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While algorithms increasingly outperform human experts and gain widespread adoption, many individuals still resist using them due to algorithmic aversion. Although prior research has examined the appreciation and avoidance of algorithmic advice, the underlying mechanisms driving these decisions remain underexplored. This paper investigates the role of individuals’ readiness to act, specifically whether they adopt a deliberative or implemental mindset, in shaping their openness to algorithmic advice. Across three hypothetical studies and one incentive-compatible study, results show that individuals in a deliberative mindset, characterized by thoughtful evaluation, tend to prefer advice from human sources. In contrast, those in an implemental mindset, characterized by action-oriented thinking, are more likely to prefer algorithmic advice. Additionally, the findings reveal that perceived uncertainty moderates the influence of mindset on algorithmic receptiveness. These findings offer nuanced insights into the psychological mechanisms that drive engagement with algorithms and suggest practical strategies to enhance collaboration with both algorithmic and human recommendations. © 2025 Elsevier Ltd