중국의 AI 기반 에너지 관리 소프트웨어 시장 : 시장 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the China AI-powered energy management software market size is projected to be USD 324.7 million in 2025, USD 386.5 million in 2026, and reach USD 985.3 million by 2031, growing at a CAGR of 20.58% from 2026 to 2031.

This report is Segmented by Component (Software, and Services), Deployment Mode (Cloud-Based, On-Premises, and Hybrid), Application (Energy Consumption and Demand Optimization, Asset Performance and Predictive Maintenance, and More), and End User (Utilities, Commercial Buildings, and More). The Market Forecasts are Provided in Terms of Value (USD).

China AI-powered Energy Management Software Market Trends and Insights

Rising Need For Real-Time Energy Optimization in Commercial and Industrial Facilities

Industrial and commercial energy users remain central to the China AI-powered Energy Management Software Market, as they face growing pressure to control consumption while meeting increasingly stringent efficiency and carbon-emission targets. The September 2025 implementation opinions from the National Development and Reform Commission and the National Energy Administration moved AI in energy from a broad policy theme to a defined application agenda across power, coal, and oil and gas systems. The May 2026 action plan then expanded on that direction by setting out 51 AI and energy application scenarios, providing enterprises and utilities with a clearer path for procurement and deployment. This policy structure matters because buyers now have stronger reasons to justify software spending that improves monitoring, control, and reporting across plants and buildings. It also helps explain why the China AI-powered Energy Management Software Market is seeing demand not only for core analytics tools, but also for implementation support and workflow integration tied to real operating decisions.

Integration of AI With Smart Grid and Distributed Energy Resources

The China AI-powered Energy Management Software Market is also gaining support from the grid side, where integrating renewables and balancing power have become more difficult to manage with static tools. China's renewables already accounted for 48% of installed power capacity, and that has raised the value of software that can forecast variable output and coordinate distributed resources more effectively. The 2026 national action plan specifically included smart grids, virtual power plants, and new energy forecasting among its priority application areas, indicating that grid-facing AI use cases are now part of formal state planning. That creates a stronger demand base for vendors whose products can work across grid operations, distributed assets, and enterprise energy systems. It also raises the bar in the China AI-powered Energy Management Software Market, as suppliers increasingly need credible local deployment experience and architectures that comply with utility operating rules.

High Integration Complexity with Legacy OT and IT Systems

Legacy control environments remain one of the clearest constraints on the China AI-powered Energy Management Software Market, as AI tools depend on stable, structured operational data. A 2025 peer-reviewed survey on IT and OT integration found that industrial digitalization depends on five linked domains: communication, IT-driven OT support, human centricity, security, and advanced industrial applications, and each one needs dedicated engineering effort. That helps explain why many projects still move slowly when sites rely on old PLCs, siloed supervisory systems, and custom interfaces built over many years. The issue is not only technical cost, because long integration cycles also delay the point at which buyers can see measurable savings or compliance gains. In the China AI-powered Energy Management Software Market, vendors that simplify data capture and system integration are likely to convert more opportunities than those that depend on full-site modernization before value can be demonstrated.

Other drivers and restraints analyzed in the detailed report include:

1. Increasing Demand for Automated Demand Response and Peak Load Management
2. Expansion of ESG Reporting and Carbon Accounting Workflows
3. Data Quality, Interoperability, and Sensor Fragmentation Issues

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Software accounted for 68.11% of revenue in 2025, making it the largest component of the China AI-powered Energy Management Software Market. This lead reflects the central role of platform licenses, software subscriptions, analytics modules, and control applications in enterprise deployments. Large utility contracts and multi-site industrial rollouts also tend to concentrate spending in core platforms first, since buyers usually need a system of record before they add advisory or optimization layers. The China AI-powered Energy Management Software Market, therefore, continued to lean on software as the basis for value creation, especially when monitoring, forecasting, and operational control needed to be integrated across multiple assets.

Services are projected to expand at a 21.22% CAGR from 2026 to 2031, which makes them the fastest-growing component over the forecast period. This rise shows that buyers are not stopping at software purchase, because many deployments require model tuning, implementation support, carbon accounting workflows, and ongoing optimization to produce usable results. The March 2026 implementation plan for energy-saving equipment called for the development of large-scale AI-based energy-saving and carbon-reducing models and for promoting intelligent device management services, which directly support a broader software adoption service layer. The shift is important because it gives vendors more room to grow recurring revenue from delivery and support, not just from initial software sales. It also explains why the China AI-powered Energy Management Software Market is becoming more dependent on execution capability and local service depth, rather than on product features alone.

Cloud-based deployment held 58.16% of the China AI-powered Energy Management Software Market share in 2025, making it the largest deployment mode. This position reflected the rapid expansion of domestic cloud infrastructure and the appeal of centralized access, faster updates, and wider data aggregation across distributed operations. The market benefited from this setup because many enterprises wanted to connect monitoring, analytics, and reporting without building fully separate software stacks at every site. Cloud deployment also suited newer use cases in commercial buildings and lighter industrial environments where buyers favored flexibility and lower upfront infrastructure needs.

Hybrid deployment is projected to expand at a 21.34% CAGR from 2026 to 2031, which makes it the fastest-growing architecture in the market. This pattern aligns with the stricter treatment of energy and operational data, especially for utilities and critical infrastructure operators that must keep sensitive information within approved jurisdictions. The December 2025 measures for data security management in the energy sector, effective July 1, 2026, strengthened the practical case for keeping some data and workloads local while still using cloud resources for aggregation and reporting. The China AI-powered Energy Management Software Market is therefore shifting toward deployment models that let enterprises keep OT-sensitive functions close to the asset while still using broader analytics and benchmarking across sites. That balance is likely to remain important as AI use cases expand across utilities, manufacturing, and data center environments.

Complete Report Scope:

• By Component
  • Software
  • Services
• By Deployment Mode
  • Cloud-Based
  • On-Premises
  • Hybrid
• By Application
  • Energy Consumption and Demand Optimization
  • Asset Performance and Predictive Maintenance
  • Smart Grid and Distributed Energy Resource (DER) Management
  • Renewable Energy Forecasting and Integration
  • Energy Trading, Pricing and Market Intelligence
• By End User
  • Utilities
  • Commercial Buildings
  • Industrial Facilities
  • Residential Buildings

List of Companies Covered in this Report:

1. Siemens AG
2. Schneider Electric SE
3. ABB Ltd.
4. Honeywell International Inc.
5. IBM Corporation
6. Johnson Controls International plc
7. Oracle Corporation
8. Microsoft Corporation
9. Amazon Web Services, Inc.
10. C3.AI, Inc.
11. Bidgely, Inc.
12. Grid4C Ltd.
13. Innowatts, Inc.
14. EnergyCAP, LLC
15. Enel X S.r.l.
16. Guoneng Rixin
17. State Grid Corporation of China
18. Dexma Sensors, S.L.
19. Rockwell Automation, Inc.
20. Envision Digital

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Rising Need for Real-Time Energy Optimization in Commercial and Industrial Facilities
  • 4.2.2 Integration of AI With Smart Grid and Distributed Energy Resources
  • 4.2.3 Increasing Demand for Automated Demand Response and Peak Load Management
  • 4.2.4 Expansion of ESG Reporting and Carbon Accounting Workflows
  • 4.2.5 Edge AI Adoption for Site-Level Energy Control and Fault Detection
  • 4.2.6 Growing Retrofit Demand From Aging Building and Industrial Infrastructure
• 4.3 Market Restraints
  • 4.3.1 High Integration Complexity With Legacy OT and IT Systems
  • 4.3.2 Data Quality, Interoperability, and Sensor Fragmentation Issues
  • 4.3.3 Cybersecurity and Data Sovereignty Concerns for Critical Energy Assets
  • 4.3.4 Payback Uncertainty in Small and Mid-Sized Sites With Limited Load Density
• 4.4 Impact of Macroeconomic Factors on the Market
• 4.5 Industry Value-Chain Analysis
• 4.6 Regulatory Landscape
• 4.7 Technological Outlook
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Bargaining Power of Buyers
  • 4.8.2 Bargaining Power of Suppliers
  • 4.8.3 Threat of New Entrants
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Component
  • 5.1.1 Software
  • 5.1.2 Services
• 5.2 By Deployment Mode
  • 5.2.1 Cloud-Based
  • 5.2.2 On-Premises
  • 5.2.3 Hybrid
• 5.3 By Application
  • 5.3.1 Energy Consumption and Demand Optimization
  • 5.3.2 Asset Performance and Predictive Maintenance
  • 5.3.3 Smart Grid and Distributed Energy Resource (DER) Management
  • 5.3.4 Renewable Energy Forecasting and Integration
  • 5.3.5 Energy Trading, Pricing and Market Intelligence
• 5.4 By End User
  • 5.4.1 Utilities
  • 5.4.2 Commercial Buildings
  • 5.4.3 Industrial Facilities
  • 5.4.4 Residential Buildings

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 Siemens AG
  • 6.4.2 Schneider Electric SE
  • 6.4.3 ABB Ltd.
  • 6.4.4 Honeywell International Inc.
  • 6.4.5 IBM Corporation
  • 6.4.6 Johnson Controls International plc
  • 6.4.7 Oracle Corporation
  • 6.4.8 Microsoft Corporation
  • 6.4.9 Amazon Web Services, Inc.
  • 6.4.10 C3.ai, Inc.
  • 6.4.11 Bidgely, Inc.
  • 6.4.12 Grid4C Ltd.
  • 6.4.13 Innowatts, Inc.
  • 6.4.14 EnergyCAP, LLC
  • 6.4.15 Enel X S.r.l.
  • 6.4.16 Guoneng Rixin
  • 6.4.17 State Grid Corporation of China
  • 6.4.18 Dexma Sensors, S.L.
  • 6.4.19 Rockwell Automation, Inc.
  • 6.4.20 Envision Digital

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment