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AI Use Cases

A collection of over 250 uses for artificial intelligence

A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more

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Energy efficiency assessment

Introduction

The property industry, like many others, is changing rapidly due to the advancements in Artificial Intelligence (AI) and Machine Learning (ML). These technologies are being applied in the construction of intelligent buildings which are energy conserving thus reducing the costs while being eco-friendly. The above mentioned systems and technologies can be employed to manage heating, cooling, lighting and suchlike in order to ensure that energy is consumed optimally and any variations may point to a fault. They can also be used to understand the usage trends and make future projections to adjust accordingly. Furthermore, AI and ML can be employed to determine the energy efficiency of a property and recommend ways of improving on it which will benefit the property owners, managers and tenants.

Challenges

The use of AI and ML in the property industry therefore has its advantages and disadvantages. A major drawback is the shortage of quality data. This is especially so for many property owners and managers who do not have access to adequate and reliable information on energy consumption and building performance that is necessary for the proper application of AI and ML. Some of the stakeholders have not embraced the use of these technologies due to the lack of understanding and awareness of the advantages that come with it. There are legal and regulatory barriers that may hinder the growth of the sector such as privacy issues and the local building codes. Also, it is expensive to integrate AI and ML solutions and this may not be affordable to some organizations.

AI Solutions

There have been several AI solutions designed to overcome these challenges. For instance, Google’s Project Sunroof has applied machine learning to parse satellite images and estimate the solar potential of roofs to help property owners on the decision regarding solar systems. Some of the companies in this sector include Enertiv which applies AI to monitor equipment and systems in real-time and identify weaknesses and potential failures to prevent downtime and reduce costs of energy utilization. IBM’s Watson IoT platform, for instance, employs AI to integrate information from multiple vantage points including weather data and room occupancy to manage buildings. Also, there are start-ups like Verdigris and Carbon Lighthouse that have employed AI to study the energy consumption and provide recommendations on how to make it more effective.

Benefits

There are a lot of advantages of using AI and ML in the property industry. These technologies are also very useful in enhancing energy efficiency where they can lead to huge cost savings. They can also enhance the level of comfort and convenience of the occupants through ensuring that the systems are well maintained. Moreover, AI and ML can also assist in decreasing the negative effects on the environment through reducing energy loss. Last but not the least, the insights and data that these technologies offer can be useful for planning and decision making to enhance the competitiveness of property owners and managers.

Return on Investment

AI and ML applications in the property industry can be very profitable in terms of the return on investment (ROI). For instance, Google’s Project Sunroof has found out that 80% of all buildings in the US are suitable for solar, which presents a massive opportunity for cost reductions. According to Enertiv, their AI can help cut down on operating costs by 10-15%, while Verdigris states that its AI-enabled energy management system can reduce energy expenses by as much as 50%. However, the ROI will vary based on the particular use case, the initial capital investment, and the price of energy.

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