Software developers were among the earliest professionals to integrate artificial intelligence into their daily workflows, but a growing number are actively stepping back from the technology. According to a new Stack Overflow survey of 30,000 software developers across 169 countries, six out of 10 tech workers report that they try to avoid using AI. The 103-question study offers a detailed look at how artificial intelligence is altering software engineering and reshaping workplace sentiment. Which includes responses from 30,000 software developers in 169 countries, were shared exclusively with ahead of their Tuesday publication, the results of Stack Overflow’s 103-question survey.
Despite widespread corporate adoption, tech professionals report mounting dissatisfaction with their roles. The survey found that nearly one in three respondents are unhappy in their current positions, up from 28.4% last year. Approximately 45% described themselves as “complacent,” while only 22.3% reported being happy. Respondents cited burnout, technology fatigue, economic uncertainty, and career stagnation as primary drivers of their frustration, with Stack Overflow CEO Prashanth Chandrasekar noting that the rapid acceleration of AI has intensified these underlying workplace anxieties. Many of those anxieties would exist regardless of AI.
“People have to completely retool their jobs, and so it is quite unnerving for folks to know exactly how much of what they’re doing will be automated,” Chandrasekar said. He explained that AI creates distinct challenges across experience levels: senior engineers worry their long-cultivated expertise is losing relevance, while entry-level developers face higher expectations, being expected to perform as if they already possess three years of experience. To keep pace with advancing tools, tech workers frequently spend their personal time training on new platforms. He said, senior programmers may feel the skills they’ve honed are no longer as relevant.
Laura Housh, a software engineer who began using AI as a coding assistant in 2024, described a love-hate relationship with the technology after two years. She regularly spends her off-hours watching AI instructional videos and reading documentation, yet still finds the pace overwhelming. “It’s taxing because you have a lot of noise saying, ‘Do this, do this, do this, or you’ll get left behind,’” she noted. “I’ve tried to use it for coding, and I just can’t get behind it.” Housh added that while AI can offer general direction or act as a second observer, it fundamentally lacks the context required to perform truly useful work. According to housh, She’s familiar with the pressures of learning and keeping up with AI.
Experienced engineers stress that using automated systems alters the core nature of software development. Audrey Eschright, a software engineer with two decades of experience, explained that relying on automated generation distances developers from problem-solving. “Writing code is how you solve problems,” Eschright said. “As a software engineer, the process of figuring out what a system does is to change it.” Housh echoed this sentiment, emphasizing the importance of human engagement: “I don’t like losing control; I like critical thinking and curiosity. It’s just so important to be more curious than ever.” A software engineer with 20 years of experience, it’s not about a lack of desire to embrace the new technology, for programmers like Housh and Audrey Eschright. Rather, the problem is that AI agents have neither the broad general knowledge of an experienced developer nor the job-specific context of a longtime employee.
The survey data highlights a sharp divide in how engineers view AI tools depending on the task. While 65% of respondents utilize coding assistants or AI agents, their trust in the software remains constrained. Over 74% find AI helpful for implementing code, and about 72% deem it useful for debugging errors. However, only 34.4% view AI as beneficial for other functions such as design and communication, and a mere 6.6% trust AI systems to make critical decisions. Additionally, roughly 78% emphasized that source attribution is vital when auditing code produced by AI.
Caution around these systems is growing as businesses push automation deeper into core operations. Last year, an Indeed Hiring Lab report named software developer as the job most poised to be transformed by AI, while a Google research division survey of 5,000 tech professionals showed that 90% used AI at work—up 14% from 2024. Meanwhile, a Deloitte report from January revealed that 54% of over 3,200 business and IT leaders expected to transition at least 40% of their AI experiments into full production within three to six months. As corporate projects move from experimental pilots to mainstream deployment, Chandrasekar emphasized that developers are exercising heightened caution because the operational stakes are now significantly higher.
