AI Coding Tools Statistics 2026

84% of respondents are using or planning to use AI tools in their development process, an increase over last year (76%).

This year we can see 51% of professional developers use AI tools daily.

The overwhelming majority of respondents now use coding assistants and agents daily (73%), with nearly a third of daily users spending upwards of four hours.

Coding assistants and agents have pulled ahead as the dominant use case for AI (66%), outpacing even general-purpose LLM-powered chatbots (63%).

AI is becoming a standard in developers’ lives: 85% of developers regularly use AI tools for coding and development, and 62% rely on at least one AI coding assistant, agent, or code editor.

AI is becoming a standard in developers’ lives: 85% of developers regularly use AI tools for coding and development, and 62% rely on at least one AI coding assistant, agent, or code editor.

There’s no wonder 68% expect employers to require proficiency in AI tools in the near future.

This year's report reveals a significant finding: AI adoption among software development professionals has surged to 90%, marking a 14% increase from last year.

Gartner predicts that by 2028, 90% of enterprise software engineers will use AI code assistants, up from less than 14% in early 2024.

More developers actively distrust the accuracy of AI tools (46%) than trust it (33%), and only a fraction (3%) report "highly trusting" the output.

When asked when it’s acceptable to trust AI, 48% indicate they trust AI when they can easily validate the answers and only 16% extend that trust to most tasks that are not important work decisions.

In 2024, 35% of professional developers already believed that AI tools struggled with complex tasks. This year, that number has dropped to 29% among professional developers and is consistent amongst experience levels.

Our report uncovers a surprising "trust paradox": While 24% of respondents report a "great deal" (4%) or "a lot" (20%) of trust in AI, 30% trust it "a little" (23%) or "not at all" (7%).

Our report uncovers a surprising "trust paradox": While 24% of respondents report a "great deal" (4%) or "a lot" (20%) of trust in AI, 30% trust it "a little" (23%) or "not at all" (7%).

However, a critical disconnect remains: while 96% of developers report they do not fully trust that AI-generated code is functionally correct, only 48% state they always check their AI-assisted code before committing it.

However, a critical disconnect remains: while 96% of developers report they do not fully trust that AI-generated code is functionally correct, only 48% state they always check their AI-assisted code before committing it.

Today, 75% of all new code at Google is now AI-generated and approved by engineers, up from 50% last fall.

Today, 75% of all new code at Google is now AI-generated and approved by engineers, up from 50% last fall.

The study, which surveyed over 1,100 developers globally, confirms that AI adoption in coding has reached critical mass: 72% of developers who have tried AI use it every day, and AI accounts for 42% of all committed code—a volume that developers expect will rise to 65% by 2027.

A new study published in Science shows that AI-assisted coding is spreading rapidly, though unevenly: in the U.S., the share of new code relying on AI rose from 5% in 2022 to 29% in early 2025, compared with just 12% in China.

By contrast, experience levels matter: less experienced programmers use generative AI in 37% of their code, compared to just 27% for experienced programmers.

A recent analysis estimated that 4% of all GitHub public commits worldwide were being authored by Claude Code—double the percentage from just one month prior.

Every major coding agent runs on the platform and one in three pull requests on GitHub now involves an agent.

When it comes to coding, GitHub Copilot is the most popular AI pair programmer, now with over 26 million users.

When it comes to developers, GitHub Copilot now has 50 million users.

And, all up now we have over 4.7 million paid Copilot subscribers, up 75% year-over-year.

Moreover, AI adoption starts quickly: 80% of new developers on GitHub use Copilot in their first week.

We’re also happy to share that Cursor has grown to over $500 million in ARR and is used by over half of the Fortune 500, including NVIDIA, Uber, and Adobe.

We’ve also crossed $1B in annualized revenue, counting millions of developers and many of the world’s most accomplished engineering organizations as our customers.

Over 70% of the Fortune 500 now use Cursor to deploy and manage coding agents across the software development lifecycle.

Today, Claude Code’s run-rate revenue has grown to over $2.5 billion; this figure has more than doubled since the beginning of 2026.

Business subscriptions to Claude Code have quadrupled since the start of 2026, and enterprise use has grown to represent over half of all Claude Code revenue.

Claude Code (66%) and GitHub Copilot (59%) are the leaders for coding agents.

Claude Code (66%) and GitHub Copilot (59%) are the leaders for coding agents.

Core Result When developers are allowed to use AI tools, they take 19% longer to complete issues—a significant slowdown that goes against developer beliefs and expert forecasts.

This gap between perception and reality is striking: developers expected AI to speed them up by 24%, and even after experiencing the slowdown, they still believed AI had sped them up by 20%.

For the subset of the original developers who participated in the later study, we now estimate a speedup of -18% with a confidence interval between -38% and +9%.

The median self-reported speed change (which we expect to be higher than value change) is 3x.

Significant productivity gains: Over 80% of respondents indicate that AI has enhanced their productivity.

Nearly nine out of ten developers save at least an hour every week, and one in five saves eight hours or more.

Almost all developers (99%) now report time savings by using AI tools, with 68% saving more than 10 hours a week!

Developers are losing valuable time to non-coding tasks: 50% report losing 10+ hours per week, and 90% lose 6+ hours or more, largely due to organizational inefficiencies.

EXPERIENCED DEVELOPERS BENEFIT MOST The study shows that the use of generative AI increased programmers’ productivity by 3.6% by the end of 2024.

Recently, a particularly complex code migration done by agents and engineers working together was completed six times faster than was possible a year ago with engineers alone.

The Results: AI-generated Code That Works, But Isn’t Safe Here are the topline stats from our evaluation: 45% of code samples failed security tests and introduced OWASP Top 10 security vulnerabilities into the code.

Java was the riskiest language, with a 72% security failure rate across tasks.

The biggest single frustration, cited by 66% of developers, is dealing with "AI solutions that are almost right, but not quite," which often leads to the second-biggest frustration: "Debugging AI-generated code is more time-consuming" (45%)

The biggest single frustration, cited by 66% of developers, is dealing with "AI solutions that are almost right, but not quite," which often leads to the second-biggest frustration: "Debugging AI-generated code is more time-consuming" (45%)

The verification burden to avoid this debt is significant, with 38% of developers noting that reviewing AI-generated code requires more effort than reviewing code written by their human colleagues.

Improved code quality: A majority (59%) report a positive influence of AI on code quality.

We conducted in-depth interviews with developers about their code review process and found that 72.6% of developers who use Copilot code review said it improved their effectiveness .