Applied AI in Energy and Utilities Market Size, Share, and Trends 2026 to 2035

Applied AI in Energy and Utilities Market (By Component: Software, Services, Hardware; By Deployment Mode: Cloud, On premises, Hybrid; By Application: Renewable Energy Forecasting, Grid Optimization, Demand Forecasting, Predictive Maintenance, Outage Management, Energy Trading, Customer Analytics, Fraud Detection; By End Use: Power Generation, Transmission, Distribution, Retail Energy, Water and Wastewater Utilities; By Technology: Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Digital Twin, Predictive Analytics, Reinforcement Learning) - Global Industry Analysis, Size, Trends, Leading Companies, Regional Outlook, and Forecast 2026 to 2035

Last Updated : 20 Mar 2026  |  Report Code : 8190  |  Category : ICT   |  Format : PDF / PPT / Excel

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology 

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on AI in Energy and Utilities Market 

5.1. COVID-19 Landscape: AI in Energy and Utilities Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global AI in Energy and Utilities Market, By Component

8.1. AI in Energy and Utilities Market, by Component

8.1.1. Software

8.1.1.1. Market Revenue and Forecast

8.1.2. Services

8.1.2.1. Market Revenue and Forecast

8.1.3. Hardware

8.1.3.1. Market Revenue and Forecast

Chapter 9. Global AI in Energy and Utilities Market, By Deployment Mode

9.1. AI in Energy and Utilities Market, by Deployment Mode

9.1.1. Cloud

9.1.1.1. Market Revenue and Forecast

9.1.2. On premises

9.1.2.1. Market Revenue and Forecast

9.1.3. Hybrid

9.1.3.1. Market Revenue and Forecast

Chapter 10. Global AI in Energy and Utilities Market, By Application 

10.1. AI in Energy and Utilities Market, by Application

10.1.1. Renewable Energy Forecasting

10.1.1.1. Market Revenue and Forecast

10.1.2. Grid Optimization

10.1.2.1. Market Revenue and Forecast

10.1.3. Demand Forecasting

10.1.3.1. Market Revenue and Forecast

10.1.4. Predictive Maintenance

10.1.4.1. Market Revenue and Forecast

10.1.5. Outage Management

10.1.5.1. Market Revenue and Forecast

10.1.6. Energy Trading

10.1.6.1. Market Revenue and Forecast

10.1.7. Customer Analytics

10.1.7.1. Market Revenue and Forecast

10.1.8. Fraud Detection

10.1.8.1. Market Revenue and Forecast

Chapter 11. Global AI in Energy and Utilities Market, By End Use

11.1. AI in Energy and Utilities Market, by End Use

11.1.1. Power Generation

11.1.1.1. Market Revenue and Forecast

11.1.2. Transmission

11.1.2.1. Market Revenue and Forecast

11.1.3. Distribution

11.1.3.1. Market Revenue and Forecast

11.1.4. Retail Energy

11.1.4.1. Market Revenue and Forecast

11.1.5. Water and Wastewater Utilities

11.1.5.1. Market Revenue and Forecast

Chapter 12. Global AI in Energy and Utilities Market, By Technology

12.1. AI in Energy and Utilities Market, by Technology

12.1.1. Machine Learning

12.1.1.1. Market Revenue and Forecast

12.1.2. Deep Learning

12.1.2.1. Market Revenue and Forecast

12.1.3. Natural Language Processing

12.1.3.1. Market Revenue and Forecast

12.1.4. Computer Vision

12.1.4.1. Market Revenue and Forecast

12.1.5. Digital Twin

12.1.5.1. Market Revenue and Forecast

Chapter 13. Global AI in Energy and Utilities Market, Regional Estimates and Trend Forecast

13.1. North America

13.1.1. Market Revenue and Forecast, by Component

13.1.2. Market Revenue and Forecast, by Deployment Mode

13.1.3. Market Revenue and Forecast, by Application

13.1.4. Market Revenue and Forecast, by End Use

13.1.5. Market Revenue and Forecast, by Technology

13.1.6. U.S.

13.1.6.1. Market Revenue and Forecast, by Component

13.1.6.2. Market Revenue and Forecast, by Deployment Mode

13.1.6.3. Market Revenue and Forecast, by Application

13.1.6.4. Market Revenue and Forecast, by End Use

13.1.6.5. Market Revenue and Forecast, by Technology  

13.1.7. Rest of North America

13.1.7.1. Market Revenue and Forecast, by Component

13.1.7.2. Market Revenue and Forecast, by Deployment Mode

13.1.7.3. Market Revenue and Forecast, by Application

13.1.7.4. Market Revenue and Forecast, by End Use

13.1.7.5. Market Revenue and Forecast, by Technology

13.2. Europe

13.2.1. Market Revenue and Forecast, by Component

13.2.2. Market Revenue and Forecast, by Deployment Mode

13.2.3. Market Revenue and Forecast, by Application

13.2.4. Market Revenue and Forecast, by End Use  

13.2.5. Market Revenue and Forecast, by Technology  

13.2.6. UK

13.2.6.1. Market Revenue and Forecast, by Component

13.2.6.2. Market Revenue and Forecast, by Deployment Mode

13.2.6.3. Market Revenue and Forecast, by Application

13.2.7. Market Revenue and Forecast, by End Use  

13.2.8. Market Revenue and Forecast, by Technology  

13.2.9. Germany

13.2.9.1. Market Revenue and Forecast, by Component

13.2.9.2. Market Revenue and Forecast, by Deployment Mode

13.2.9.3. Market Revenue and Forecast, by Application

13.2.10. Market Revenue and Forecast, by End Use

13.2.11. Market Revenue and Forecast, by Technology

13.2.12. France

13.2.12.1. Market Revenue and Forecast, by Component

13.2.12.2. Market Revenue and Forecast, by Deployment Mode

13.2.12.3. Market Revenue and Forecast, by Application

13.2.12.4. Market Revenue and Forecast, by End Use

13.2.13. Market Revenue and Forecast, by Technology

13.2.14. Rest of Europe

13.2.14.1. Market Revenue and Forecast, by Component

13.2.14.2. Market Revenue and Forecast, by Deployment Mode

13.2.14.3. Market Revenue and Forecast, by Application

13.2.14.4. Market Revenue and Forecast, by End Use

13.2.15. Market Revenue and Forecast, by Technology

13.3. APAC

13.3.1. Market Revenue and Forecast, by Component

13.3.2. Market Revenue and Forecast, by Deployment Mode

13.3.3. Market Revenue and Forecast, by Application

13.3.4. Market Revenue and Forecast, by End Use

13.3.5. Market Revenue and Forecast, by Technology

13.3.6. India

13.3.6.1. Market Revenue and Forecast, by Component

13.3.6.2. Market Revenue and Forecast, by Deployment Mode

13.3.6.3. Market Revenue and Forecast, by Application

13.3.6.4. Market Revenue and Forecast, by End Use

13.3.7. Market Revenue and Forecast, by Technology

13.3.8. China

13.3.8.1. Market Revenue and Forecast, by Component

13.3.8.2. Market Revenue and Forecast, by Deployment Mode

13.3.8.3. Market Revenue and Forecast, by Application

13.3.8.4. Market Revenue and Forecast, by End Use

13.3.9. Market Revenue and Forecast, by Technology

13.3.10. Japan

13.3.10.1. Market Revenue and Forecast, by Component

13.3.10.2. Market Revenue and Forecast, by Deployment Mode

13.3.10.3. Market Revenue and Forecast, by Application

13.3.10.4. Market Revenue and Forecast, by End Use

13.3.10.5. Market Revenue and Forecast, by Technology

13.3.11. Rest of APAC

13.3.11.1. Market Revenue and Forecast, by Component

13.3.11.2. Market Revenue and Forecast, by Deployment Mode

13.3.11.3. Market Revenue and Forecast, by Application

13.3.11.4. Market Revenue and Forecast, by End Use

13.3.11.5. Market Revenue and Forecast, by Technology

13.4. MEA

13.4.1. Market Revenue and Forecast, by Component

13.4.2. Market Revenue and Forecast, by Deployment Mode

13.4.3. Market Revenue and Forecast, by Application

13.4.4. Market Revenue and Forecast, by End Use

13.4.5. Market Revenue and Forecast, by Technology

13.4.6. GCC

13.4.6.1. Market Revenue and Forecast, by Component

13.4.6.2. Market Revenue and Forecast, by Deployment Mode

13.4.6.3. Market Revenue and Forecast, by Application

13.4.6.4. Market Revenue and Forecast, by End Use

13.4.7. Market Revenue and Forecast, by Technology

13.4.8. North Africa

13.4.8.1. Market Revenue and Forecast, by Component

13.4.8.2. Market Revenue and Forecast, by Deployment Mode

13.4.8.3. Market Revenue and Forecast, by Application

13.4.8.4. Market Revenue and Forecast, by End Use

13.4.9. Market Revenue and Forecast, by Technology

13.4.10. South Africa

13.4.10.1. Market Revenue and Forecast, by Component

13.4.10.2. Market Revenue and Forecast, by Deployment Mode

13.4.10.3. Market Revenue and Forecast, by Application

13.4.10.4. Market Revenue and Forecast, by End Use

13.4.10.5. Market Revenue and Forecast, by Technology

13.4.11. Rest of MEA

13.4.11.1. Market Revenue and Forecast, by Component

13.4.11.2. Market Revenue and Forecast, by Deployment Mode

13.4.11.3. Market Revenue and Forecast, by Application

13.4.11.4. Market Revenue and Forecast, by End Use

13.4.11.5. Market Revenue and Forecast, by Technology

13.5. Latin America

13.5.1. Market Revenue and Forecast, by Component

13.5.2. Market Revenue and Forecast, by Deployment Mode

13.5.3. Market Revenue and Forecast, by Application

13.5.4. Market Revenue and Forecast, by End Use

13.5.5. Market Revenue and Forecast, by Technology

13.5.6. Brazil

13.5.6.1. Market Revenue and Forecast, by Component

13.5.6.2. Market Revenue and Forecast, by Deployment Mode

13.5.6.3. Market Revenue and Forecast, by Application

13.5.6.4. Market Revenue and Forecast, by End Use

13.5.7. Market Revenue and Forecast, by Technology

13.5.8. Rest of LATAM

13.5.8.1. Market Revenue and Forecast, by Component

13.5.8.2. Market Revenue and Forecast, by Deployment Mode

13.5.8.3. Market Revenue and Forecast, by Application

13.5.8.4. Market Revenue and Forecast, by End Use

13.5.8.5. Market Revenue and Forecast, by Technology

Chapter 14. Company Profiles

14.1. Schneider Electric

14.1.1. Company Overview

14.1.2. Product Offerings

14.1.3. Financial Performance

14.1.4. Recent Initiatives

14.2. GE Vernova

14.2.1. Company Overview

14.2.2. Product Offerings

14.2.3. Financial Performance

14.2.4. Recent Initiatives

14.3. ABB

14.3.1. Company Overview

14.3.2. Product Offerings

14.3.3. Financial Performance

14.3.4. Recent Initiatives

14.4. Honeywell

14.4.1. Company Overview

14.4.2. Product Offerings

14.4.3. Financial Performance

14.4.4. Recent Initiatives

14.5. Siemens

14.5.1. Company Overview

14.5.2. Product Offerings

14.5.3. Financial Performance

14.5.4. Recent Initiatives

14.6. Amazon Web Services

14.6.1. Company Overview

14.6.2. Product Offerings

14.6.3. Financial Performance

14.6.4. Recent Initiatives

14.7. IBM

14.7.1. Company Overview

14.7.2. Product Offerings

14.7.3. Financial Performance

14.7.4. Recent Initiatives

14.8. Microsoft

14.8.1. Company Overview

14.8.2. Product Offerings

14.8.3. Financial Performance

14.8.4. Recent Initiatives

14.9. Oracle

14.9.1. Company Overview

14.9.2. Product Offerings

14.9.3. Financial Performance

14.9.4. Recent Initiatives

14.10. SAP

14.10.1. Company Overview

14.10.2. Product Offerings

14.10.3. Financial Performance

14.10.4. Recent Initiatives

Chapter 15. Research Methodology

15.1. Primary Research

15.2. Secondary Research

15.3. Assumptions

Chapter 16. Appendix

16.1. About Us

16.2. Glossary of Terms

For questions or customization requests, please reach out to us at sales@precedenceresearch.com

Frequently Asked Questions

Answer : The applied AI in energy and utilities market size is expected to increase from USD 802.16 million in 2025 to USD 5,325.60 million by 2035.

Answer : The applied AI in energy and utilities market is expected to grow at a compound annual growth rate (CAGR) of around 20.84% from 2026 to 2035.

Answer : The major players in the applied AI in energy and utilities market include Schneider Electric, GE Vernova, ABB, Honeywell, Siemens, Amazon Web Services, IBM, Microsoft, Oracle, SAP, Hitachi Energy, Bidgely, C3 AI, Google Cloud, and Palantir.

Answer : The driving factors of the applied AI in energy and utilities market are the increasing need for intelligent grid management solutions as utilities integrate renewable energy, digital infrastructure, and electrified energy systems.

Answer : North America region will lead the global applied AI in energy and utilities market during the forecast period 2026 to 2035.

Ask For Sample

No cookie-cutter, only authentic analysis – take the 1st step to become a Precedence Research client