Artificial intelligence (AI) is being used in electric grid systems to enhance their stability. The grid system refers to an interconnected network that stores energy and maintains the energy flow. These grids differ in size and technical parameters like transnational grids for continents, national grids for countries, and grids for buildings. These systems store energy from sources like electricity generation plants, wind power stations, and solar power plants. Inputs from multiple sources lead to the generation of large volume of data, which is analyzed by using AI to increase the stability of the systems.

Moreover, the current trend of integrating internet of things (IoT) in energy management systems will drive the AI in energy management market at a CAGR of 18.9% during 2019–2024. The market has the potential to grow from $4,439.1 million in 2018 to $12,200.9 million by 2024. IoT is used for data insight services, remote controlling, software automation, and proactive monitoring in the energy management systems. This new-age technology helps in displaying the amount of energy consumed through sensors and smart meters at the machine and production line levels.  

In addition, energy companies are also deploying AI-enabled robots in large numbers, as these have the potential to revolutionize the operations and cost structure of such firms. Further, the usage of these robots helps in reducing the number of risks and improving the health of personnel, in the energy sector.  The AI-supported robots can also inspect, certify, maintain, and repair energy installation units. Besides, these robots can also be used in decommissioning and cleaning up of nuclear waste. 

Categories under the solution segment of the AI in energy management market include demand management, infrastructure management, and renewable management. In 2018, the demand management category held the largest market share, on account of the increasing focus of utilities on predicting total energy demand by using AI-enabled smart meters, to provide required energy across households. Whereas, in the coming years, the renewable management category will observe the fastest growth, due to the escalating focus on generating energy from renewable sources like biomass, wind, thermal, solar, and geothermal, to reduce the global carbon footprint.

These solutions are being used for forecasting energy output, and generating, distributing, and transmitting energy. In recent years, the energy sector has been increasingly deploying such solutions and AI technologies like computer vision, natural language processing (NLP), and machine learning (ML), to predict energy output. In the coming years, these technologies will be primarily used for generating energy, due to the burgeoning requirement for managing the total output of energy generated through solar power plants, thermal plants, and wind power stations, to match the temporal and spatial variations in real time.

According to P&S Intelligence, the North American AI in energy management market generated the highest revenue in 2018, globally, and it is expected to maintain its position in the foreseeable future. This is attributed to the presence of key leading AI solution providers and supportive government policies in the region. The U.S. is expected to lead the North American market in the coming years, due to the active deployment of AI solutions in its energy sector to integrate energy generated from non-renewable and renewable sources into the total energy supply. 

Thus, the rising demand for energy and the increasing focus on grid stability will fuel the integration of AI solutions in the energy sector, globally.