Categories: FAANG

Harnessing AI and data analytics can make clean energy more viable

The effects of climate change grow more tangible by the day. As a result, the electric power industry is hastening efforts to reduce environmental impact. To do so, they need help to get a clearer picture of where they fall on the emissions reduction roadmap, and to better understand their opportunities for improvement. This is where harnessing artificial intelligence (AI) and data analytics can help.

To assist utility companies, IBM has created the Clean Electrification Maturity Model (CEMM) in conjunction with the American Productivity & Quality Center (APQC). Based on 14 years of development and input from electric utility experts, the CEMM provides a series of benchmarks to help utility companies measure the maturity of their clean electrification capabilities, set priorities for transformation and track their progress along the way.

The results from the first global CEMM benchmark of 90 transmission and distribution utilities paint a telling picture of the role that technology can play in this critical transformation. Companies that harness AI and data analytics can also make clean energy more viable overall by increasing their cost competitiveness over legacy energy sources.

On average, 3.3 times more of the most mature utilities prioritize research in energy balancing and trading. This research can enable more liquid markets and lower energy prices for customers. By introducing AI into the renewable energy generation, transmission and distribution processes, utilities can better predict weather patterns in advance, giving them better insights into the output of solar and wind farms.

AI: The road ahead for energy and utilities

AI can also benefit customer care, freeing up resources for innovation in other aspects of their business. The most mature utilities were more than four times more likely to utilize customer experience platforms, including AI-powered chatbots and data analytics for personalized service. The latter can also help drive efficiency by lowering end-user energy use. Informed by automated reports, customers can better understand their energy consumption and take steps to reduce their power draw during peak periods of demand.

Despite these strides, the industry still has a lot of ground to make up to realize its carbon reduction goals. According to the CEMM study, the most mature 25% of transmission and distribution utilities still only achieved the modest overall score of 2.2 out of 5 across all domains. The average maturity for all T&D utilities was at the 1.6 mark. Technological maturity has vast potential for improvement; here, the most mature segment fared only marginally better than the bottom 75%, falling into the lowest development category.

Global electricity demands continue to rise. Utility companies must take urgent action to realign their organizations’ strategies and implement intelligent, data-driven processes for change. By emulating the successes of industry leaders and adopting the latest proven AI-enabled technologies, utility companies can take a big step toward meeting their own emissions goals and reducing the impact of climate change on the planet.

Access the full report and insights on the IBM Institute for Business Value

The post Harnessing AI and data analytics can make clean energy more viable appeared first on IBM Blog.

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