Grid Resilience Analytics Global Market Report 2026

Grid resilience analytics is a software-based solution that examines power system data to evaluate, predict, and enhance the electricity grid's resilience against disruptions. It leverages real-time and historical data, modeling, and AI-driven simulations to detect vulnerabilities, anticipate extreme events, and assess the impact of outages or disturbances. It aids utilities in boosting grid reliability, minimizing downtime, and planning preventive and corrective actions against natural disasters, cyber threats, or equipment malfunctions.

The main components of grid resilience analytics include software, hardware, and services. Software encompasses solutions that monitor and analyze the electrical grid to predict, prevent, and respond to disruptions, enhancing reliability and operational efficiency. These solutions are deployed through on-premises and cloud modes and utilize technologies including advanced analytics platforms, artificial intelligence (AI) and machine learning (ML) solutions, IoT-enabled systems, supervisory control and data acquisition (SCADA), and others. They are applied across transmission, distribution, generation, renewable integration, disaster recovery, and other applications, serving a wide range of end-users, including utilities, independent power producers, government or municipal bodies, industrial, and other sectors.

Tariffs are influencing the grid resilience analytics market by increasing costs of imported sensors, edge computing devices, communication hardware, and advanced analytics infrastructure. Utilities and government agencies in North America and Europe are most affected due to reliance on imported monitoring equipment, while Asia-Pacific faces higher deployment costs for large-scale analytics platforms. These tariffs are increasing upfront implementation expenses and extending procurement cycles. However, they are also supporting domestic technology development, regional analytics providers, and localized deployment of resilience monitoring solutions.

The grid resilience analytics market research report is one of a series of new reports from The Business Research Company that provides grid resilience analytics market statistics, including grid resilience analytics industry global market size, regional shares, competitors with a grid resilience analytics market share, detailed grid resilience analytics market segments, market trends and opportunities, and any further data you may need to thrive in the grid resilience analytics industry. This grid resilience analytics 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 grid resilience analytics market size has grown rapidly in recent years. It will grow from $2.07 billion in 2025 to $2.47 billion in 2026 at a compound annual growth rate (CAGR) of 19.4%. The growth in the historic period can be attributed to increasing grid exposure to extreme weather, expansion of sensor deployment across grids, reliance on historical outage analysis, early adoption of analytics-based monitoring, growing awareness of grid vulnerabilities.

The grid resilience analytics market size is expected to see rapid growth in the next few years. It will grow to $5.06 billion in 2030 at a compound annual growth rate (CAGR) of 19.6%. The growth in the forecast period can be attributed to increasing frequency of climate-related disruptions, rising investments in grid hardening, growing adoption of AI-driven analytics platforms, expansion of resilience-focused regulatory requirements, increasing demand for predictive grid intelligence. Major trends in the forecast period include increasing use of AI-based grid risk modeling, rising deployment of predictive outage analytics, growing integration of real-time grid monitoring data, expansion of climate and disaster impact simulations, enhanced focus on proactive resilience planning.

The increasing adoption of renewable energy sources is expected to propel the growth of the grid resilience analytics market going forward. Renewable energy sources are naturally replenished resources used for power generation, including sunlight, wind, water, and biomass. The growing uptake of renewable energy is largely driven by environmental priorities and climate change concerns, as governments and organizations aim to lower greenhouse gas emissions, reduce pollution, and shift toward sustainable, low-carbon energy systems. Grid resilience analytics supports renewable energy integration by identifying system vulnerabilities, enhancing grid efficiency, and ensuring consistent and reliable electricity delivery despite the intermittent nature of wind, solar, and other clean energy sources. For instance, in December 2024, according to Eurostat, a Luxembourg-based government agency, renewable energy accounted for 24.5% of total energy consumption in the European Union in 2023, up from 23.0% in 2022. Therefore, the increasing adoption of renewable energy sources is driving the growth of the grid resilience analytics market.

Key companies operating in the grid resilience analytics market are focusing on developing innovative solutions, such as context-aware operational intelligence, to enhance grid reliability, optimize load management, and reduce outage incidents. Context-aware operational intelligence refers to the integration of real-time grid data, environmental conditions, and asset performance metrics to enable predictive and data-driven decision-making across power generation, transmission, and distribution networks. For example, in February 2023, AiDASH Inc., a US-based geospatial analytics company, and Schneider Electric SE, a France-based energy management company, jointly launched a grid resilience offering at DISTRIBUTECH 2023, aimed at helping utilities improve infrastructure monitoring, maintenance, vegetation management, and storm and wildfire resilience, along with other analytics-driven operational functions. The platform combines AiDASH's satellite imagery and AI-powered analytics with Schneider Electric's asset management and operational expertise to deliver real-time insights and proactive grid resilience strategies. This solution illustrates how advanced grid resilience analytics can enhance utility operations by improving situational awareness, operational efficiency, and enterprise-wide resilience planning.

