How Tech Workers Actually Feel About AI in 2026 | Annual AI Sentiment Survey

AI Divides Tech Into Two Opposite Camps
- AI has split the tech workforce roughly in half between those who feel amplified and those who feel destabilized or diminished.
- The AI identity stance predicts optimism, burnout, layoff worry, and willingness to recommend careers much more strongly than role, level, or company size. (Time 0:07:48)
Ship Faster, Burn Out Harder
- Burnout spiked from 44.7% to 54.7% year-over-year while optimism fell from 54.8% to 48.7%.
- Faster shipping and more outputs enabled by AI correlate with more burnout, not less, despite increased enjoyment for many. (Time 0:19:40)
Tech Roles Are Hard To Recommend Right Now
- Across functions, no one strongly recommends entering tech right now; NPS-like scores are negative across roles.
- Designers and researchers are the least likely to recommend their roles, reflecting high anxiety about role future. (Time 0:30:30)
Ladder Metaphor For AI Pulling Rungs
- Noam uses the ladder metaphor: AI climbs rungs from junior to senior, pulling rungs out from under workers lower on the ladder.
- The higher you are, the safer you feel; lower-rung workers perceive disappearing career rungs. (Time 0:37:00)
Productivity Gains Come With Cognitive Cost
- 97.2% say AI makes them better at their job, but deeper probing shows quality and thinking are suffering.
- People report doing more faster, yet experiencing cognitive rot and loss of judgment from over-reliance on models. (Time 0:45:49)
Main Fear Is Being Squeezed Not Replaced
- The top fear in tech is being squeezed to do more for the same pay, not job loss to AI.
- Pace of work and relentless expectations, amplified by AI, are the dominant sources of anxiety. (Time 0:53:03)
Ambivalence And Smiling Exhaustion Define The Moment
- Ambivalence is dominant: curiosity and excitement lead emotions, but overwhelm, conflicted feelings, and smiling exhaustion coexist.
- ‘Smiling exhaustion’ captures people who are energized yet have no off switch and feel relentless tempo. (Time 0:55:56)
Founders And Small Teams Report Better Outcomes
- Founders and people at smaller companies remain the happiest: higher optimism, lower burnout, lower layoff worry.
- Company size correlates linearly with worse outcomes; larger companies show steadily higher burnout and worry. (Time 1:06:31)
Pick Two AI Bets And Go Deep
- Pick a couple of AI use cases and go deep rather than trying to use AI for everything.
- Deep specialization correlated with energized respondents while spreading yourself thin correlated with burnout. (Time 1:25:20)
Manage Scope And Negotiate When Expectations Rise
- Watch the scope squeeze and negotiate scope or comp with your manager when expectations increase.
- Take the burnout test, recalibrate scope with your manager, and seek mentorship if early in your career. (Time 1:26:50)
Seek Mentorship If You’re Early In Your Career
- Early-career people should seek strong mentorship and teams that invest in development.
- Mentorship, not just tooling, helps preserve skill growth as entry-level rungs shift under AI disruption. (Time 1:28:23)
Invest In Managers To Improve Wellbeing
- If you lead teams, invest heavily in manager development because manager effectiveness strongly predicts burnout and retention.
- Only ~25% rated their managers highly effective, so manager training is a high-leverage intervention. (Time 1:28:44)
AI Guilt Appears Among Early Career Workers
- ‘AI guilt’ is emerging among juniors who feel using AI is cheating; this guilt declines with seniority.
- Product marketing, data, and analytics roles report the most guilt tied to using AI as a crutch. (Time 1:31:52)
Help Research By Participating In Future Surveys
- Participate in future research and community surveys to help the industry understand evolving worker sentiment.
- Noam asks listeners to join polls, longer surveys, and Slack discussions to improve shared understanding. (Time 1:34:23)