The algorithmic turn has fundamentally transformed journalistic work. Academic interest in the implication of automated algorithms for journalism has grown hand-in-hand with their everyday use. This paper presents a literature review of peer-reviewed research reports (N = 62) on automated algorithms in the context of journalistic work. Our review focuses on the first decade (2010–2019) during which automated journalism gained traction. The study identifies the most prominent perspectives or themes that studies in automated journalism have explored and the future directions for research that researchers have proposed. Based on the analysis, the dominant themes that studies in automated journalism have covered include (1) testing and developing algorithmic tools, (2) developing practices and policies for journalistic work, (3) attitudes and technology acceptance, and (4) societal and macro-level discourses concerning AI and journalism. The new directions for research that studies on automated algorithms have recognized relate to (1) target groups and stakeholders—that is, who to study in the future; (2) emergent themes and phenomena—that is, what to study in the future; and (3) approaches and methodologies—that is, how to study these topics in the future. These findings help create a holistic picture of possible future directions for the field.