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

Jul 12, 2026 Episode Page ↗
Overview

Noam Segal, a research leader and certified coach, joins Lenny to discuss the results of their annual Tech Worker Sentiment Survey. The survey reveals a tech workforce split by AI, surging burnout, declining career recommendations, and the top fear of being squeezed to do more for the same pay, alongside actionable advice for employees and leaders.

At a Glance
3 Insights
1h 36m Duration
15 Topics
5 Concepts

Deep Dive Analysis

Introduction to Noam Segal and the Tech Worker Sentiment Survey

AI's Impact: The Tech Workforce Split in Half

The Four Emotional Archetypes of Tech Workers

Burnout is Surging and Optimism is Declining

Layoff Worries and the Enjoyment of Work

Career Recommendation NPS Score for Tech Roles

AI's Impact: Faster Productivity, Lower Quality, Cognitive Rot

The #1 Fear: Doing More for the Same Pay

The Emotional Landscape and 'Smiling Exhaustion'

Designers and Researchers: The Most Negative Groups

Founders and Small Companies: The Happiest Groups

Managers: The Single Biggest Lever on Employee Well-being

The Chaotic and Unstable State of the Tech Industry

Actionable Advice for Employees and Leaders

Addressing AI Guilt and Closing Thoughts

AI Identity Stance

This framework describes how AI has shifted individuals' professional identities, categorizing them into amplified (positive), redefined (uncertain), destabilized (anxious), and diminished (negative).

Four Tech Worker Archetypes

These are distinct emotional profiles of tech workers: Energized (excited by AI), Conflicted (fun but uncertain), Disoriented (role shifting, unclear path), and Resentful (pressured, checked out).

Smiling Exhaustion

A phenomenon where tech workers feel reborn and excited by AI's capabilities and output, but are simultaneously exhausted by the relentless pace, constant learning, and lack of an 'off switch' in the industry.

Cognitive Rot

The decline in an individual's own thinking, judgment, and self-efficacy due to over-reliance on AI models, leading to a passive acceptance of AI outputs rather than critical engagement.

Net Promoter Score (NPS)

A metric typically used to gauge customer loyalty, adapted here to measure how likely tech workers are to recommend their role or the tech industry to others, ranging from -100 (detractors) to +100 (promoters).

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How has AI impacted tech workers' professional identity?

AI has shifted nearly everyone's professional identity, with 50% feeling amplified, 27% feeling redefined, 14% destabilized, and 5% diminished, indicating a significant and varied emotional response.

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What are the main emotional archetypes of tech workers today?

Tech workers fall into four archetypes: Energized (41%), Conflicted (35%), Disoriented (12%), and Resentful (12%), reflecting a wide spectrum of feelings from excitement to pressure and uncertainty.

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Is burnout increasing in the tech industry?

Yes, significant burnout has surged from 44.7% in 2025 to 54.7% in 2026, while optimism about the future of roles and careers has fallen from 54.8% to 48.7% in the same period.

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Are tech workers recommending their roles to others entering the industry?

No, across all roles, including founders, product managers, engineers, designers, and researchers, tech workers are not recommending their current roles to people entering the industry today.

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Is AI making tech workers better at their jobs?

While 97.2% of people feel AI makes them better, this often means doing more faster, not necessarily producing higher quality work, and it comes with a concerning cost to thinking and judgment, leading to 'cognitive rot'.

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What is the #1 fear among tech workers regarding AI?

The dominant fear is the expectation to do more for the same pay, followed by the unsustainable pace of work and technological change, rather than the fear of losing one's job to AI directly.

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How does manager effectiveness impact employee well-being?

Manager effectiveness has a massive impact; highly effective managers lead to dramatically lower burnout and 65% higher job enjoyment, but only about 25% of managers are rated as highly effective.

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Is it okay to feel mixed emotions about AI and the tech industry?

Yes, it is natural for positive emotions like curiosity and excitement to coexist with negative ones like feeling overwhelmed, conflicted, tired, or anxious, as the industry is undergoing a massive and complex shift.

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Who are the happiest people in tech right now?

Founders and people working in smaller companies consistently report the highest optimism, lowest burnout, and lowest layoff worry, making them the happiest groups in tech.

1. Prioritize Human Connection Over AI Focus

If you feel energized by AI, redirect some of that energy towards building relationships at work, supporting peers, and collaborating with those who perceive the technology differently, rather than solely focusing on new AI developments.

2. Combat Cognitive Rot with Deliberate Practice

Actively resist the tendency to offload all thinking and judgment to AI. Engage in deliberate practice, thinking, and judgment to maintain and improve your skills, ensuring you meet the rising bar of technology with your own capabilities.

3. Embrace AI Without Guilt

Do not feel guilty about leveraging AI, especially if you are early in your career. AI is a powerful and continuously improving technology, and learning to use it effectively is a valuable skill.

