems.

Role of artificial intelligence in smart building controls

Artificial intelligence-based technologies have already penetrated the smart building marketplace, which now offers machine learning-based building controls for lighting, HVAC, energy management, elevator maintenance, occupant tracking collectively designed to reduce operational costs, enhance tenant experience and improve workplace productivity.

In 2019, smart building security systems which use AI/ML for the purposes of biometric identification and facial recognition to control property access will start to emerge.

The continued development and adoption of AI will provide enhanced operational efficiencies, advanced employee productivity and improved customer service in nearly every facet of the business, from the optimization of energy to the financial forecasting of commercial real estate portfolios.

As its adoption continues, building owners and operators will start to shift the allocation of capital from investment in infrastructure to investment in technology.

Disintermediation threat or opportunity?

A potential, nascent area which holds tremendous unrealized value is disintermediation, or the reduction in the use of intermediaries between producers and consumers.

Innovation surrounding disintermediation has been largely focused on the residential sector, offering AI-driven applications for home-buying.

However, the report found that it is not likely that advancements in AI/ML will result in ?the real estate broker? becoming obsolete, especially in an industry where distinctly human factors like judgment and trust play a significant role.

Instead, AI-based applications will be used as a tool to enhance the customer experience, alongside brokers.

The report also found that disintermediation in the commercial property arena will be more challenging, due to the lack of homogeneity in relevant data and the complexity of investment choices available to buyers and lessees, when compared with residential markets.

Despite these challenges, as the range of AI/ML use cases continue to expand over time, the industry will undoubtedly find greater cost savings through operational efficiencies, reduced labor costs and new ways to generate income through data monetization.

As predictive capabilities harness value from the vast insights derived from machine learning feedback mechanisms, building owners and real estate executives described AI?s potential as becoming increasingly ?parabolic? with a steep curve of increasing utility and adoption.

The real estate investment community sees real estate as an information-generating industry where monetizing data from office and retail buildings can serve as a means of creating income beyond traditional rents and leases in the near future.

Challenges data security and privacy

While tremendous opportunities for growth exist, the report underscores that AI does not come without its challenges.

The report concluded that data security and privacy concerns continue to remain top-of-mind for building owners, who will need to find a way to balance the need for functionality and growth while protecting the identity and data of those whose activities are being tracked.

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Table of Contents

  • Role of artificial intelligence in smart building controls
  • Disintermediation threat or opportunity?
  • Challenges data security and privacy
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