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Keywords: Advanced Metering Infrastructure (AMI), Artificial Intelligence (AI), Cloud Computing, Data Sharing, Demand Response, Distributed Energy Resources (DERs), Energy Transition, Machine Learning (ML), Utility Modernization
Overview
The transformative role of cloud computing, AI, and enhanced collaboration in the electric utility industry emerged as key trends at the DistribuTECH conference and were exemplified by the solutions and partner ecosystem of Amazon Web Services.
AWS and other hyperscalers are partnering more deeply with their utility customers to enable them to modernize operations, improve grid reliability, enhance customer engagement, and accelerate the energy transition. To see how new value is being unleashed one finds, front and center, the importance of an optimal industrial data fabric. Having a unified data platform helps not only in de-siloing data, but in enabling such data to be leveraged cross-functionally for greater levels of collaboration as well as deeper and more scalable levels of insight.
The Background
Data-sharing partner ecosystems can mitigate risk. Such systems tend to thrive in economic sectors where collaboration levels are relatively high.
Part I of this series showed how higher levels of collaboration can set the stage for widespread success in reducing risk in an industry, while maintaining a healthy competitive standing of the companies involved if the industry’s position in the overall economy is sufficiently strong. The measure of the needed strength was made evident in the finance and insurance industries, where industry size and profitability were large enough to enable a risk-sharing data-centric partner ecosystem to scale, as needed, to meet key shared challenges.
The advancements highlighted by AWS at the recent DistribuTECH conference show how utilities and energy companies are now able to move their capabilities into higher gear by leveraging their own versions of these type of ecosystems.
Amazon Web Services - Powering Innovation at Scale at DistribuTECH 2025
At the recent DistribuTECH conference in Dallas, Texas, AWS and its end users and partners demonstrated scalable solutions that have raised the bar for what is “doable” today, and possible tomorrow. While the ability to build sophisticated models to support greater collaboration has existed in theory for decades in the utility industry, practical obstacles have hindered scalable and widespread development.
An obstacle that is being removed stems from the fact that data for many utilities was not sufficiently uniform for solution providers or end users to economically build accurate models, and maintain them economically, let alone deploy them in models to address new needs and foster new modes of collaboration. The sheer volume of data was, until recently, also a hindrance.
For example, Generation and Transmission (G&T) entities who supply electric service to industrial and distribution-level utility customers need more accurate planning capabilities. Short, mid-term, and long-term accuracy of planning is vital for G&T’s to prepare to secure or build additional generating capacity to meet future increases in peak electricity demand from their industrial and DSO customers. But accurate models cannot be built and run at scale, economically, when there is widespread lack of uniformity in the energy usage data associated with all the DSO’s different Advanced Metering Infrastructure (AMI) and Meter Data Management (MDM) solutions. Additional gaps remain to be filled for the 30% to 40% portion of U.S. utilities that still do not have AMI systems installed, or who have not used their AMI to model electricity usage sufficiently.
Similar issues exist in many other valuable use cases, including ones for modeling supply chains, and also for modelling up-to-date network connectivity data, and for optimizing ongoing operations and maintenance data associated with assets that are utilized by utilities and energy companies.
Amazon Web Services (AWS) is at the forefront of providing solutions and fostering the collaboration needed to navigate this evolution and enable industry to address the Energy Trilemma. In this regard, cloud computing, artificial intelligence (AI), and machine learning (ML) are critical to overcome data and modeling and related challenges and enable the transformation of the utility and energy sectors.
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