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The Engineering Leadership Report 2026

How engineering leadership is evolving, and what it means for the future of the role.

In partnership with

Illustrated graphic depicting a grey silhouette of a person in a dynamic, reaching pose at the centre, overlaid with glowing constellation-style dots and lines suggesting a star map or circuit diagram. Surrounding the figure are dashed orbital paths in teal, blue, and purple, each containing icons representing different professional and technical domains: a people or mentoring icon, a bar chart with an upward trend, a microchip or processor, a target with an arrow, a settings gear, a wrench or tool, and a circuit connector. The composition suggests a skilled individual at the intersection of multiple disciplines — people, strategy, technology, and delivery — set against a deep navy space background with scattered stars and light bursts.

Software engineering leadership is operating under huge pressure.

Engineering leaders are being asked to do more – technically, strategically, and managerially – as organizations flatten and AI reshapes how code gets written, reviewed, and shipped.

Based on 600 responses, the data tells a story of an industry under sustained and compounding forces.

What’s inside

  • Analysis of 600 engineering leaders’ survey responses
  • How engineering leadership is evolving
  • A glimpse into the future of engineering leadership
Illustrated graphic depicting a stylised galaxy or solar system against a deep navy background. At the centre sits a bright white starburst surrounded by concentric elliptical rings in grey, purple, and teal, evoking a spinning galaxy or orbital system. Orbiting the centre are several icons representing technology concepts: a speech bubble with text lines suggesting communication or LLMs, a planet with a circuit board pattern representing AI or computing, a hierarchical org chart diagram, and a sun-like circuit node in the bottom right corner. Two ringed planets in blue and purple float at the edges. The overall composition uses the galaxy metaphor to suggest an interconnected ecosystem of AI-powered tools and systems.

Key takeaways

Technical work. 37% of engineering leaders are doing more hands-on technical work
Manager sentiment. One in three managers are considering ditching management to become an IC.
Working hours. 45% of leaders are working more hours than this time last year.
Junior developers. 84% believe AI will make it harder for junior developers to enter and grow in the profession.
Team motivation. 41% say their team is less motivated than 12 months ago.
AI for internal use is now the number one engineering priority.

Download the report

Report findings

Organizations are changing, not falling apart

Re-organization of team and division structures represents the most common significant change, cited by 67% of respondents.

Leadership changes affected 45% of respondents, while hiring freezes (35%) and layoffs (33%) were reported at similar rates to 2025.

The management layer picture is more nuanced, with 22% of respondents reporting a decline in managerial jobs and 19% seeing an increase in 2026.

A horizontal grouped bar chart showing the top five significant workforce changes companies made in the last 12 months, comparing 2026 (pink), 2025 (blue), and 2024 (teal). Re-organization of team or division structures is the most common change, cited by 67% in both 2026 and 2025 and 66% in 2024. Leadership changes follow at 45% (2026), 49% (2025), and 48% (2024). Hiring freezes were reported by 35% in 2026 and 2025, dropping from 50% in 2024. Layoffs were cited by 33% in 2026, 34% in 2025, and 44% in 2024. Policy changes requiring more time in the office were reported by 24% in 2026, 25% in 2025, and 18% in 2024.

Among respondents whose organizations saw a decrease in manager roles, the impact was concentrated at line management (59%) and middle management (65%) level.

However, a notable shift is occurring at the top:
23% of those reporting manager decreases said
upper management has been significantly
impacted, up from 18% in 2025 and 13% in 2024.

When organizations are hiring managers, the focus
remains on line (67%) and middle management
(50%).

Bar chart titled "If the number of managers has decreased, which levels were significantly impacted?" showing data across three years (2024, 2025, 2026) for four management levels. Middle management was most impacted in 2026 at 65%, up from 56% in 2025 and 43% in 2024. Line management follows at 59% in 2026, down slightly from 67% in 2025 but up from 42% in 2024. Upper management impact has grown steadily, reaching 23% in 2026 compared to 18% in 2025 and 13% in 2024. Other roles account for 5% in 2026, down from 12% in 2025.

The engineering leader’s role is expanding

Engineering leaders are being pulled in more directions simultaneously.

Scope and area of responsibility increased for 63% of respondents, consistent with previous years. Technical work is returning to the leadership agenda in a way that would have surprised many observers just two years ago.

More than a third (37%) of respondents say their hands-on technical responsibilities have increased in the last 12 months, compared to just 25% in 2025.

Nearly half of respondents (48%) say they spend more time on technical-related tasks than management-related ones, up from 42% in 2025.

