US Smart Grid Data Analytics Market 2026 – 2035

Reports Description

As per the US Smart Grid Data Analytics Market analysis conducted by the CMI team, the US smart grid data analytics market is expected to record a CAGR of 11.23% from 2025 to 2035. In 2026, the market size was USD 2.97 Billion. By 2035, the valuation is anticipated to reach USD 7.73 Billion.

Overview

The rising volumes of advanced metering infrastructure (AMI) data, faster deployment of the distributed energy resources (DERs), and expanding EV charging networks are compelling the grid operators regarding adoption of cloud-native analytics that convert petabytes into actionable, timely insights.

AI and ML do underpin outage prediction, load forecasting, and DER orchestration, thereby giving the utilities tools for shifting to predictive from reactive grid management. The vendors who are looking forward to bridging legacy SCADA environments with modern-day cloud services are witnessing a robust demand, particularly in the markets with strict cybersecurity mandates. Also, decarbonization targets are calling for real-time carbon-intensity reporting, thereby creating demand for sophisticated analytics.

Market Highlights

• By component, the solutions segment held 44.67% of the market share in 2025.

• By component, the services segment is expected to witness the fastest CAGR of 12.37% during the forecast period.

• By deployment, the on-premises segment dominated with 39.76% of the market share in 2025.

• By deployment, the cloud-based segment is expected to witness the fastest CAGR of 11.47% during the forecast period.

• By application, the advanced metering infrastructure analysis segment is expected to witness the fastest CAGR of 11.27% during the forecast period.

• By end-use, the large enterprises segment dominated with 47.47% of the market share in 2025.

• By end-use, the small & medium enterprises are expected to witness the fastest CAGR of 10.45% during the forecast period.

Key Trends & Drivers

• Technological Advancements in Metering Infrastructure

Smart meters are abreast with digital communication technology, which provides real-time data regarding electricity consumption, voltage level, and power quality with time, which lets both – consumers and providers manage and monitor usage of energy effectively. This collection of real-time data is important for deploying smart grid analytics, which does transform raw data into insights meant for improving grid efficiency, reliability, and sustainability. The accurate data that AMI provides lets utilities actively address the issues even before they arise, thereby lessening downtime and saving on the operational costs on the whole.

What’s trending in the US Smart Grid Data Analytics Market?

Cloud deployment is accelerating. Research states that it is holding over 60% of the market share as the utilities are prioritizing cost-effective, scalable, and secure (emphasizing on cybersecurity) platforms over the on-premise infrastructure. The AI-powered analytics are turning out to be necessary regarding predictive maintenance and real-time, autonomous decision-making, which does improve grid reliability and curtail operational costs. Also, proliferation of IoT sensors and smart meters is facilitating monitoring of grid performance, improving billing precision, and managing load efficiency.

What would be Business Impact of the US Tariffs on the US Smart Grid Data Analytics Market?

The US tariffs, especially on the Chinese components, are fuelling ~6% of the cost increase in the grid modernization projects, thereby resulting in smart grid data analytics providers incurring higher operational expenses. Tariffs on sensors, IoT devices, and transformers raise the capital expenditure (CapEx) pertaining to smart grid infrastructure. Providers of EaaS (Energy-as-a-Service) and analytics are likely to witness compressed margins as they absorb the costs in place of passing them on to consumers with immediate effect. The manufacturers are also diversifying, thereby decreasing sourcing from Asia to dependency on China.

Key Threats

Several consumers are not aware of the advantages offered by smart grid technologies. Also, small-size utility companies, particularly in the developing regions, are likely to lack knowledge as well as resources to utilize data analytics and advanced metering infrastructure efficiently. Plus, perceived complexity as well as the cost involved in the deployment of AMI systems could hamper the growth of the US smart grid data analytics market.

Besides, hybrid models enable a gradual change to cloud technologies, thereby letting utilities modernize infrastructure incrementally without any major investments upfront. As such, this lessens operational and monetary risks linked with full-scale cloud operation.

Opportunities

The hybrid deployment model does present a substantial opportunity for the US smart grid data analytics market. This approach does combine the finest aspects of cloud-based and on-premise solutions, wherein scalable and flexible options for optimization of grid operations are offered without compromising on control and security. The utilities, with the help of a hybrid model, can manage critical infrastructure and sensitive data on-premises, thereby assuring compliance with the regulatory standards and maintenance of higher levels of security.

Category Wise Insights

By Component

• Solutions

The solutions segment dominated the US smart grid data analytics market in 2025 and the scenario is expected to remain unchanged during the forecast period. This is due to several advantages provided, such as improved grid reliability, regulatory compliance, and enhanced security. Data analysis in real-time allows utilities to optimize distribution of energy, thereby effectively helping in balancing demand and supply. It also ascertains compliance with the regulatory standards for maintaining authenticity and reliability of solutions provided. Advanced analytics implies a proactive approach regarding safeguarding a system from cyber threats.

• Services

With modernization of grids, the service providers help in the installation, configuration, and integration of new hardware and software with legacy systems. They do offer skills in AI, ML, and cloud technologies required for sophisticated analytics (such as predictive maintenance) that several utilities are incapable of developing in-house. Services do handle the large-scale influx of data from the smart meters, wherein they perform tasks such as data modelling, cleansing, and building the digital twins. Security services, with raised connectivity, turn out to be critical in order to protect the grid, thereby driving the demand for ongoing monitoring and risk assessments.

• Professional

Large enterprises and utilities are equipped with resources for implementing integrated, complex analytics platforms from mega players such as SAS, IBM, and Oracle for handling huge data streams. Using analytics for predictive maintenance so as to avert failures, reduce the operating costs, and optimize balancing of load improves grid reliability on the whole. Analytics tools aid utilities in adhering to mandates for cybersecurity, grid resiliency, and demand response programs. Big data analytics do identify the unusual patterns pertaining to the protection of the grid from cyber threats.

