This study aims to analyze the impacts of Artificial Intelligence (AI) and automation in the supermarket sector, focusing on three main areas: tasks, jobs, and automation processes. The research builds on studies about technology adoption and its impact on employment, including Christensen approach on disruptive innovation, Huang & Rust [19] on artificial intelligence in services, and Jarrahi [27] on human-AI symbiosis. A multiple case study approach was employed, involving interviews with four groups: cashiers, managers, customers who use self-checkouts, and customers who do not use self-checkouts. The interviews were analyzed using qualitative methods to identify emerging subcategories. Many customers prefer manned checkouts due to convenience. Self-service checkout technology is primarily used for small purchases, and younger customers find it easier to use. Employees do not currently feel threatened by automation, but there is a trend toward job reduction and relocation to roles requiring analytical, intuitive, and emotional skills. Managers do not see the need to prepare employees for a future without self-service checkouts, focusing instead on current training. Future research should analyze other supermarket functions that could be impacted by AI automation and investigate more deeply the acceptance and impact of these technologies on the labor market.

There are large varieties of governmental organizations using clouds in different ways. The purpose of this article is to explore and classify the types of public organizations using cloud computing. This will help to improve our understanding of cloud adoption and use by governments. For this, a systematic review of literature on cloud government (CloudGov) was performed by searching for articles in several databases. The review resulted into the main elements of the framework for classifying cloud use. In addition, using diffusion of innovation and institutional theory a categorization of public organizations was made. When applying the CloudGov framework empirically in government organizations, we identified three types of organizations: Leaders, Followers and Laggers. The types differ in various ways including their technology expertise, attitude towards innovation and level of political support. In further research, we recommend investigating which drivers influence the type of CloudGov users and generalize the framework to other contexts.