Artificial intelligence (AI) technologies enable several jobs that have been considered not to be handled without human intelligence, until quite recently, to be handled by computers or robots administered by computers in a faster and more efficient way.
The technology which is among the most significant players in future's business world is already actively used in several sectors. However, some sectors have just begun to adapt these innovations to their business models. For example, AI technology use in the energy sector is still very limited and most of the applications are still in the planning phase. Although AI technology is expected to provide revolutionary advancements in energy saving, some of the most significant factors that limit its progress are the potential negative impacts on energy systems and socio-economic structures of communities. Construction is also among the sectors that have limited adaptation to AI technologies. There were almost no developments in AI technologies compared to other sectors, even though AI is deemed to create major opportunities for construction.
The changes in energy production, sales and distribution methods are expected to disseminate the use of AI technology. This revolutionary technology in energy saving can minimise carbon emissions and therefore help tackle climate change. This will be only possible when the new methods are adapted to production processes from renewable energy resources. Another point which should be considered in developing new methods is costs. Eventually, it will be required to benefit from AI more and more each day, which will create a larger impact area in medium to long-term, to meet the ever-increasing clean, cheap and reliable energy demand.
One of the biggest challenges in integration of renewable resources to the system is the direct impact of weather conditions and the resulting intermittency on production. For instance, if the weather is cloudy or there is no wind, this may cause the energy production to stop. Overproduction is also possible depending on the weather conditions. AI technologies are expected to come in handy for solutions to store the excess production resulting from intermittent production regime, which usually require higher costs.
AI technologies enable us to get informed in advance on energy consumption and manage the fluctuations in production, which may reduce the dependency on alternative mechanisms operated based on weather conditions. Besides, these technologies can go beyond the extents of a human being in decision-making and planning processes and overcome more complicated processes. For instance, in the event of an energy shortage in a region, AI can resolve the issue by managing the energy consumptions of larger regions and communities in a faster and more efficient way. The main object of the solution may vary from large industries to the refrigerator in your home. Today, it may sound like a part from a science fiction movie, for the energy use of the home appliances to be controlled by a computer or a robot, however the number of examples we see in our daily lives already started to increase. For example, the AI that detects how frequently you use the apps through a new app that can be used in an operating system shuts down the rarely-used apps that run in the background, which enables your battery to last longer. Similarly, AI solutions can be utilized to use energy more efficiently in household appliances. For instance, it is possible to know the exact energy use and the corresponding cost of home appliances and, remedial actions can be taken based on this information. Thus, users can plan to do the laundry when the electricity is at its cheapest, instead of running it at times when they don't really know how much it would cost. The demand for devices that consume higher amounts of energy is expected to decrease due to such progresses; hence, producers will attach more importance to energy efficiency. Business world may also use similar methods to benefit from the energy saving solutions of AI.
In the construction sector, of which the cost of annual operations exceeds USD 10 trillion, AI solutions are still limited despite the ever-changing demands of the customers. Yet, AI technologies may help the sector to overcome major issues such as exceeding costs and work schedules and security vulnerabilities.
Despite the weaknesses of construction sector on the path to digitalization, business sectors that intersect like transportation and manufacturing have already begun adapting to AI technologies and they commenced to run like an ecosystem by removing boundaries. The impacts of these recent developments are expected to be observed in medium and long-term periods. Hence, the players in the construction sector need to adopt the AI applications and techniques to be able to take their places in the vast ecosystems of the future and compete with innovative companies that will join the sector. However, current capacities, employees, business models of the companies and the tools used are not enough to adapt to AI, despite the opportunities offered by the new technologies. As a result, it is expected that the sector will allocate more resources soon in order to access the required infrastructure.
There are three main stages that sector leaders shall follow to introduce AI technologies with construction sector. The first one is to look through the limited number of AI initiatives that have been put into operation so far. For example, there are construction companies that optimize the project schedules by using technologies that offer millions of different alternatives for planning from the beginning until the delivery of the project. The second one is to identify technologies used in other sectors which are applicable for construction sector. Visual scanning and categorization technologies used in several sectors for various reasons can be used to identify employee behaviors that may pose security threats. Moreover, the data can be used as a tool to determine the priorities in employee training. The last stage is to develop new AI technologies for sector’s exclusive needs and fulfil the requirements of the modern business era. In this stage, thousands of different needs and thousands of solutions for each need can be identified.
Implementing AI technologies at both energy and construction sectors offers tremendous opportunities; however, there are also some risky sides of these technologies. For example, when controls are left to AI in the energy sector makes the system vulnerable to cyber-attacks. Therefore, one of the main purposes shall be building structures protected from these threats while developing and applying these technologies. In addition, if innovations in the energy sector resulting from digitalization stay limited to consumers with high purchasing power, then the energy prices may increase for the rest. The lack of capacity in the construction sector, which has been mentioned before, is also a factor that increases the cost of adaptation to AI technologies. Yet, despite the risks and challenges, the pioneering companies that are eager to adopt innovations in both sectors are expected to stand out and make higher profits.