The current demographic development in Sweden points to a dramatic rise in the elderly population. At the same time, the population entering working age is projected to have a much smaller increase, combined with the fact that not every individual reaching working age will be part of the actual workforce. This is particularly problematic in certain rural communities where the overall population is experiencing a steady decline along with tax revenue, while the elderly population is rising. To compensate for the shrinking workforce in elderly care, authorities have identified digitalization, automation and AI as possible solutions. This qualitative study examines the perceived and actual need for AI in a rural community in northern Sweden, the community’s capability to implement AI in elderly care, and the capabilities of current healthcare AI solutions, in order to determine whether AI is a viable option to maintain an efficient elderly care. The empirical data collected via interviews was assigned to a theoretical framework based on Rational Choice Theory, in order to clarify the individual perceptions of the work environment and suitability of implementing AI to that environment. These findings were further related and applied to theoretical data collected through a literature review of research into past and present AI use cases, and the associated benefits and drawbacks of AI in elderly and general healthcare. First and foremost, our study shows that AI offers exciting opportunities but is yet in its infancy and therefore requires much attention and trials to operate at an acceptable level, with several concerns regarding sloppy or rushed implementations. Secondly, there is an apparent need and desire to automate certain processes in order to reduce stress in the workplace and allow the personnel to dedicate their time to the people under their care. Finally, we recommend that the examined community focus their initial efforts on “low-tech” AI solutions due to the inherent complexity of the technology and the high costs that follows a sloppy or failed implementation.