Artificial intelligence (AI) tools have demonstrated great potential to increase productivity in various areas. However, recent research suggests that indiscriminate use of these technologies can lead to the weakening of individuals' cognitive abilities.
Dependence and Cognitive Performance
Studies analyzed indicate that excessive dependence on these systems can diminish users' aptitude for problem-solving without technological support. This warning arose from investigations conducted with students and professionals, where participants who used AI showed immediate improvements in performance but faced difficulties when performing the same tasks autonomously.
Immediate Benefits in Different Areas
Experiments with workers and students confirmed that AI can optimize results when applied to activities aligned with their competencies. In a study involving hundreds of consultants from the Boston Consulting Group, researchers from the Wharton School noted an increase in the number of completed tasks and a decrease in time spent by those who had access to the tool.
This survey, published in 2026 in the journal Organization Science, revealed that employees assisted by AI produced higher quality work in functions where the technology was most competent. The most significant progress was observed among professionals who had a more modest initial performance.
A similar finding was found in a study conducted by Grace Liu of Carnegie Mellon University, focusing on mathematical problem-solving. By comparing students with and without access to AI, the study identified superior performance among those who could use the resource during exercises.
Negative Consequences of Technological Assistance
Despite the instant gains, researchers detected adverse effects after the removal of technological assistance. Individuals accustomed to AI began to show lower performance than those who had never used the resource and demonstrated less resilience in the face of difficulties.
Additionally, another study investigated how excessive trust in responses generated by AI systems affects decision-making. Steven Shaw and Gideon Nave evaluated over 1,300 participants and identified a phenomenon called 'cognitive surrender,' characterized by the user abandoning their own evaluation in favor of the conclusion provided by the machine.
AI as a Complement, Not a Replacement
Researchers argue that AI can operate as a third cognitive mechanism, complementing the traditional methods of fast thinking and detailed analysis described by Daniel Kahneman. The problem arises when this tool ceases to be a complement to human reasoning and begins to replace it entirely.
Experts emphasize that the crucial skill in the age of AI will be discerning which tasks should remain under human control and which can be delegated to automated systems. Collaboration is most effective when the user understands the limits of the technology and can judge its outputs.
An analysis from 2024, published in the journal Nature Human Behavior and based on 106 AI experiments, showed that joint performance between humans and machines is optimized when each party acts in its area of greatest advantage. However, when the system demonstrates superiority, the human difficulty in knowing whether to trust or contest the tool can compromise the final result.
Implications for Education and Creation
The interviewed experts highlighted that processes such as initial idea conception, text writing, and knowledge generation require active human participation. For them, AI is most valuable in phases of review, questioning arguments, and refining existing work.
The concern extends to the educational environment. The cited studies indicated that students may learn less by using AI solely to speed up school assignments. On the other hand, when the tool is used to gain clarification, formulate questions, and assimilate concepts, the damage to the learning process is minimized.
Judy Hanwen Shen and Alex Tamkin, from Anthropic, reported in their research with developers learning a new programming library conceptual difficulties, code reading, and debugging when AI was used as a shortcut to obtain ready-made solutions. The researchers' recommendation is to reconfigure AI as a tool for deepening understanding, stimulating questioning and expanding analytical capacity, rather than simply eliminating the mental effort required to learn.
