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This paper aims to challenge the assumption that AI can fully replace human labor in organizations.

June 20, 2026Open Access

The Automation Efficiency Paradox: Why Generative AI Increases the Need for Human Expertise

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This paper aims to challenge the assumption that AI can fully replace human labor in organizations.
Introduced a behavioral and cognitive framework to analyze the effects of using AI in organizations.
Evaluated the implications of conversational AI outputs on human decision-making and cognitive processes.
Examined the relationship between AI use and the need for human expertise in operational workflows.
AI outputs often lead to cognitive fatigue in human operators, resulting in flawed data acceptance.
The system's design can camouflage errors instead of eliminating them, leading to potential mistrust.
AI increases the demand for skilled human experts to verify and guide algorithmic outputs, preserving workflow integrity.

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Randomized trial reveals AI increases reliance on human experts for effective verification, suggesting a need for balance in automation.

Sashikanta Barik (2026) studied this question.

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