Stacked horizontal bar chart titled "How have your roles and responsibilities changed over the past 12 months?" showing four response categories — Increased, Stayed about the same, Decreased, and Not sure or don't know — across four areas. Scope and area of responsibility saw the most increase at 63%, with 33% staying the same. Hands-on technical work increased for 36% of respondents and stayed the same for 45%, with 16% reporting a decrease. Number of direct reports increased for 29%, stayed the same for 50%, and decreased for 16%. Teams reporting to me changed least, with 22% reporting an increase and 61% staying the same.

Just under half (45%) of respondents report working more hours each week than at this point last year, up from 38% in 2025 and 35% in 2024.

The biggest increase was among advanced engineers, 53% in 2026 compared to 28% in 2025, followed by managers of engineers (44% vs. 38%)
and managers of managers (46% vs. 42%).

Six stacked horizontal bar charts comparing 2025 and 2026 responses to "Are you working more or less hours each week than this time last year?" across six engineering roles, with three response categories: More, About the same, and Less. Software Engineers working more rose from 31% in 2025 to 35% in 2026, while those working about the same fell from 60% to 54%. Advanced Engineers saw the sharpest increase, with those working more jumping from 28% in 2025 to 53% in 2026. Tech Leads bucked the trend, with those working more falling slightly from 48% to 44%. For Managers of Engineers, working more increased from 38% to 44%. Managers of Managers working more rose from 42% to 46%. CTOs or equivalents were the only group where working more decreased, dropping from 52% in 2025 to 46% in 2026.

A third (32%) of those in managerial positions are currently considering a return to individual contributor (IC) roles, up from 24% in 2025.

Managers of managers (29%) are less likely to transition back to IC roles compared with managers of engineers and CTOs (both 34%).

“Now more than ever, leaders must keep their technical skills sharp in order to understand, adopt, measure, and validate their team’s usage of AI tools,” says engineering leader Vaidehi Joshi.

AI adoption is widespread but poorly measured

AI-coding tools and agents are now mainstream in engineering organizations.

More than half (54%) of respondents say their organization has widely or totally adopted these tools. Only 1% say they have no plans to use them at all.

For the first time in this study’s three-year history, internal AI adoption (77%) has overtaken feature development (71%) as the leading engineering priority.

Horizontal bar chart titled "Which of the following best describes the stage of your engineering organization's adoption of AI-powered coding tools and agents?" showing six adoption stages. Widely adopted by many teams for many use cases is the most common response at 42%, followed by selectively adopted for a few use cases at 22%, proof-of-concept experimentation at 16%, adopted by all teams for all use cases at 12%, exploratory research at 8%, and no plans to use AI tools at just 1%. Combined, 54% of organisations report broad or full adoption.

The tools being used reveal where AI adoption currently sits in practice.

LLM-based chat interfaces for architectural research and debugging are the most widely used, cited by 79% of respondents. IDE-based coding tools with autocomplete and inline suggestions follow at 71%.

Vibe coding tools for rapid prototyping are
used by 48% of respondents overall, and 66%
of CTOs personally.

Horizontal bar chart titled "Which of the following types of AI-powered coding tools and agents do you personally use?" showing usage across five tool categories. LLM-based chat interfaces for architectural research, conceptual guidance, and debugging assistance are the most widely used at 79%, followed by IDE-based coding tools such as autocomplete and inline refactoring at 71%. CLI-based coding agents capable of executing terminal commands and multi-file edits are used by 64%, while AI-powered tools for automated code review, security auditing, and quality governance are used by 62%. Vibe coding tools for rapid prototyping are used by 48%. Respondents could select multiple options.

Measuring the impact of AI systems, however, remains a significant gap.

Employee feedback is the most commonly used metric for assessing AI’s impact on productivity (63%), but it is an imprecise instrument.

More rigorous metrics are used by only around a fifth of organizations.

“Self-reported productivity has never been the best signal,” says James Stanier, CTO at Nordhealth. “It should be paired with other signals, like the traditional DORA metrics (are we actually going faster?) and token spend (who is using the tools the most?).”

Five pie charts showing responses to "Is your organization using or considering the following metrics to assess the impact of AI-powered coding tools and agents on engineering productivity?" across four response categories: Using, Considering using in next 6–12 months, Not using, and Not sure or don't know. Employee feedback about tools being used is the most widely adopted metric, with 63% already using it, 14% considering it, 14% not using it, and 9% unsure. Development time per feature is more evenly split, with 31% using it, 20% considering it, 31% not using it, and 18% unsure. Change failure and pull request reversion rates show the lowest current usage at 22%, with 26% considering it, 34% not using it, and 18% unsure. Weekly time saved per developer is used by 22%, with 27% considering it, 33% not using it, and 18% unsure. Time spent reviewing and updating AI-suggested code is used by 21%, with 29% considering it, 34% not using it, and 16% unsure.

AI concerns, risks, and the
junior developer crisis

For all the momentum behind adoption of AI-powered coding tools and agents, the concerns among engineering leaders are substantial and deserve serious attention.

