Relying on generative AI for complex cognitive tasks boosts productivity in the short term. But it comes at a cost measured over the long term: a reduction in the cognitive abilities of those who use it passively. This is not a theoretical hypothesis. It is what emerges from the Gartner analysis published in December 2025 in the report Predicts 2026: Intelligent Applications Shape the Future of Work.
What is cognitive offloading
Cognitive offloading is the process through which a person delegates to an external tool activities that would require mental processing. With generative AI, this phenomenon reaches a new scale. Guided GenAI systems, meaning AI capabilities embedded in business applications that automatically provide suggestions, recommendations, and next steps without the user explicitly requesting them, are bringing this dynamic to the center of daily work.
The problem is not using AI. The problem is using it passively. Relying on LLMs without first engaging independent thinking significantly reduces brain activity related to working memory and executive control, the cognitive functions critical for planning, decision-making, and evaluating options.
The real risk: erosion of skills and identity
When workers become passive recipients of AI output, their responsibilities shift from active control to mere oversight. Automating cognitively demanding tasks leads to rapid skill erosion from lack of continuous practice. This process can also erode professional mastery and work identity.
Gartner estimates that up to 25% of GenAI outputs contain hallucinations. Those who use guided GenAI without active critical thinking risk failing to recognize these errors, increasing exposure to public incidents and reputational damage. The echo chamber effect, meaning the tendency of LLMs to produce homogeneous outputs, also stifles the diversity of strategies and creative ideas as workers become progressively passive.
The "moral crumple zone"
Gartner introduces a precise concept to describe an emerging organizational dynamic: the moral crumple zone. Just as the crumple zone of a car absorbs the energy of an impact, workers who use guided GenAI often become the point where accountability falls when something goes wrong, despite having limited authority to intervene or correct system errors.
This is a problem of organizational design before it is a technological one. If the person responsible for an outcome has no real ability to interact with the AI process that generates it, the accountability system is broken.
Experience starvation in junior professionals
A specific side effect concerns those at the start of their careers. When guided GenAI removes people from the operational loop, they lose the hands-on experience needed to develop the judgment skills required to add value over time. Gartner calls this phenomenon "experience starvation": the lack of on-the-job learning opportunities that was previously guaranteed by direct task execution.
The paradox is that AI could be used in the opposite way: to create realistic, interactive simulations that allow junior professionals to exercise judgment in safe environments, building the necessary skills before operating on real processes.
How to manage the trade-off
Gartner does not suggest limiting AI use. It suggests designing it better. Whoever is responsible for an outcome must have the concrete ability to interact with the model, adjust prompts, and exercise decision-making authority over output quality. The success metric cannot be speed and completion alone: it must include instances where workers questioned, verified, and creatively applied AI-generated content.
Maintaining role rotations, using GenAI simulators for reskilling, and implementing critical thinking programs are the recommended levers for balancing automation efficiency with the preservation of people's cognitive abilities.
The takeaway
AI boosts productivity when used as an active tool. It reduces it, over the long term, when it becomes a passive delegation. The distinction is not technical but organizational: it depends on how processes are designed, who has real authority over outputs, and how much room people have to exercise their professional judgment.
