How tech workers actually feel about AI in 2026 | Annual AI sentiment survey (Noam Segal)

Noam Segal and Lenny Rachitsky discuss the second annual technology-worker sentiment survey, which received responses from about 6,000 people across product, engineering, design, research, marketing, and other roles. The study asks how workers feel about AI, their jobs, layoffs, burnout, and career prospects. Segal contrasts its focus on these experiences with standard company culture surveys that tend to ask about managers and leadership.

The headline finding is a sharp divide in how respondents experience AI. Fifty percent say AI has amplified their capabilities; 27% feel their role is being redefined, 14% feel destabilized, and 5% feel diminished. Those who feel destabilized report uncertainty and anxiety, while those who feel diminished believe AI has taken something from their work that may not return. Segal presents these as reported emotions, not as proof of what will happen to these roles.

Segal says AI’s relationship to professional identity is more strongly associated with other measures of work than role, company, company size, or level. He cautions against relying on statistical significance alone and points to effect size as a way to assess practical importance. In the prior survey, manager effectiveness and founder happiness were among the largest relationships; the identity shift associated with AI was about three times as large.

The identity categories also track with career optimism, burnout, layoff worry, and willingness to recommend one’s role. Moving from feeling amplified toward feeling diminished is associated with lower optimism and higher reported burnout and layoff concern. Respondents were also less likely to recommend that early-career workers enter technology now. These associations describe the survey sample; they do not show that AI alone caused each outcome.

The survey asked respondents to select any emotions they felt, and people chose five on average. Segal groups the responses into four broad profiles: 41% energized, 35% conflicted, 12% disoriented, and 12% resentful. These labels capture the dominant patterns he observed, while the ability to choose multiple emotions reflects how mixed people’s experiences can be.