Half of the people in tech are feeling incredible, energized, amplified, excited about the technology and the future of, you know, their role. And the other half feel like the future is unclear. They feel destabilized. They feel diminished.

Noam Segal

AI and air models are the worst today that they'll ever be. They're only getting better.

Noam Segal

The productivity gains are real, but the quality of the work and the sharpness of the person producing it are taking a hit.

Noam Segal

The speed AI unlocked got plowed straight back into expectations. Every gain becomes a new baseline and the people expected to hit it are running out of room to breathe.

Noam Segal

We're in the second inning of a massive shift. No one knows how it will end, but all you can do is keep taking at-bats.

Anonymous Survey Respondent

Tech is manic, half out of touch, clinging to the bandwagon, pouring into the overhype. The other half are exhausted by the first half.

Senior PM

We have to remember that underlying all of this stuff are people, people. We, as people are going through the most massive shift and changes that we ever have in our lives.

Noam Segal

Employee Strategies for Thriving in the AI Era

Noam Segal
  1. Go deep on specific tasks: Focus on a couple of specific tasks or 'jobs to be done' where AI can be most useful, rather than trying to be a generalist who uses AI for everything.
  2. Watch out for the 'squeeze': Be aware of increased expectations to do more work for the same pay. Take a burnout test, reflect on your state, talk to your manager, and recalibrate your scope.
  3. Invest in your manager relationship: Protect and build good communication lines with your manager, as this relationship significantly impacts your well-being.
  4. Consider smaller companies or founding: If seeking advantages, explore working for a smaller company or starting your own, as these environments show higher satisfaction.
  5. Seek mentorship, especially early in career: If you're early in your career and feel uncertain, actively seek out mentors, teams, and managers willing to invest in your development.

Leader Strategies for Supporting Teams in the AI Era

Noam Segal
  1. Invest in your managers: Provide manager training and support, as effective managers are the biggest lever for improving employee enjoyment, reducing burnout, and increasing retention.
  2. Manage the 'squeeze' and expectations: Set realistic expectations for productivity and manage the increased workload driven by AI to prevent unsustainable demands on employees.
  3. Support early career advancement: Ensure entry-level people have clear paths to advance and grow, as they are often AI-native and valuable, preventing the 'bottom rung of the ladder' from rotting.
  4. Pay attention to struggling roles: Give extra attention and support to roles like design and research, which are currently experiencing more negative sentiment, recognizing their critical value.
  5. Acknowledge diverse AI experiences: Understand that AI impacts people differently, lifting some while destabilizing others, and tailor support accordingly.
~6,000
Survey Participants People from product, engineering, design, research, marketing, and other tech roles.
3%
AI Identity Shift (None) Percentage of people who reported AI hasn't shifted their professional identity.
50%
AI Identity Shift (Amplified) Percentage of people who feel amplified by AI.
27%
AI Identity Shift (Redefined) Percentage of people who feel their role is being redefined by AI.
14%
AI Identity Shift (Destabilized) Percentage of people who feel destabilized by AI.
5%
AI Identity Shift (Diminished) Percentage of people who feel diminished by AI.
44.7%
Significant Burnout (2025) Percentage of tech workers reporting burnout higher than moderate in 2025.
54.7%
Significant Burnout (2026) Percentage of tech workers reporting burnout higher than moderate in 2026, an 11-point increase.
54.8%
Career Optimism (2025) Percentage of tech workers optimistic about their future roles and careers in 2025.
48.7%
Career Optimism (2026) Percentage of tech workers optimistic about their future roles and careers in 2026.
72%
Layoff Worry (Overall) Percentage of tech workers worried to a certain extent about being laid off.
41.2%
Layoff Worry (Moderate or Higher) Percentage of tech workers at least moderately worried about being laid off.
97.2%
AI Making Better at Job Percentage of people who say AI is making them better at their job.
Close to 50%
AI Making Very/Extremely Better Percentage of people who say AI is making them very much or extremely better at their job.
71%
Founder Optimism Percentage of founders who are optimistic about their careers.
47%
Founder Burnout (Moderate or Higher) Percentage of founders who are at least moderately burnt out.
~25%
Manager Effectiveness (Highly Effective) Percentage of the sample who rate their manager as highly effective.
36%
Manager Effectiveness (Ineffective) Percentage of the sample who rated their managers as ineffective.
37%
Tech Industry Descriptions (Positive) Percentage of words used in open-ended responses to describe the tech industry that were positive.
37%
Tech Industry Descriptions (Negative) Percentage of words used in open-ended responses to describe the tech industry that were negative.
26%
Tech Industry Descriptions (Neutral) Percentage of words used in open-ended responses to describe the tech industry that were neutral.