Some software developers are choosing not to use AI tools for certain work—not because developers have broadly rejected AI, but because they weigh its usefulness against concerns about skill loss, privacy, ethics, and the value of staying involved in problem-solving. Stack Overflow’s 2026 survey captures that mix: respondents reported using AI for coding tasks while many also named reasons to avoid it.
What the 2026 survey says about AI avoidance
Stack Overflow asked respondents whether they tried to avoid using AI tools or agents at work or school and allowed them to identify a reason. Among 13,857 responses, 41.3% selected “I do not avoid using AI at work or school.” Other respondents selected one or more concerns:
- 17.1% (2,367 respondents): concern about losing job skills or training an AI to replace them.
- 15.2% (2,108): moral or ethical concerns.
- 13.0% (1,802): privacy or security issues.
- 8.2% (1,129): environmental concerns.
These are answers to a survey question, not a census of developers or a measure of how often people use AI. The categories also should not be treated as mutually exclusive: a respondent could identify a reason to avoid AI while still using it for some tasks. The figures and question-specific denominator are from Stack Overflow’s 2026 AI-avoidance data.
Why some developers hesitate
They want to keep building their own skills
The most frequently selected avoidance reason in the listed categories was concern about losing job skills or training an AI to replace the worker. That answer reflects respondents’ worry; it does not demonstrate that using AI causes skill loss or that a particular job will be automated.
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The concern is especially tangible in work where writing or changing code is part of learning how a system behaves. In CNN Business’s October 5, 2026 report, software engineer Audrey Eschright said, “Writing code is how you solve problems,” and described changing a system as a way to figure out what it does. Her account illustrates why some engineers may see coding as more than producing a finished block of code: the process itself can build understanding.
They need context and control
Software engineer Laura Housh told CNN she had tried AI for coding but could not get behind it. She said AI could offer direction or a second set of eyes, yet lacked enough context to be truly useful in her work. “I don’t like losing control; I like critical thinking and curiosity,” she said. Those are her views, not a finding that AI tools universally lack context or that every developer shares her experience.
Other objections are ethical, security-related, or environmental
Respondents also selected moral or ethical concerns, privacy or security issues, and environmental concerns. The survey records these as reasons people gave; it does not establish which specific product, policy, or environmental impact motivated each answer.
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Where developers report finding AI useful
The survey’s use of AI and avoidance responses are not contradictory. A developer might accept assistance on a task that is easy to check while avoiding AI for work that depends on sensitive information, deep system knowledge, or learning through hands-on problem-solving. Stack Overflow’s 2026 survey identifies coding assistants and agents as a leading AI use case, alongside the reasons some respondents avoid them. See the survey’s AI results for the broader context.
CNN’s account of the survey reported that a little more than 74% of respondents found AI useful for implementing code and about 72% for debugging. It also reported 34.4% found it useful for other job functions, such as communication and design. These figures are reported by CNN and should be read as survey responses about usefulness, not proof that AI produces reliable results or improves every developer’s work.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Trust often depends on whether the answer can be checked
In a separate question, 14,304 respondents described how much they trusted AI output. The most common trust response was conditional: 48.0% said they trusted it when they could easily verify the output. Just 6.6% said they trusted it for many tasks, including important work decisions. These figures come from Stack Overflow’s 2026 trust-in-AI data.
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That distinction offers a practical way to interpret mixed attitudes. An AI suggestion that can be reviewed against tests, documentation, or a known expected result presents a different decision from an answer that is hard to validate or could affect an important decision. The survey describes respondents’ reported trust; it does not test the accuracy of AI-generated code.
AI is only one part of developers’ job concerns
CNN also reported low job satisfaction in its account of the survey: 22.3% of respondents described themselves as happy with their current roles, while nearly one in three said they were unhappy. CNN compared the unhappy share with 28.4% the prior year. The article also cited burnout, tech fatigue, economic uncertainty, and unclear upward mobility as concerns. Those figures and explanations are CNN’s account of the survey, and they do not establish that AI is the cause of developers’ dissatisfaction.
Stack Overflow CEO Prashanth Chandrasekar told CNN that uncertainty about how much of a job may be automated can be unnerving. That observation helps explain the employment anxiety, but the survey responses do not show how many jobs AI has displaced or predict an individual worker’s prospects.
Quick Recap
How to read the findings
- They describe respondents, not every developer. The survey’s question-specific sample sizes differ, and its respondents should not be treated as a representative census of software workers.
- Using AI and avoiding it can coexist. A response naming an avoidance reason does not mean the person never uses AI.
- Reported usefulness and trust are not accuracy tests. They reflect what respondents said about their experience and confidence.
- Personal accounts show possible reasons, not prevalence. Housh’s and Eschright’s comments explain individual perspectives; they do not measure how common those views are.
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