Journalism is at a radical point of change that requires organizations to come up with new ideas and formats for news reporting. Additionally, the notable surge of data, sensors and technological advances in the mobile segment has brought immeasurable benefits to many fields of journalistic practice (data journalism in particular). Given the relative novelty and complexity of im-plementing artificial intelligence (AI) in journalism, few areas have man-aged to deploy tailored AI solutions in the media industry. In this study, through a mixed-method approach that combines both participant obser-vations and interviews, we explain the hurdles and obstacles to deploying computer vision news projects, a subset of AI, in a leading Latin American news organization, the Argentine newspaper La Nación. Our results high-light four broad difficulties in implementing computer vision projects that involve satellite imagery: a lack of high-resolution imagery, the unavail-ability of technological infrastructure, the absence of qualified personnel to develop such codes, and a lengthy and costly implementation process that requires significant investment. This article concludes with a discus-sion of the centrality of AI solutions in the hands of big tech corporations.