Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in industry and business practice, while management-oriented research disciplines seem reluctant to adopt these sophisticated data analytics methods as research instruments. Even the Information Systems (IS) discipline with its close connections to Computer Science seems to be conservative when conducting empirical research endeavors. To assess the magnitude of the problem and to understand its causes, we conducted a bibliographic review on publications in high-level IS journals. We reviewed 1,838 articles that matched corresponding keyword-queries in journals from the AIS senior scholar basket, Electronic Markets and Decision Support Systems (Ranked B). In addition, we conducted a survey among IS researchers (N = 110). Based on the findings from our sample we evaluate different potential causes that could explain why ML methods are rather underrepresented in top-tier journals and discuss how the IS discipline could successfully incorporate ML methods in research undertakings.

人工智能（AI）和机器学习（ML）当前是行业和商业实践中的热门话题，而面向管理的研究学科似乎不愿采用这些复杂的数据分析方法作为研究工具。在进行实证研究时，甚至与计算机科学有着紧密联系的信息系统（IS）学科也似乎是保守的。为了评估问题的严重程度并了解其原因，我们对IS高层期刊上的出版物进行了书目审查。我们审查了1,838篇与AIS高级学者篮子，电子市场和决策支持系统（排名B）中的关键字查询相匹配的文章。此外，我们在IS研究人员中进行了一项调查（N = 110）。