This article explores the challenges faced by companies in profiting from artificial intelligence (AI). The case of Swedish multinational networking and telecommunications company Ericsson highlights that while AI holds great promise, realizing returns on investment in AI is difficult. This article identifies two main strategies: bottom-line improvements, which focus on internal efficiency gains, and top-line growth, which involves creating new businesses enabled by AI. The latter strategy is particularly challenging given the need for co-specialized complementary assets that amplify challenges related to data, capabilities, and value. This study of Ericsson’s experience emphasizes the importance of having clear strategic objectives and a deep understanding of complementarities in efforts to implement AI successfully.
