The history of human progress is, in many ways, a history of outsourcing labour. We built tools to extend our muscles, machines to extend our reach, and institutions to extend our collective capacity. Yet, up until now, one domain has remained fundamentally untouched: thinking. Decisions, judgement, interpretation, creativity, these are all areas where it was practically impossible to alter human agency. The brain and our specific capacity for thought seemed to be entirely unique to the human species. However, that last frontier is shifting. As AI systems increasingly handle writing, analysis, and even conceptual exploration, a quiet psychological transformation is underway. The question is no longer whether Artificial Intelligence can achieve human levels of thought, but rather whether we still choose to think within the context of its existence.
The appeal is obvious. Artificial Intelligence reduces friction in thought processes. It drafts emails in seconds, accelerates research, generates ideas without fatigue, and produces summaries in a fraction of the time it would take a human. It relieves us of the cognitive heavy lifting that once defined our work and our brain. But, in the same way as calculators altered numeracy and phones have altered literacy, the assistance we receive from artificial intelligence may come at the deeper cognitive cost of the erosion of independent thought. When a system becomes capable of doing something faster than we can, the temptation to hand the task over becomes almost irresistible. And once that handover becomes habitual, the skill begins to fade.
Thinking is often misconceived as a function, an inherent ability of the brain. However, this isn’t the case; it is a discipline, a muscle that strengthens through effort and weakens through disuse. Reasoning is not innate brilliance, but endurance trained from the bashing of our brains against the problems of logic. It is the ability to sit with ambiguity, to wrestle with contradiction, and to fight our internal biases. However, these are slow processes and often frustrating ones at that. AI, by contrast, offers the same, but for a fraction of the time and effort. It removes the discomfort, and with it, the very conditions under which the skill for deep thinking develops.
To clarify, the concern is not that people will lose the capability to think entirely. Rather a threshold for when thinking initiates will start to develop. There was never a question that thinking was required for drafting an argument, proposal, or concept; however, now these actions feel inefficient to attempt alone. The only reason we know we can do these tasks is that we have done them before. However, what does this imply for future generations that have always had access to artificial intelligence? When the mind knows that an external system can do the job faster, the intrinsic motivation to try diminishes. Over time, the act of thinking becomes a choice rather than a reflex, and choices made repeatedly tend toward ease, not discipline.
There is also a subtle psychological shift that occurs when one relies on a system that always responds with structured logic. Large Language Models (LLMs), like ChatGPT and Grok, offer explanations without hesitation. There is an inherent confidence in the style and speed with which they answer; they generate ideas without any sense of uncertainty. This smoothness has slowly started to create an implicit belief that thinking itself should feel like this. Unfortunately, however, human reasoning is never this tidy and immediate. Our minds very seldom explore concepts linearly. They meander, pause, contradict themselves, return to earlier steps, abandon promising ideas, and sometimes arrive at insight only after wandering without direction. If we grow accustomed to thought produced in perfectly formed paragraphs, our own more chaotic processes may begin to feel inadequate by comparison. Or worse, the uniqueness of each brain will slowly be trained out by the continuous habitual use of LLMs to a point where everyone thinks and writes in the same way.
This can lead to another form of dependence: not just outsourcing the work of thinking but outsourcing the validation of thought. The more we consult AI for confirmation, the more we become hesitant to trust our own intuition, especially when it conflicts with something that is always confident in its answers. A generation raised on search engines has already shown signs of this effect; the shift to generative systems may intensify it. While there will still be holdouts and possibly movements against the utilisation of these models, the path of least resistance will always be favoured by the majority of the population.
Yet dependence is not inevitable. It is entirely possible to integrate AI into the thinking process without surrendering the thinking process. The key distinction lies in whether artificial intelligence is used as a tool or as a substitute. If it is used to assist in clarification of concepts and research, and to bounce ideas off, the human remains the author of direction. However, when it replaces the human, by generating ideas wholesale and structuring arguments autonomously, it shifts the brain into that of an editor or validator, rather than the originator. The risk is that this reactive stance becomes the norm, and with it, the erosion of cognitive initiative will follow.
It is important to recognise that outsourcing thought is not inherently detrimental. Just as past technologies allowed human beings to transcend physical limitations, artificial intelligence can free cognitive space for tasks that are more strategic, conceptual, or interpersonal. The problem arises when we misunderstand what thinking actually achieves. It is not simply the production of output. Thinking shapes character, cultivates patience and discipline; these qualities cannot be shaped through the delegation of the thinking processes. Unfortunately, maintaining these qualities requires substantially more energy than just utilising these models entirely for thinking. In the field of business, if these qualities weaken, organisations may find themselves increasingly efficient yet decreasingly insightful, with the capability to act quickly but unable to reason deeply.
This has a profound impact on companies. It’s a paradox. The more we utilise artificial intelligence to do our thinking for us, the more essential human judgement becomes, but the more we utilise it, the weaker human judgement becomes. Judgement does not materialise automatically; it is the product of contending with difficult issues and building the skill to deal with new, more difficult situations. If teams grow accustomed to handing off the early stages of thought, they risk losing the rigour required to challenge assumptions, logic, and ambiguity. Organisations will possess more information than ever before, yet produce weaker decisions because the cognitive muscles required to interpret that information have atrophied.
There is also a cultural dimension. In many workplaces, thinking has already become compressed by demands for speed and output. AI accelerates this compression. If employees feel pressure to generate polished work instantly, they will be more tempted to outsource thinking to meet expectations. Over time, a company will no longer reward reflection and effort, but responsiveness. Culture doesn’t generally shift through policy; any CEO could tell you that, it changes through practices. With that in mind, the culture will be a shift from substantive reasoning to superficial efficiency.
None of this means that Artificial Intelligence must be resisted. On the contrary, it means that it must be integrated thoughtfully. Artificial Intelligence should expand our thinking, not replace it. This requires intentional habits: beginning a project with purposeful thinking and planning. It requires drafting initial ideas before consulting a model and using artificial intelligence to test arguments rather than generate them entirely.
Ultimately, the psychology of outsourcing thought is not a technological issue, but a philosophical one. It asks what value we place on thinking itself. If we treat thought as a burden, we will hand it away gladly. However, if we shift the idea of thinking to the foundation of creativity, autonomy, and what makes us inherently human, we may guard it more carefully. These models have never threatened human intelligence; they threaten our willingness to exercise it and tempt us into the easy way out. The more seamless the systems become, the easier the surrender will be.
The responsibility is not to resist using the tools, but to resist using them to think for us. It’s to ensure that in gaining cognitive convenience, we do not lose cognitive capacity. Really, our entire cognitive capacity will not be determined by what artificial intelligence can do, but by what we choose not to delegate. Thought, after all, is not merely a feature of humanness. It is a practice. And like any practice, it survives only through use.
- Written and researched by Sean Veldboer, Consultant at CBOS.