Amid a cost-of-living crisis and the shift from fossil fuels to low-carbon alternatives, power and utilities face a seismic shift. According to the International Energy Agency (IEA), the world is on course to add more renewable capacity in the next five years than has been installed since the first commercial renewable energy power plant was built more than 100 years ago.1 This transition, characterized by a departure from traditional reliance on large, dependable plants to a landscape marked by numerous renewable energy units, brings new challenges. These include intermittent output, system instability, reliability concerns and the escalating impact of climate change-induced events like floods, storms and wildfires. We expect that digital transformation, specifically emerging technologies like AI, will be essential for technology officers to navigate these complexities.
This transformation presents challenges, compounded by increasing demand from customers seeking reliable, always-on essential services that lower their greenhouse gas emissions. Some consumers have taken matters into their own hands, engaging in self-generation and storage. Meanwhile, natural gas networks are grappling with how to decarbonize their networks and what emissions reduction targets mean for their businesses.
According to the KPMG 2023 CEO Outlook,2 nearly two-thirds (64 percent) of energy CEOs agree investing in generative AI is a top priority, with 48 percent expecting to see a return on their investment in three to five years. However, progress among many utilities is slow, stemming from a lack of capability, understanding or, in some cases, reluctance to embrace change. For example, many kinds of assets now generate an abundance of data — the global fleet of wind turbines alone is estimated to produce more than 400 billion data points per year3 — but without collection and organization this cannot be used to improve decision making.