• Managed

Cloud/hybrid managed services make provisions for powerful computing for massive grid data without large-scale investments in utility hardware, thereby paving the way for on-demand, flexible resources. The utilities can implement advanced analytics for monitoring, DER management, and EV charging in real-time without going through the lengthy procedure of procurement. Managed service providers also offer the skilled workforce required for interpreting complicated data and managing ML/AI tools.

By Deployment

• Cloud-based

The cloud-based segment is expected to witness the fastest CAGR in the US smart grid data analytics market during the forecast period. This is credited to high scalability, cost-effectiveness, and accurate outcomes through advanced analytics provided by cloud-based deployment. It also facilitates real-time data analysis, which enhances decision-making and improves efficiency. Moreover, advancements in smart grid technologies do generate large quantities of data that need effective analysis. As such, data analysis accelerates the growth of cloud-based deployment.

• On-premises

The utilities do maintain 100% control over sensitive operational data such as AMI, SCADA, and the like, thereby reducing the breach risks and complying with NERC CIP, which is vital for grid integrity. On-site deployment ascertains minimal delay pertaining to real-time decisions that are necessary for detection of faults, grid stability, and automated responses. It also acts as one of the secure bases, wherein it allows for gradual deployment of the cloud for various less sensitive tasks such as customer analytics while keeping the on-premise operations.

• Hybrid

Hybrid setups do offer the cloud’s elasticity, meant for handling massive data influxes from DERs (Distributed Energy Resources) and smart meters without the large-scale upfront costs involved in constructing big data centers. Hybrid models, through distribution of computing across diverse environments, do increase fault tolerance as well as recovery times, thereby rendering the grid more robust. Hybrid approaches make provisions for realistic pathways for utilities for modernizing, integrating the novel cloud-native analytics with infrastructure that exists, thereby facilitating 5G integration and grid-edge analytics.

By Application

• Advanced Metering Infrastructure Analysis

The advanced metering infrastructure analysis segment is expected to witness a significant rate of growth in the US smart grid data analytics market during the forecast period. Advanced metering is transforming the market owing to rising demand for anomaly detection, load forecasting, predictive maintenance, and response optimization. Advanced metering infrastructure (AMI) data does provide accurate information regarding consumption of energy as well as its patterns. The operators, by conducting analysis of these patterns, can obtain valuable insights – like peak time for demand and the way supply should be optimized.

• Demand Response & Grid Optimization Analysis

Demand response (DR) & grid optimization analysis is driving the US smart grid analytics market by using data for balancing demand/supply, integrating renewables, averting outages, cutting costs, and enhancing efficiency, thereby generating demand for various analytics tools that predict peaks, manage complex grid dynamics, and facilitate dynamic pricing for a more cost-effective, resilient grid. The segment this paves the way for actionable insights for lessening reliance on the costly peaker plants.

By End-use

• Public Sector

The governments are providing sizable budgets as well as incentives in order to modernize aging power grids, thereby directly funding the deployments of large-scale smart grids, which include advanced metering infrastructure (AMI). The policies that are pushing for reduction of carbon footprints are adopting smart grid tech as well as analytics for meeting the targets. Public sector backing does support grid sensors’ and smart meters’ installation, thereby generating huge datasets fuelling demand for various analytics solutions.

• Large Enterprise

The large enterprise segment held the largest market share in 2025 and the status quo is expected to remain unchanged during the forecast period. This is credited to the fact that large enterprises have sizable monetary capabilities, which, in turn, let them invest handsomely in advanced technologies for supporting smart grid analytics. They do offer a skilled manual workforce for managing and operating complex grid networks and optimizing the operations in an effective manner. They also get involved in strategic alliances and partnerships with the other firms.

• Small & Medium Enterprises

The small & medium enterprises segment is expected to witness the fastest CAGR during the forecast period. This is due to the government’s support toward start-ups. Moreover, the cloud-based solutions are turning out to be affordable, which does make SMEs buy them and implement the data analytics solutions into business models.

Report Scope

Key Developments

The US smart grid data analytics market is witnessing a significant organic and inorganic expansion. Some of the key developments include –

• In July 2024, AES Ohio inked an agreement with Landis+Gyr as one of its technology providers for a grid upgrade project that is aimed at enhancing the efficiency of the power distribution system as well as customer services. The utility is poised to install around 500,000 smart meters and the Gridstream Connect IoT platform using cellular networks and RF Mesh IP.

• In June 2024, Schneider Electric announced that it had launched Villaya Flex, its microgrid solution. It has been designed for communities, thereby enabling a journey toward independent, decarbonized electricity while addressing the modern-day energy challenges.

Leading Players

The US smart grid data analytics market is highly competitive, with a large number of service providers. Some of the key players in the market include:

• Siemens AG
• Oracle Corporation
• GE Vernova
• Itron Inc.
• IBM Corporation
• Landis+Gyr
• Schneider Electric
• SAS Institute
• Honeywell
• ABB Ltd.
• Others

These firms apply a plethora of strategies to enter the market, including innovations and mergers and acquisitions, as well as collaboration. The US smart grid data analytics market is shaped by the presence of diversified players that compete based on product innovation, vertical integration, and cost efficiency.

The US Smart Grid Data Analytics Market is segmented as follows:

By Component

• Solutions
• Services
• Professional
• Managed

By Deployment

• Cloud-based
• On-premises
• Hybrid

By Application

• Advanced Metering Infrastructure Analysis
• Demand Response & Grid Optimization Analysis

By End-use

• Public Sector
• Large Enterprise
• Small & Medium Enterprises