More and more businesses are turning to AI-powered technologies to help close the data-insight gap and improve their decision-making capabilities in time-critical, high-pressure situations. These technologies encompass a wide range of tools, including virtual assistants, virtual and augmented reality, process discovery, task mining, and an array of data analytics and business intelligence platforms. Recently, there has been tremendous interest in generative AI or large-language models, a whole class of algorithms that are able to ingest vast tracts of data — text, numbers, software code, images, videos, formulas, and so on — understand their probabilistic structure, and create summaries, answers, simulations, and alternative scenarios based on these data. This article addresses three critical questions faced by decision-makers in using these technologies: 1) In what contexts are AI decision-making technologies likely to be beneficial? 2) What are some of the challenges and risks of using these technologies? and 3) How can business leaders effectively benefit from these technologies while mitigating the risks?