The hidden learning cost of generative AI: the THINK framework for preserving critical thinking in AI-enabled workplaces
Samuel Babatunde BodunrinPurpose
This paper examines how regular use of generative AI enhances productivity, but somehow, in contrast, reduces the opportunities for employees to utilize critical thinking skills and translate their hands-on experience into organizational learning.
Design/methodology/approach
The paper is a problem-based conceptual synthesis linking AI literacy, organizational learning, human-AI collaboration, evidence from knowledge workers, and knowledge collapse theory. On the other hand, human-AI augmentation and disengagement are considered opposing risks from which five workplace safeguards are derived.
Findings
The paper shows that the issue is not the use of GenAI, but organizations that reward flawless automation output while ignoring verification, human reasoning, and visible employee learning. The paper introduces the THINK framework interlinking organizational practices: Transparency, Human judgment, Intellectual engagement, Navigation of evidence and Knowledge construction.
Research limitations/implications
The THINK framework conceptual synthesis is selective and not empirically tested. Future research should validate the application effect across different sectors, industries and levels of GenAI adoption.
Practical implications
The THINK framework can be integrated into employee training, performance management discussions, decision-making and AI governance systems.
Originality/value
The paper transposes the traditional argument about GenAI-mediated cognition into a simple, auditable framework that managers can apply on the job as coaches, learning professionals, and AI governance teams.