The artificial intelligence (AI) in electric vehicle (EV) charging market size is expected to see exponential growth in the next few years. It will grow to $6.01 billion in 2030 at a compound annual growth rate (CAGR) of 25.8%. The growth in the forecast period can be attributed to expansion of dc fast charging networks, rising demand for fleet electrification, increasing grid modernization efforts, growth in renewable energy-based ev charging, advances in ai-enabled predictive maintenance. Major trends in the forecast period include predictive charging optimization, AI-driven grid interaction enhancement, adaptive charging user experience personalization, real-time charger health diagnostics, dynamic load balancing algorithms.
Rising consumer interest in sustainable and low-emission transportation is expected to drive growth in the artificial intelligence (AI) in electric vehicle (EV) charging market in the coming years. Sustainable and low-emission transportation focuses on reducing greenhouse gas emissions and reliance on fossil fuels through vehicle electrification, integration of renewable energy, and efficiency improvements. This growing demand is fueled by environmental awareness and cost-saving considerations, encouraging broader adoption of electric vehicles and supporting charging infrastructure. AI in EV charging facilitates this transition by enabling smart, efficient, and environmentally friendly charging solutions. For example, in January 2023, the U.S. National Blueprint for Transportation Decarbonization reported that decarbonizing the transportation sector by 2050 is achievable through widespread EV adoption, clean fuels, and intelligent charging infrastructure. Consequently, increasing consumer demand for sustainable transport is expected to propel the AI in EV charging market.
Leading companies in this market are focusing on advanced solutions such as AI-powered fast chargers that enhance the EV charging experience through interactivity and personalization. AI-enabled fast chargers optimize charging speed, manage energy distribution, and improve reliability. For instance, in October 2025, Electric Era, a U.S.-based EV charging company, introduced its RetailEdge EV charging platform featuring AI-powered fast chargers. These chargers integrate the HaloAI voice-activated concierge, providing personalized promotions, answering questions, and even offering entertainment, while combining ultra-fast 400 kW charging with retail features such as loyalty programs, membership validation, and direct commerce via touchscreen. Battery-backed technology improves reliability, reduces operating costs by up to 70%, and allows rapid deployment without major grid upgrades. This innovation extends retail experiences into parking lots, increasing customer satisfaction, creating new revenue streams for retailers, and supporting the transition to EVs with an efficient, enjoyable charging process.
In November 2023, OVO Energy Ltd., a UK-based energy company, acquired Bonnet App Ltd. for an undisclosed amount. The acquisition enables OVO Energy to expand its public EV charging network and integrate Bonnet’s app with its smart home charging products, promoting wider EV adoption and supporting sustainable mobility. Bonnet App Ltd., based in the U.K., developed a widely used EV charging application.
Major companies operating in the artificial intelligence (AI) in electric vehicle (EV) charging market are Amazon.com Inc., TotalEnergies SE, Microsoft Corporation, ENGIE SA, BYD Co. Ltd., Siemens AG, Iberdrola S.A., Panasonic Holdings Corporation, Intel Corporation, Schneider Electric SE, Honeywell International Inc., Qualcomm Incorporated, ABB Ltd, Delta Electronics Inc., Vattenfall AB, OVO Energy Ltd., Hitachi Energy Ltd., ChargePoint Holdings Inc., GRIDSERVE Sustainable Energy Limited, Driivz Ltd.
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.
Tariffs are influencing the AI in EV charging market by increasing the cost of importing hardware components such as sensors, communication modules, and AI-enabled charging units, leading to higher installation and system deployment expenses. These impacts are more prominent in hardware-intensive segments like DC fast charging and public charging networks, especially across Asia-Pacific and Europe, where cross-border equipment sourcing is common. However, tariffs are also encouraging domestic manufacturing, stimulating localized production of AI-enabled chargers and reducing long-term dependence on imports. This shift is gradually creating opportunities for innovation, improved supply chain resilience, and cost competitiveness within key markets.
The artificial intelligence (AI) in electric vehicle (EV) charging market research report is one of a series of new reports that provides artificial intelligence (AI) in electric vehicle (EV) charging market statistics, including the artificial intelligence (AI) in electric vehicle (EV) charging industry global market size, regional shares, competitors with the artificial intelligence (AI) in electric vehicle (EV) charging market share, detailed artificial intelligence (AI) in electric vehicle (EV) charging market segments, market trends, and opportunities, and any further data you may need to thrive in the artificial intelligence (AI) in electric vehicle (EV) charging industry. This artificial intelligence (AI) in electric vehicle (EV) charging market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.
