ComTech Advisory announces a market study of AI technologies in energy business

ComTech Advisory is excited to announce the launch of new market research focused on data management and AI in the energy sector. This new study follows our recently published research on Virtual Power Plant (VPP) technologies (available for download here: VPP Market Study – ETT Center | ETT Center) and will use a similar methodology.

Nowadays AI appears to be rapidly emerging as a transformative technology, sparking ongoing debates among experts and policymakers about its potential benefits and risks. As companies increasingly pursue automation, advanced data processing, enhanced user experiences (e.g., through natural language interfaces), and more sophisticated real time decision-making tools, AI has become a central component in this drive.

AI is already being applied across various areas of the energy business. Some applications involve processing large volumes of data, such as predictive analytics, decision support and market data analysis. Others enhance user experience by integrating natural language processing (NLP) for reporting or deal entry or help to automate back-office processes and operations.

In many cases, AI and machine learning (ML) techniques are employed where complex data processing is required. Modern forecasting models are based on ML techniques or combine traditional analytical methods with ML to improve accuracy. Generative AI (GenAI) applications, which generate data with specific characteristics, also rely heavily on robust data processing. A key challenge for AI applications is ensuring that input data is clean, reliable, and that the methodologies used for data processing are transparent and adhering to privacy laws.

Additionally, most AI services and applications are developed as cloud-native solutions to leverage cloud computing’s elasticity and scalability, especially when handling large datasets. This introduces critical concerns around cybersecurity for data management. How are modern data management solutions addressing these concerns? What are the most effective strategies to ensure data reliability, security, real-time processing, and compliance with privacy regulations?

Another significant challenge is the perceived “black box” nature of AI-generated results, raising concerns about the trustworthiness of AI outputs. There’s also the fear of losing competitive advantage, especially when multiple companies adopt similar open-source AI tools in decision support functions. The more complex the decision support AI provides, the greater the need to demonstrate the validity and superiority of its outcomes. How are software vendors making AI-based decision support systems more transparent and gaining broader user acceptance?

These are just some of the questions ComTech Advisory aims to explore in our AI and data management study. Our research will also identify the most promising AI applications in the energy sector, analyze how vendors are addressing these industry concerns, and assess overall sentiment toward AI technology within the energy space.

We are actively seeking sponsors interested in showcasing their AI-based solutions and benefiting from the insights generated through this market research. If are interested, please let us know.

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