Artificial intelligence (AI) is an umbrella term for various software-based systems that use data inputs to make decisions on their own. There are strong AI use cases in the power industry. Many activities, from asset optimization to customer segmentation, can be enhanced by AI.
The past 10 years have seen an explosion in the amount of data generated by power companies, mostly due to the rise of the Internet of Things (IoT). AI provides an opportunity to significantly increase performance through the use of data collected from IoT devices, and power companies that are not making use of AI will fall behind those that do.
GlobalData anticipates that the global market for AI platforms in the power industry will reach an estimated $5.3bn in 2024, having grown at a compound annual growth rate (CAGR) of 24% from 2019. Large utilities will continue to develop their in-house capabilities, hiring machine learning and data science specialists, and more AI-specific start-ups will persist in growing the list of AI-focused partnerships in the power sector.
Electricity trading, smart grids, and asset management represent primary growth areas for AI in the power sector. Machine learning, a key element of the AI value chain, will drive most of this growth.
Segmentation of artificial intelligence value chain, with details of vital topics such as machine learning and conversational platforms. Coverage of a wide variety of applications of such technologies within the power sector, with further detail in case studies.
Market forecasts of revenues for AI-related technologies in the power sector, and analysis of expected growth areas. Invest-explore-ignore recommendations for each AI technology segment of the power value chain.
Analysis of challenges currently faced by power companies and how these challenges are being addressed through AI.
Detailed assessment of leading companies in the AI theme including leading AI vendors, leading adopters of AI in the power sector, and specialist AI vendors in power.
Listings of major M&A activities related to AI in power.
Scorecards identifying the leaders and laggards in the 10 most important themes for the power utilities sector, ranked using GlobalData’s thematic methodology.
Reasons to Buy
Identify key use cases for AI technologies: reduce costly downtime with predictive maintenance platforms or improve customer engagement through personalized energy alerts.
Develop long term business cases for AI by accessing details on nascent AI technologies, ensuring you know how they may impact your industry in the future.
Equip your company with the knowledge of how to use AI to combat the most important power challenges, such as improving the customer experience which will help your company drive revenues.
Compare leading AI vendors, decide whether it’s best to develop partnerships with AI vendors in Big Tech, or specialist AI companies, and shortlist some potential suppliers.
Benchmark your company against competitors and justify key areas of investment by using GlobalData’s thematic scorecard, which ranks the top 40 power companies globally on the 10 most important industry themes.
Avoid wasteful investments and ensure you are delivering value by utilizing GlobalData’s invest-explore-ignore ratings for each AI technology for each segment of the power industry (generation, transmission & distribution, and suppliers).
ABB, Alibaba, Alphabet, Amazon, Apple, AutoGrid, Baidu, Bidgely, BP, C3 AI, Cambricon, Darktrace, DEWA, Drift Marketplace, Duke Energy, EDF, Enel, E.ON, Exelon, Facebook, Fluence, General Electric, Graphcore, Honeywell, Iberdrola, IBM, Intel, Microsoft, mPrest, National Grid, Nvidia, Rockwell Automation, Saudi Aramco, Schneider, SenseTime, Shell, Southern Company, SparkCognition, Stem, Suncor, Tencent, Uplight, XenonStack
Table of Contents
AI value chain
The impact of AI on power
Market size and growth forecasts
Mergers and acquisitions
Leading AI adopters in power
Leading AI vendors
Specialist AI vendors in power
Power utilities sector scorecard
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