In March 2025, Bidgely Inc., a US-based AI-powered energy intelligence company, acquired Grid4C for an undisclosed amount. Through this acquisition, Bidgely aims to reinforce and expand its UtilityAI Platform by integrating advanced fault detection, diagnostics, load forecasting, and distributed energy resource (DER) analytics capabilities, improving utility forecasting accuracy and grid operations. Grid4C Inc. is a US-based developer of AI-based predictive analytics for the energy sector, offering solutions that deliver predictive insights into grid assets and energy consumption to support enhanced resilience and operational planning.

Major companies operating in the grid resilience analytics market are Siemens AG, Accenture plc, International Business Machines Corporation, General Electric Compan, Oracle Corporation, Hitachi Energy Limited., Schneider Electric Societe Anonyme, Honeywell International Inc., ABB Limited, Eaton Corporatio.n Public Limited Company, Capgemini SE, Infosys Limited., Schweitzer Engineering Laboratories, Incorporated, Bentley Systems, Incorporated, S&C Electric Company, Enel X S.r.l., Energy Exemplar Pty Ltd., Camlin Group Private Limited., Uptake Technologies Inc., AutoGrid Systems Inc., Opus One Solutions Inc., Cybirical Inc.

North America was the largest region in the grid resilience analytics market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the grid resilience analytics market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the grid resilience analytics market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The grid resilience analytics consists of revenues earned by entities by providing services such as data integration, real-time grid monitoring, risk modeling, predictive analytics, outage analysis, scenario simulation, resilience planning, and ongoing technical support. The market value includes the value of related goods sold by the service provider or included within the service offering. The grid resilience analytics includes sales of analytics software platforms, artificial intelligence (AI) based modeling tools, data visualization dashboards, grid simulation software, monitoring systems, and decision support 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.

Grid Resilience Analytics Market Global Report 2026 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses grid resilience analytics market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for grid resilience analytics ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The grid resilience analytics market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

• The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
• The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
• The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
• The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
• The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
• The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
• The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
• The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
• Market segmentations break down the market into sub markets.
• The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
• Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
• The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
• The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.

Scope

• Markets Covered:1) By Component: Software; Hardware; Services
• 2) By Deployment Mode: On Premises; Cloud
• 3) By Technology: Advanced Analytics Platforms; Artificial Intelligence (AI) And Machine Learning (Ml) Solutions; Internet Of Things (Iot) Enabled Systems; Supervisory Control And Data Acquisition (Scada); Other Technologies
• 4) By Application: Transmission; Distribution; Generation; Renewable Integration; Disaster Recovery; Other Applications
• 5) By End User: Utilities; Independent Power Producers; Government And Municipalities; Industrial; Other End Users
• Subsegments:
• 1) By Software: Grid Monitoring And Analytics Software; Predictive Maintenance Software; Risk Assessment And Management Software; Artificial Intelligence And Machine Learning (AI And Ml) Enabled Software
• 2) By Hardware: Sensors And Measurement Devices; Intelligent Electronic Devices; Communication And Networking Equipment; Edge Computing Devices
• 3) By Services: Consulting And Advisory Services; Implementation And Integration Services; Maintenance And Support Services; Training And Capacity Building Services
• Companies Mentioned: Siemens AG; Accenture plc; International Business Machines Corporation; General Electric Compan; Oracle Corporation; Hitachi Energy Limited.; Schneider Electric Societe Anonyme; Honeywell International Inc.; ABB Limited; Eaton Corporatio.n Public Limited Company; Capgemini SE; Infosys Limited.; Schweitzer Engineering Laboratories; Incorporated; Bentley Systems; Incorporated; S&C Electric Company; Enel X S.r.l.; Energy Exemplar Pty Ltd.; Camlin Group Private Limited.; Uptake Technologies Inc.; AutoGrid Systems Inc.; Opus One Solutions Inc.; Cybirical Inc.
• Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain
• Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
• Time Series: Five years historic and ten years forecast.
• Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
• Data Segmentations: country and regional historic and forecast data, market share of competitors, market segments.
• Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
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