Artificial Intelligence (AI) and other digital tools hold enormous potential to help the energy sector deliver energy cheaper and more efficiently while also accelerating the transition to a lower-emission energy system. Where are companies putting these tools to use today? What are the opportunities on the horizon? How can executives parse hype from reality to make the most of these tools in their businesses? How “fast” is AI coming? What are the risks in embracing AI?
Electric vehicle (EV) sales are growing quickly in key markets. Strong government support and stringent tailpipe emissions standards, along with robust early consumer interest, have underpinned this growth. In reaction, auto manufacturers have placed EVs at the center of their net zero and long-term financial strategies. Now, slowing EV sales are raising important questions around consumer readiness for the electrified transport model. Why is there a striking gap between China and Europe, on one side, and the United States on the other? Is the EV demand growth of recent years sustainable? What role will governments, fuel providers and consumers play in the sector’s future?
The term “gamechanger” has nearly become cliché in describing the exciting technologies disrupting the energy ecosystem. But quantum computing might very well warrant its use. Making calculations a billion times faster than a conventional computer, think of the applications for this technology in addressing climate change. From longer-use battery technology for our electric vehicles to helping farmers plant with less carbon-intensive fertilizer are just two of the many, many ways quantum computing might indeed change the game.
The synergy between digital/AI technologies and the hydrogen ecosystem can be critical in the scaling of key operations throughout the hydrogen value chain. Whether in sector coupling, optimization, or end-use simulation, these technologies utilize great potential for improving the efficiency and effectiveness of operations and business models. How do we realize these benefits? What potential blind-spots exist?