February 2024Global Energy & Materials PracticeBeyond the hype: New opportunities for gen AI in energy and materialsGenerative AI can create additional value from other forms of AI and analytics—and the energy and materials sector is uniquely well-positioned to benefit from these advancements. This article is a collaborative effort by Filipe Barbosa, Soenke Lehmitz, Jukka Maksimainen, Lapo Mori, Bryan Richardson, Erik Roth, Humayun Tai, Sapna Thakker, Ian Wells, and Rodney Zemmel, representing views from McKinsey’s Global Energy & Materials Practice.It’s nearly impossible to scroll through daily headlines without encountering commentary on generative AI (gen AI)—the latest frontier of artificial intelligence. It seems as if every Silicon Valley personality, venture capitalist, or casual technologist is talking about ChatGPT or Bard, among dozens of other systems, and the potential these tools have to unlock possibilities far beyond imagination. How closely should leaders pay attention to the hype? This isn’t the first time that technology pundits have lined up behind the latest best thing. Should gen AI be dismissed as a fad, or should leaders double down on the latest tools as the panacea for their technical troubles? The answer is likely neither. Our research shows that organizations that rely on innovation, data analysis, and process automation stand to benefit the most from gen AI. Within the agricultural, chemical, energy, and materials sectors, many companies are now moving beyond straightforward use cases and taking increasingly innovative approaches to adopting gen AI, and estimates show that an additional $390 billion to $550 billion of value can be created in the years to come.Harnessing the power of gen AIGen AI’s potential to accelerate growth and reduce costs cannot be ignored (exhibit). This is particularly true for the energy and materials space, which relies heavily on data and analytics for innovation and comprises sectors built upon increasingly nuanced and complicated processes. Simply stated, gen AI adds intelligence to any data, which can then be used to inform decision making—potentially reducing long processes to a single question—and it enables workers to gain previously unknown Exhibit Generative AI could create additional value potential above what could be unlocked by other AI and analytics.McKinsey & CompanyAI’s potential impact on the global economy, $ trillion1Updated use case estimates from “Notes from the AI frontier: Applications and value of deep learning,” McKinsey Global Institute, April 17, 2018. Source: “The economic potential of generative AI: The next productivity frontier,” McKinsey, June 14, 2023Advanced analytics,traditional machinelearning, and deeplearning1New generativeAI use casesTotal usecase–drivenpotentialAll worker productivityenabled by generativeAI, including in usecasesTotal AIeconomicpotential11...
