Understanding Firms’ AI Efforts and Their Economic Impact
Our research asks a central question for businesses investing heavily in artificial intelligence: Is AI actually making firms more productive, and if so, how? Using 15 years of data on AI-skilled employment at U.S. public firms, we find that firms increasing their AI investments experienced significantly faster productivity growth from 2018 to 2024—roughly one percentage point of additional productivity growth per year for a one-standard-deviation increase in AI investment. Importantly, these gains do not appear immediately; they build gradually over several years.
Behavioral Intervention Construal: A Framework for Understanding Inferences from Behavioral Interventions
Managers and policymakers frequently use behavioral interventions—including incentives and messaging campaigns—to influence people’s behavior. They often choose an intervention by asking whether it will make a desired behavior easier, cheaper, or more attractive. Our research suggests they should also ask a second question: “What could this intervention unintentionally communicate?” For instance, interventions can signal that an organization is self-interested or trying to control people’s choices.
Three Strategic Bets on AI’s Future
This paper examines competition in the consumer AI assistant market using worldwide iOS and Android app-store data from seven major AI assistants from May 2023 through December 2025. Rather than finding a winner-take-all market, we show that major product launches tend to coincide with growth in the overall category, with little evidence of direct cannibalization across leading models. In other words, the “AI war” appears less zero-sum than commonly assumed.
The Caring Machine: Feeling AI for Customer Care
Feeling skills have always been a human domain, but AI is advancing rapidly. This article shows how AI can be used to develop feeling intelligence and build empathetic customer relationships.
Simulation Optimization and Artificial Intelligence
With the relentless increase in computing power and the ubiquitous availability of data in many industries, the fields of simulation optimization and artificial intelligence have emerged at the scientific and engineering forefront in their societal impact, manifested in the pervasiveness of technologies such as large language models, chatbots, digital twins, and agent-based systems. We examine cross-fertilization between simulation optimization and artificial intelligence, with a particular focus on reinforcement learning, highlighting research that has been mutually beneficial.