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

According to Mordor Intelligence, the Middle East AI-powered energy management software market size is projected to expand from USD 220.12 million in 2025 and USD 260.13 million in 2026 to USD 670.13 million by 2031, registering a CAGR of 20.84% between 2026 and 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), End User (Commercial Buildings, Industrial Facilities, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Middle East AI-powered Energy Management Software Market Trends and Insights

Accelerated Smart Grid and Utility Digitization in Gulf Cooperation Council States

The Middle East AI-powered Energy Management Software Market is gaining direct support from utility digitization programs because grid operators now need software that can interpret high-frequency operational data rather than simply collect it. Saudi Arabia and the UAE are moving ahead with grid modernization agendas that place predictive analytics, automation, and digital operating tools closer to core utility processes rather than in pilot-stage experimentation. Abu Dhabi's Department of Energy signed an agreement with Google Cloud in October 2025 to apply AI and machine learning to grid management, demand forecasting, and predictive maintenance, which shows how grid digitization is translating into software procurement. The same shift is expanding AI's role from back-office reporting to real-time operational support across power plants, renewable assets, and distribution systems. As utilities build larger digital control environments, vendors that can integrate forecasting, maintenance, and energy optimization into a single operating layer are likely to gain an advantage in the Middle East AI-powered Energy Management Software Market. Procurement is also becoming broader across the GCC because software requirements now come from system visibility, operating resilience, and renewable balancing needs simultaneously.

Rising Demand for AI-Driven Load Forecasting in Commercial Buildings

The Middle East AI-powered Energy Management Software Market is seeing stronger demand from commercial buildings because energy use in offices, retail sites, hospitality assets, and mixed-use properties is increasingly tied to cooling loads, compliance targets, and utility cost management. Building owners are no longer looking only for monitoring dashboards, and they increasingly want forecasting tools that can help manage peak demand, schedule consumption, and improve operational control without replacing entire building systems. The UAE's push toward broader energy visibility and emissions accountability from 2026 is strengthening the commercial case for digital energy platforms that can organize site-level performance data into usable decisions. Schneider Electric expanded its EcoStruxure Building platform across 26 Brands For Less stores in the UAE in May 2026, demonstrating that software-led building optimization is moving beyond flagship properties into multi-site commercial portfolios. This matters for the Middle East AI-powered Energy Management Software Market because mid-market property operators usually need faster payback and less disruption than large custom projects can offer. As a result, vendors that provide modular forecasting, remote optimization, and easier integration with existing building systems are gaining a wider addressable base in the region.

Data Sovereignty Concerns Slowing Cloud Migration

The Middle East AI-powered Energy Management Software Market faces a real constraint due to data sovereignty, as many buyers handle sensitive grid data, plant telemetry, building controls, and infrastructure information. Saudi Arabia's localization rules have increased the cost of cross-border cloud design, and the broader GCC environment remains uneven because residency expectations differ by country and by application. The draft Global AI Hub Law in Saudi Arabia suggests that more flexible structures may emerge over time, but the current period still leaves vendors navigating compliance uncertainty when they architect regional offerings. This slows adoption because enterprises often choose hybrid or country-specific deployments that are legally safer but less efficient than a single regional cloud environment. Smaller specialists are affected more than incumbents because building sovereign-compliant infrastructure and certification layers requires capital, local presence, and longer sales support. The result is not a collapse in demand, but a slower transition path for fully cloud-native models in the Middle East AI-powered Energy Management Software Market.

Other drivers and restraints analyzed in the detailed report include:

1. Mandatory Energy Efficiency Targets Under National Decarbonization Programs
2. Expansion of Cloud-Native Enterprise Energy Platforms
3. Integration Complexity With Legacy Building and Industrial Control Systems

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

Segment Analysis

Software held 68.22% of the Middle East AI-powered Energy Management Software Market share in 2025, which confirms that buyers still place the greatest value on platforms that can centralize analytics, forecasting, optimization, and control workflows. The leading role of software also reflects the region's preference for scalable platforms that can serve large utilities, commercial portfolios, and industrial networks without being confined to a single site deployment. In the Middle East AI-powered energy management software industry, platform breadth matters because customers increasingly want one operating layer that can support demand management, maintenance planning, renewable balancing, and reporting requirements at the same time. This explains why software demand remains strongest where procurement decisions are tied to enterprise licenses, integrated dashboards, and long-term digital transformation programs rather than narrow application tools. It also means that product depth, ease of integration, and compliance fit are becoming as important as core analytics performance when buyers evaluate suppliers.

Services is projected to expand at a 20.91% CAGR through 2031, which shows that many deployments still need outside support for integration, model tuning, change management, and ongoing optimization. This growth pattern suggests the Middle East AI-powered Energy Management Software Market is moving beyond first-stage software rollout and toward a longer cycle of recalibration, site expansion, and operational support. A peer-reviewed study validated a multi-agent framework for automating building load forecasting model development, which points to the kind of service-intensive use cases vendors can package around software subscriptions in coming years. The same logic is visible in enterprise contracts, where buyers increasingly value expert support that helps internal teams move from data collection to measurable operational improvement. C3.AI's June 2026 expansion of its agreement with Shell, including AI agent-based root cause analysis across more than 13,000 pieces of equipment, illustrates how long-term service engagement can deepen once the platform is already embedded.

Cloud-based deployment accounted for 58.14% of the Middle East AI-powered Energy Management Software Market in 2025, indicating that buyers still favor scalability, update speed, and lower upfront infrastructure costs where regulation allows. Cloud adoption has been strongest where organizations manage multiple assets and need centralized visibility across large operating footprints. In the Middle East AI-powered energy management software industry, this model is attractive because it helps standardize performance tracking across buildings, grids, industrial sites, and energy-intensive service environments. It also aligns with procurement preferences among enterprises that want subscription models, remote management capability, and quicker platform upgrades than older on-premises environments can usually support. At the same time, cloud leadership in 2025 does not mean regulation is no longer a barrier, because deployment choices still depend heavily on where operational data sits and how sensitive that data is deemed to be.

Hybrid deployment is projected to expand at a 21.02% CAGR through 2031, underscoring how the region is settling on a middle path between cloud efficiency and sovereignty requirements. The appeal of hybrid design lies in its ability to keep sensitive telemetry close to the asset while still enabling broader analytics, optimization, and portfolio reporting across a wider enterprise. The February 2026 Phaidra AI pilot involving the UAE Ministry of Energy and Infrastructure, Khazna Data Centers, and Agility showed how energy optimization can be advanced within a compliant local operating structure rather than through a purely offshore cloud setup. This architecture is becoming increasingly strategically important in the Middle East AI-powered Energy Management Software Market, as buyers increasingly seek flexibility without incurring unnecessary regulatory exposure. Vendors that built hybrid capability into the core product are therefore better placed than those now trying to retrofit limited on-premises features onto a cloud-first offering.

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
• By Geography
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Rest of Middle East

List of Companies Covered in this Report:

1. Schneider Electric SE
2. Siemens Aktiengesellschaft
3. Honeywell International Inc.
4. ABB Ltd
5. Johnson Controls International plc
6. IBM Corporation
7. Cisco Systems, Inc.
8. Oracle Corporation
9. SAP SE
10. Eaton Corporation plc
11. Rockwell Automation, Inc.
12. Emerson Electric Co.
13. Enel X S.r.l.
14. GridPoint, Inc.
15. Bidgely, Inc.
16. C3.AI, Inc.
17. Verdigris Technologies, Inc.
18. eSight Energy Ltd.
19. Spacewell International N.V.
20. BrainBox AI Inc.

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 Accelerated Smart Grid and Utility Digitization in Gulf Cooperation Council States
  • 4.2.2 Rising Demand For AI-Driven Load Forecasting in Commercial Buildings
  • 4.2.3 Mandatory Energy Efficiency Targets Under National Decarbonization Programs
  • 4.2.4 Expansion of Cloud-Native Enterprise Energy Platforms
  • 4.2.5 Increasing Need For Predictive Maintenance Across Energy-Intensive Assets
  • 4.2.6 Greater Deployment of Submetering and IoT Sensor Networks in Large Facilities
• 4.3 Market Restraints
  • 4.3.1 Data Sovereignty Concerns Slowing Cloud Migration
  • 4.3.2 Integration Complexity With Legacy Building and Industrial Control Systems
  • 4.3.3 Limited AI Skills and Implementation Capacity Among End Users
  • 4.3.4 Fragmented Utility Tariff and Regulatory Structures Across The Region
• 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
• 5.5 By Geography
  • 5.5.1 Saudi Arabia
  • 5.5.2 United Arab Emirates
  • 5.5.3 Qatar
  • 5.5.4 Rest of Middle East

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 Schneider Electric SE
  • 6.4.2 Siemens Aktiengesellschaft
  • 6.4.3 Honeywell International Inc.
  • 6.4.4 ABB Ltd
  • 6.4.5 Johnson Controls International plc
  • 6.4.6 IBM Corporation
  • 6.4.7 Cisco Systems, Inc.
  • 6.4.8 Oracle Corporation
  • 6.4.9 SAP SE
  • 6.4.10 Eaton Corporation plc
  • 6.4.11 Rockwell Automation, Inc.
  • 6.4.12 Emerson Electric Co.
  • 6.4.13 Enel X S.r.l.
  • 6.4.14 GridPoint, Inc.
  • 6.4.15 Bidgely, Inc.
  • 6.4.16 C3.ai, Inc.
  • 6.4.17 Verdigris Technologies, Inc.
  • 6.4.18 eSight Energy Ltd.
  • 6.4.19 Spacewell International N.V.
  • 6.4.20 BrainBox AI Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment