Generative AI In Energy Market Trends That Will Shape the Next Decade: Insights from Generative AI For Real-Time Asset Performance Management In The Energy Sector

Use code ONLINE30 to get 30% off on global market reports and stay ahead of tariff changes, macro trends, and global economic shifts.

How Large Will the Generative AI In Energy Market Size By 2025?
In recent times, the market size of generative AI in the energy sector has seen exponential growth. The market size which is poised to be $0.95 billion in 2024, is projected to escalate to $1.18 billion in 2025, growing at a compound annual growth rate (CAGR) of 24.2%. This growth during the historical period is linked to the emergence of renewable energy sources, increased demand in forecasting, the expansion of energy storage systems, optimization of demand response, and improved risk management and resilience.

How Big Is the Generative AI In Energy Market Size Expected to Grow by 2029?
The market size of generative AI in the energy sector is predicted to experience exceptional growth in the upcoming years, reaching $2.8 billion by 2029 with a compound annual growth rate (CAGR) of 24.0%. The surge during the projection period can be credited to improvements in accuracy, the need for enhanced electricity distribution, an intensified focus on customer engagement, a growing reliance on solar and wind energy, and an increase in asset management. Key trends in this projection period involve real-time predictions, dynamic adjustments and optimization, improved predictive analysis, the incorporation of advanced data sources, predictive upkeep and asset management, and intelligent grid control.

View the full report here:
https://www.thebusinessresearchcompany.com/report/generative-ai-in-energy-global-market-report

Which Key Market Drivers Powering Generative AI In Energy Market Expansion and Growth?
The surge in solar energy production is predicted to boost the generative AI energy market in the near future. Photovoltaic (PV) panels or focused solar power (CSP) systems are used to convert sunlight into electricity in solar power generation. The lowering costs of solar technology and growing acknowledgment of its environmental advantages, including decreased carbon emissions compared to fossil fuels, are fueling the uptake of solar electricity. Combining generative AI technology with solar power generation can provide great chances to fortify the efficiency, reliability, and endurance of energy systems pivotal for a shift towards a greener and more robust energy future. For example, in March 2023, the U.S. Energy Information Administration (EIA) of the U.S. Federal Statistical System anticipated that solar power will make up more than half of the U.S.'s new power capacity additions for the year. Worldwide, renewables are poised to expand their portion in the power generation junction from 29% in 2022 to 35% by 2025. Even though CO2 emissions from the worldwide power sector hit a zenith of approximately 13.2 gigatons (Gt) in 2022, they are expected to even out through 2025. As of January 2023, utility-scale solar power constituted 73.5 gigawatts (GW), roughly 6% of the U.S.'s total power capacity, while wind power was at 141.3 GW, or roughly 12% of the total. Moreover, U.S. developers are planning to boost wind capacity by 7.1 GW and add 8.6 GW of battery storage this year, doubling the nation's battery storage capacity effectively. As a consequence, the growth of solar power generation is propelling generative AI in the energy market.

Get your free sample here:
https://www.thebusinessresearchcompany.com/sample.aspx?id=15183&type=smp

Which Fast-Growing Trends Are Poised to Disrupt the Generative AI In Energy Market?
Prominent firms engaged in the energy sector's generative AI are honing their focus on the creation of innovative products like real-time asset performance management to enhance the procedures of energy production, distribution, and consumption. The term real-time asset performance management pertains to the process of overseeing, examining, and improving asset performance like machinery, equipment, or infrastructure, either in real-time or close to real-time. For example, in April 2024, Databricks Inc., a company based in the US specializing in global data, analytics, and artificial intelligence, introduced the data intelligence platform for the energy sector. This combined platform inhabits the energy sector with the force of AI, extending its impact on data and people. It resolves vital industry hurdles through real-time asset performance management, forecasts for renewable energy, and grid optimization, thus granting organizations the ability to refine their energy infrastructures and minimize market volatility. The data intelligence platform by Databricks is constructed on a lakehouse architecture to ensure a unified, open foundation for all data and governance. The driving force behind the platform is a data intelligence engine that recognizes the distinctiveness of data.

What Are the Emerging Segments in the Generative AI In Energy Market?
The generative ai in energymarket covered in this report is segmented -

1) By Component: Solutions, Services
2) By Application: Demand Forecasting, Renewable Energy Output Forecasting, Grid Management And Optimization, Energy Trading And Pricing, Customer Offerings, Energy Storage Optimization, Other Applications
3) By End User: Energy Transmission, Energy Generation, Energy Distribution, Utilities, Other End Users

Subsegments:
1) By Solutions: Energy Demand Forecasting, Predictive Maintenance Solutions, AI-Driven Energy Optimization Tools, Renewable Energy Management Solutions
2) By Services: Consulting Services, Implementation And Integration Services, Support And Maintenance Services, Training Services

Tailor your insights and customize the full report here:
https://www.thebusinessresearchcompany.com/customise?id=15183&type=smp

Who Are the Global Leaders in the Generative AI In Energy Market?
Major companies operating in the generative AI in energy market report are Google LLC; Microsoft Corporation; Engie SA; Enel Green Power S.p.A.; Huawei Technologies Co. Ltd; Amazon Web Services Inc; Siemens AG; General Electric Company; Intel Corporation; International Business Machines Corporation; Deloitte Touche Tohmatsu Limited; Cisco Systems Inc; Schneider Electric SE; Honeywell International Inc.; Flex Ltd; ABB Ltd; Duke Energy Corporation; Nvidia Corporation; Atos SE; Zen Robotics Ltd; Freshworks Inc.; C3 AI Inc; Databricks Inc; AppOrchid Inc; Verdigris Technologies; Ecube Labs Co. Ltd; Bidgely Inc

Which are the Top Profitable Regional Markets for the Generative AI In Energy Industry?
North America was the largest region in the generative AI in energy market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the generative AI in energy market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

Purchase the full report today:
https://www.thebusinessresearchcompany.com/purchaseoptions.aspx?id=15183

This Report Supports:
1.Business Leaders & Investors - To identify growth opportunities, assess risks, and guide strategic decisions.
2.Manufacturers & Suppliers - To understand market trends, customer demand, and competitive positioning.
3.Policy Makers & Regulators - To track industry developments and align regulatory frameworks.
4.Consultants & Analysts - To support market entry, expansion strategies, and client advisory work.

Speak With Our Expert:
Saumya Sahay,
Americas: +1 310-496-7795,
Asia: +44 7882 955267 & +91 8897263534,
Europe: +44 7882 955267,
Email: saumyas@tbrc.info

The Business Research Company - www.thebusinessresearchcompany.com

Follow Us On:
LinkedIn: https://in.linkedin.com/company/the-business-research-company

Learn More About The Business Research Company
With over 15,000+ reports from 27 industries covering 60+ geographies, The Business Research Company has built a reputation for offering comprehensive, data-rich research and insights. Our flagship product, the Global Market Model delivers comprehensive and updated forecasts to support informed decision-making.

This release was published on openPR.