Artificial Intelligence (AI)-Driven Smart Grid Intrusion Detection Market Report 2025

The artificial intelligence (AI)-driven smart grid intrusion detection market size has grown rapidly in recent years. It will grow from $1.76 billion in 2024 to $2.11 billion in 2025 at a compound annual growth rate (CAGR) of 19.9%. The growth in the historic period was driven by the rising number of cyberattacks on power infrastructure, increasing adoption of smart grids, government regulations focused on critical infrastructure protection, heightened awareness of energy security, and the privatization and deregulation of power utilities.

The artificial intelligence (AI)-driven smart grid intrusion detection market size is expected to see rapid growth in the next few years. It will grow to $4.3 billion in 2029 at a compound annual growth rate (CAGR) of 19.5%. The growth in the forecast period can be attributed to the expansion of renewable energy sources, the increasing integration of Internet of Things (IoT) and connected devices in power grids, rising investments in grid modernization, stricter compliance requirements, and growing urbanization alongside higher electricity demand. Key trends expected during this period include a shift toward real-time threat detection, adoption of edge computing for grid security, integration of blockchain to ensure data integrity, wider use of digital twins in grid management, and increased collaboration between utilities and cybersecurity firms.

The rising cybersecurity threats are expected to drive the growth of the artificial intelligence (AI)-driven smart grid intrusion detection market in the coming years. Cybersecurity threats are malicious actions or events aimed at compromising the confidentiality, integrity, or availability of digital systems, networks, or data. The increase in these threats is largely due to greater digitalization, which expands the attack surface by placing more data, systems, and services online, making them vulnerable to malicious actors. AI-driven smart grid intrusion detection helps address these threats by continuously monitoring the grid, detecting anomalies in real time, and preventing potential attacks before they disrupt critical infrastructure. For example, in November 2023, the Australian Signals Directorate reported that nearly 94,000 cybercrime reports were submitted during the 2022-23 financial year, marking a 23% increase from the previous year, with an average of one report received every six minutes. This surge in cybersecurity threats is thus propelling the market growth.

The growth of the AI-driven smart grid intrusion detection market is also being fueled by the increasing number of connected devices. Connected devices are physical objects equipped with sensors, software, and other technologies that allow them to collect and exchange data over the internet. The proliferation of these devices is driven by advances in communication technologies that enable faster, more reliable, and seamless data exchange. AI-driven smart grid intrusion detection supports these devices by continuously monitoring network activity, identifying potential security threats, and responding in real time to ensure safe and reliable operation. For instance, BuildOps Inc., a US-based SaaS company, reported that the number of Internet of Things (IoT) connected devices grew by 25% between 2021 and 2022, followed by a 28% increase from 2022 to 2023. The expanding number of connected devices is therefore contributing to market growth.

Rising energy demand is another factor driving the growth of the AI-driven smart grid intrusion detection market. Energy, derived from sources such as electricity, fossil fuels, or renewables, powers homes, industries, transportation, and technology. Population growth is increasing energy consumption as more people require electricity, heating, transportation, and industrial services. This growth in demand adds complexity and scale to power grids, making AI-driven smart grid intrusion detection critical for monitoring, analyzing, and protecting the network from potential threats in real time. For example, Statistics Canada reported that in 2022, Canada’s primary energy production rose by 3.9% to 22,616 petajoules, following a 4.5% increase in 2021. Consequently, the rising energy demand is supporting the expansion of the market.

Major players in the artificial intelligence (ai)-driven smart grid intrusion detection market are Siemens Energy AG, Hitachi Energy Ltd., IBM Corporation, Cisco Systems Inc., ABB Ltd., BAE Systems plc, Cognizant Technology Solutions Corporation, Palo Alto Networks Inc., Fortinet Inc., Splunk Inc., Itron, Trellix, Trend Micro Incorporated, Persistent Systems, Tenable Holdings Inc., Darktrace plc, Kongsberg Digital Software And Services Pvt. Ltd., Claroty Ltd., Dragos Inc., Nozomi Networks Inc.

North America was the largest region in the artificial intelligence-driven smart grid intrusion detection market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in artificial intelligence (AI)-driven smart grid intrusion detection report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the artificial intelligence (AI)-driven smart grid intrusion detection market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the utilities sector, particularly in power generation, grid infrastructure, and renewable energy projects. Higher duties on imported equipment such as turbines, transformers, solar panels, and battery storage systems have increased capital and operational costs for utility providers, forcing them to reconsider project timelines or pass on expenses to consumers through higher energy rates. The water and waste management segments are also affected, with tariffs driving up the cost of essential machinery, piping, and treatment technologies. Additionally, retaliatory tariffs have disrupted global supply chains for critical raw materials like rare earth metals used in clean energy technologies, further complicating the transition to sustainable energy sources. The sector must now prioritize domestic sourcing, digitalization, and efficiency-driven innovations to manage escalating costs while ensuring energy security and regulatory compliance.

Artificial Intelligence (AI)-driven smart grid intrusion detection is a system that leverages AI to continuously monitor and safeguard smart power grids against cyberattacks by detecting abnormal activities in real time, thereby ensuring the security and stability of energy infrastructure. It utilizes advanced machine learning techniques to quickly identify and respond to both known and emerging threats, reducing disruptions and improving grid resilience.

The primary components of AI-driven smart grid intrusion detection include software, hardware, and services. Software comprises intelligent programs that analyze data in real time, detect anomalies, and enable automated, adaptive responses to new threats. It can be deployed on-premises or in the cloud, providing various types of security such as network, endpoint, and application security. These solutions are applied across energy management, critical infrastructure protection, fraud detection, and other areas, serving end users including utilities, industrial, commercial, residential, and other sectors.

The artificial intelligence (AI)-driven smart grid intrusion detection market research report is one of a series of new reports that provides artificial intelligence (AI)-driven smart grid intrusion detection market statistics, including artificial intelligence (AI)-driven smart grid intrusion detection industry global market size, regional shares, competitors with the artificial intelligence (AI)-driven smart grid intrusion detection market share, artificial intelligence (AI)-driven smart grid intrusion detection market segments, market trends, and opportunities, and any further data you may need to thrive in the artificial intelligence (AI)-driven smart grid intrusion detection industry. This artificial intelligence (AI)-driven smart grid intrusion detection market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The artificial intelligence (AI)-driven smart grid intrusion detection market consists of revenues earned by entities by providing services such as consulting and professional services, integration services, managed security services, training and support services, and bundled end-to-end services. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI)-driven smart grid intrusion detection market also includes sales of antivirus and antimalware solutions, firewall solutions, identity and access management systems, security and vulnerability management tools, and distributed denial-of-service (DDoS) protection solutions. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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