Artificial Intelligence (AI) in electric vehicle (EV) charging refers to the use of advanced algorithms and machine learning to optimize charging operations, energy distribution, and grid interaction. AI supports smart load management by predicting charging demand, efficiently scheduling sessions, and reducing energy costs. It also improves user experience through adaptive charging recommendations and predictive maintenance, helping enhance the efficiency, reliability, and sustainability of EV charging networks.
The main components of AI in EV charging include software, hardware, and services. AI-enabled EV charging software supports smart scheduling, real-time monitoring, predictive maintenance, and user interface management. The various charging types include alternating current (AC) charging, direct current (DC) fast charging, and wireless charging. These systems are deployed through on-premises and cloud-based models and are used for residential, commercial, public, and fleet charging applications. End users include private electric vehicle owners, commercial fleets, charging network operators, utilities, and other users.North America was the largest region in the artificial intelligence (AI) in electric vehicle (EV) charging market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI) in electric vehicle (EV) charging market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence (AI) in electric vehicle (EV) charging market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
The artificial intelligence (AI) in the electric vehicle (EV) charging market consists of revenues earned by entities by providing services such as predictive maintenance services, energy load forecasting, cloud analytics and monitoring, and charging network optimization. The market value includes the value of related goods sold by the service provider or contained within the service offering. The artificial intelligence (AI) in the electric vehicle (EV) charging market also includes sales of AI-powered energy management systems, smart charging algorithms and controllers, vehicle-to-grid (V2G) integration devices, and predictive maintenance monitoring tools. 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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Table of Contents
Executive Summary
Artificial Intelligence (AI) In Electric Vehicle (EV) Charging Market Global Report 2026 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses artificial intelligence (ai) in electric vehicle (ev) charging 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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Description
Where is the largest and fastest growing market for artificial intelligence (ai) in electric vehicle (ev) charging? 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 artificial intelligence (ai) in electric vehicle (ev) charging market global report 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; Services2) By Charging Type: Alternating Current (AC) Charging; Direct Current (DC) Fast Charging; Wireless Charging
3) By Deployment Mode: On-Premises; Cloud
4) By Application: Residential Charging; Commercial Charging; Public Charging; Fleet Charging
5) By End User: Private Electric Vehicle Owners; Commercial Fleets; Charging Network Operators; Utilities; Other End-Users
Subsegments::
1) By Software: AI-Based Energy Management Software; Predictive Maintenance Software; Smart Charging Scheduling Platforms; Fleet Management And Optimization Software2) By Hardware: AI-Enabled EV Chargers; Sensors And IoT Devices For Charging Stations; Communication Modules; Edge Computing Devices For AI Processing
3) By Services: Installation And Deployment Services; Maintenance And Support Services; Data Analytics And Consulting Services; Remote Monitoring And Optimization Services
Companies Mentioned: Amazon.com Inc.; TotalEnergies SE; Microsoft Corporation; ENGIE SA; BYD Co. Ltd.; Siemens AG; Iberdrola S.A.; Panasonic Holdings Corporation; Intel Corporation; Schneider Electric SE; Honeywell International Inc.; Qualcomm Incorporated; ABB Ltd; Delta Electronics Inc.; Vattenfall AB; OVO Energy Ltd.; Hitachi Energy Ltd.; ChargePoint Holdings Inc.; GRIDSERVE Sustainable Energy Limited; Driivz Ltd.
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 Segmentation: 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.
Delivery Format: Word, PDF or Interactive Report + Excel Dashboard
Added Benefits:
- Bi-Annual Data Update
- Customisation
- Expert Consultant Support
Companies Mentioned
The companies featured in this Artificial Intelligence (AI) in Electric Vehicle (EV) Charging market report include:- Amazon.com Inc.
- TotalEnergies SE
- Microsoft Corporation
- ENGIE SA
- BYD Co. Ltd.
- Siemens AG
- Iberdrola S.A.
- Panasonic Holdings Corporation
- Intel Corporation
- Schneider Electric SE
- Honeywell International Inc.
- Qualcomm Incorporated
- ABB Ltd
- Delta Electronics Inc.
- Vattenfall AB
- OVO Energy Ltd.
- Hitachi Energy Ltd.
- ChargePoint Holdings Inc.
- GRIDSERVE Sustainable Energy Limited
- Driivz Ltd.
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 250 |
| Published | January 2026 |
| Forecast Period | 2026 - 2030 |
| Estimated Market Value ( USD | $ 2.4 Billion |
| Forecasted Market Value ( USD | $ 6.01 Billion |
| Compound Annual Growth Rate | 25.8% |
| Regions Covered | Global |
| No. of Companies Mentioned | 20 |


