Artificial intelligence investments reduce risks to critical mineral supply.

ABSTRACT: This paper employs insights from earth science on the financial risk of project developments to present an economic theory of critical minerals. Our theory posits that back-ended critical mineral projects that have unaddressed technical and non-technical barriers, such as those involving lithium and cobalt, exhibit an additional risk for investors which we term the "back-ended risk premium". We show that the back-ended risk premium increases the cost of capital and, therefore, has the potential to reduce investment in the sector. We posit that the back-ended risk premium may also reduce the gains in productivity expected from artificial intelligence (AI) technologies in the mining sector. Progress in AI may, however, lessen the back-ended risk premium itself by shortening the duration of m

SUBMITTER: Vespignani J 

PROVIDER: S-EPMC11344786 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature