Artificial Intelligence (AI) has now evolved from a phase of being merely adopted as a new system to now fueling the decision-systems to generate specific data. Borrowing from the social sciences and emerging sub-body of mathematics research literature and theories around algorithmic knowledge and value realization leads to the formation of perceptions around the confidence of allowing AI to be at the heart of any domain’s decision-making. This amalgamation of AI in decision-making systems (ADMS). The current study has undertaken attempts to link personal attributes to perceptions around ADMS with the boundary constraints of these perceptions, namely the stretch to which these perceptions vary across media and domain contexts. A scenario-based survey instrument has been used to collect the data from two sets of ADMS stakeholders, vis-à-vis owners and end-users of ADMS. Analysis of the collected data from this sample (N = 558) reveals that these stakeholders are by and large anxious about the risks associated with ADMS. They have a mixed and general attitude towards the on-field usefulness and fairness of ADMS outcomes at the societal level. These generic frames of mind are driven mainly by the individual traits and involvement and accountability in the domain like a revenue-generating business, social (healthcare), and the oversight of ADMS. Theoretical, management practice, and societal impacts about these findings are also discussed along the current work’s final sections.