AI Deskilling Emerges as Doctors and Programmers Lose Skills Through Over-Reliance on AI Tools

AI Deskilling Threatens Professional Competence Across Industries

Artificial intelligence has become deeply embedded in professional workflows, but mounting evidence suggests this integration comes with an unexpected cost. Recent studies document how over-reliance on AI tools is triggering measurable erosion of human skills across medicine, software development, and other knowledge-intensive fields. A survey of US healthcare workers found that 70% of nurses and 77% of physicians worry about losing professional capabilities due to excessive dependence on AI systems1

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. These concerns are no longer theoretical—researchers are now documenting concrete evidence of AI's impact on professional competence.

Decline in Diagnostic Capabilities Among Experienced Physicians

A landmark study published in The Lancet Gastroenterology and Hepatology reveals how quickly AI in medicine can weaken human expertise1

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. Polish physicians specializing in endoscopy—each with at least 2,000 colonoscopies performed—were given access to an AI system that identifies adenomas during procedures. The results were striking: before AI introduction, these specialists achieved adenoma detection rates of 28.4% during colonoscopies. After becoming accustomed to the technology, their detection rate during procedures performed without AI assistance plummeted to 22.4%2

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. Multivariate analysis confirmed that exposure to AI was an independent factor negatively associated with adenoma detection, with an odds ratio of 0.69.

The study authors concluded that continuous exposure to such tools can cause clinicians to become "less motivated, less focused, and less responsible when making cognitive decisions without AI assistance"1

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. Yuichi Mori, a physician-researcher at the University of Oslo and co-author of the study, acknowledged that "there is no established solution against deskilling right now. It should be a very hot research topic in the next decade"1

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AI in Software Development Weakens Human Expertise

Parallel concerns are emerging in technology sectors. Anthropic, an AI firm in San Francisco, designed a randomized controlled trial involving 52 software engineers tasked with completing basic coding exercises1

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. While all participants could access web resources, only half were prompted to use an AI assistant. When tested on knowledge retention, those who used AI scored significantly lower—averaging 50% compared with 67% among participants who worked without AI help3

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. The AI-assisted group struggled particularly with diagnosing coding errors and explaining underlying concepts3

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Kevin Crowston, an information scientist at Syracuse University, explained the paradox: "Now you have this very odd disconnect between performance and learning. People can perform at a pretty high level, because they're basically borrowing skills from the AI, but they are not developing those skills themselves".

Automation of Reasoning Poses Long-Term Risks

Experts distinguish AI deskilling from previous technological shifts. While GPS navigation reduced the need to memorize routes, generative AI automates tasks involving reasoning, interpretation, and decision-making—core components of professional expertise3

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. Federico Cabitza, associate professor of computer science at the University of Milano-Bicocca, highlighted vulnerabilities in physical examination, differential diagnosis, and clinical judgment through a systematic review2

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Tapani Rinta-Kahila, an information systems researcher at the University of Queensland, warns that younger professionals may miss foundational learning experiences: "Next generations of programmers may not understand the foundations of coding that well at all, if they lack the hands-on experience. The same goes for many other knowledge-intensive professions, such as accounting and law"3

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Reskilling Programs and Balanced Approaches Gain Attention

Organizations are beginning to explore countermeasures. Healthcare institutions are investing in reskilling programs designed to help professionals use AI as decision support rather than skill replacement2

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. Some experts advocate strengthening capabilities that algorithms cannot replicate—creativity, critical thinking, emotional intelligence, and ethical sensitivity2

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. Others propose selective rather than continuous AI use, allowing healthcare workers to maintain clinical expertise while benefiting from technological assistance2

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. Crowston suggests that awareness itself prompts valuable reflection: "Just being aware that this phenomenon exists hopefully provokes some self-reflection about which skills people want to maintain and which they're willing to outsource to AI tools"1

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. As artificial intelligence continues expanding across professions, the challenge lies in harnessing efficiency gains without sacrificing the cognitive responsibility and judgment that define expert practice.