Impact on code maintainability tops the list of concerns at 73%, closely followed by the quality of AI outputs at 71%.

The impact on junior developers is the third most cited concern at 62%, and it is the one with the longest-range implications for the industry.

Horizontal bar chart titled "What are your biggest concerns regarding the use of AI-powered coding tools and agents?" showing seven concerns ranked by prevalence. Impact on code maintainability is the top concern at 73%, closely followed by quality of outputs at 71%. Impact on junior developers' ability to enter and grow in the industry ranks third at 62%, with security threats such as deep fakes and adversarial attacks on models at 58%. Access to and use of sensitive data and data privacy concerns are cited by 49%, impact on future role availability by 44%, and ethical concerns by 37%. Respondents could select multiple options

Based on another question, we know that 84% of respondents believe AI-powered tools will generally have a negative impact on junior developers.

Only 4% of respondents cited supporting junior engineers’ development in an AI-assisted world as the primary way AI is affecting their approach to engineering talent.

Just shy of half (49%) say upskilling existing engineers to work effectively with AI is the primary way AI is affecting their talent strategy.

Horizontal bar chart titled "How is AI most affecting your approach to engineering talent?" showing six responses. Upskilling existing engineers to work effectively with AI is the dominant response at 49%, more than double the next highest. Increasing productivity expectations from teams ranks second at 18%, followed jointly by rethinking hiring profiles and required skills and AI has not significantly changed our talent strategy yet, both at 12%. Redefining career progression accounts for 6%, and supporting junior engineers' development in an AI-assisted world is the lowest at 4%.

The human cost
of transformation

If the data on organizational change and AI adoption tells the story of external pressures, the data on team health tells the human story of what those pressures are doing to the people inside engineering organizations.

Job security concerns have risen for the third consecutive year, with 46% of respondents more worried than at this point last year, up from 42% in 2025 and 39% in 2024.

Software engineers are most concerned (61%), followed by tech leads (49%) and managers of engineers (46%).

Grouped horizontal bar chart titled "Are you more or less concerned about your job security than at this point a year ago?" comparing responses across 2024, 2025, and 2026 for three sentiment categories. Those feeling more concerned about job security has risen steadily each year, from 39% in 2024 to 42% in 2025 and 46% in 2026. Those feeling the same has declined consistently, from 50% in 2024 to 47% in 2025 and 43% in 2026. Those feeling less concerned has remained flat at 11% across all three years.

Burnout indicators deserve specific attention.

CTOs show the most dramatic shift: 54% report feeling emotionally drained from their work at least once a week, compared to just 24% in 2025.

“CTOs are burning out because AI has given teams virtually infinite capacity, creating relentless pressure to write highly detailed product specs to ‘feed the beast,’” says Thomas Johnson, CTO at Multiplayer.

Grouped horizontal bar chart titled "At least once a week I feel emotionally drained from my work" comparing 2025 and 2026 responses across six engineering roles. Software engineers saw the largest increase, rising from 39% in 2025 to 49% in 2026. CTOs or equivalents experienced the most dramatic shift of any role, jumping from 24% in 2025 to 54% in 2026. Manager of engineers remained broadly stable, falling marginally from 49% to 48%. Advanced engineers and tech leads both saw slight decreases, from 46% to 45% and 46% to 39% respectively. Manager of managers reported a notable improvement, dropping from 56% in 2025 to 46% in 2026. Across all roles in 2026, reported emotional exhaustion ranges from 39% to 54%.

Tech leads show a different but concerning pattern.

Their receipt of regular positive feedback has dropped from 41% to 31%, while cynicism about their jobs is rising.

The people in the middle of the leadership structure and the ones translating strategy into delivery appear to be under particular strain.

Grouped horizontal bar chart titled "At least once a week I feel cynical about my job" comparing 2025 and 2026 responses across six engineering roles. CTOs or equivalents saw the largest increase, rising from 22% in 2025 to 38% in 2026. Manager of managers also increased, from 35% to 42%. Software engineers remained broadly stable, edging up from 39% to 41%. In contrast, several roles reported declining cynicism: advanced engineers fell from 44% to 37%, tech leads from 47% to 39%, and managers of engineers from 39% to 35%. Across all roles in 2026, weekly cynicism ranges from 35% to 42%.

What does this mean for engineering leaders?

Engineering leaders are being squeezed from every direction – expanding technical and managerial responsibilities, longer hours, rising anxiety, and fragile team morale.

AI adoption is outpacing the frameworks needed to manage it, and the junior developer pipeline is at risk.

The organizations that navigate this moment won’t be the fastest AI adopters – they’ll be the ones that built trust, clarity, and investment in people.

Most aren’t there yet.

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Download the report

Read the full report and get the complete picture of engineering leadership in 2026.

Read the full report