More Than Half Of Developers Say Llms Can Code Better Than Humans

(MENAFN- Robotics & Automation News) More than half of developers say 'LLMs can code better than humans'

August 28, 2025 by Mai Tao

A survey of 800 senior developers reveals rapid adoption of AI tools, but concerns remain around privacy, job loss, and accuracy.

With large language models (LLMs) rapidly becoming an unavoidable tool in the software industry, new research has revealed that over half (53 percent) of senior developers believe LLMs can already code better than most humans. LLMs are AI systems trained on vast text datasets to understand and generate human-like language. Examples include ChatGPT (OpenAI), Claude (Anthropic), and Gemini (Google DeepMind).

The survey, from Clutch , a marketplace for finding business services, polled 800 senior software developers in North America, highlighting how AI is reshaping the future of coding, with 75 percent of respondents saying they expect AI to significantly transform the industry within the next five years.

Almost half of developers use AI daily

AI has become a daily tool for many software teams. In the survey, 49 percent of senior developers and team leads said they use AI tools every day. Another 29 percent said they use them most days, meaning 78 percent rely on AI regularly.

Looking at where AI is most commonly used by developers, 48 percent of respondents use AI during coding, followed by 36 percent during testing and 36 percent during code review.

Almost a quarter 24 percent Are Concerned About Data Privacy with AI

With AI becoming more common, sentiments are generally positive regarding its rise. The largest portion of respondents had“positive” feelings about AI, at 42 percent. Another 29 percent said that they felt either“excited” or“empowered” by these tools.

However, 10 percent of developers said they're concerned about how AI is being used in software development, and 8 percent expressed skepticism.

Despite some positive sentiments, concerns do loom about its usage, as only 8 percent of respondents said they had no concerns at all about AI.

Looking at the top concerns about AI, the most common concern is data privacy, as almost a quarter (24 percent) said they're uneasy about how these tools handle sensitive data. After that, 14 percent named job loss as their top concern, and another 14 percent said they don't fully trust the accuracy of AI-generated code.

Over half of developers believe AI can already code better than humans.

In the survey, developers named data privacy and job displacement as their top concerns. That wasn't limited to early-career roles. Nearly half of respondents said they believe AI could threaten the software development field itself, not just individual jobs.

When asked how AI might affect entry into the profession, opinions were mixed. 45 percent of respondents said AI might actually lower the barrier for junior developers by giving them better tools and faster ways to learn.

But 37 percent said it would do the opposite, making it harder for newcomers to compete or even get noticed. AI's ability to automate junior-level work is reshaping hiring criteria.

Over half (53 percent) of respondents said they believe large language models can already code better than most humans. Whether that view reflects optimism or concern depends on who you ask, but either way, it's clear that expectations have shifted fast.

79 percent believe AI skills will be essential for future developers

As AI reshapes the work itself, it's also changing what teams look for when hiring. The survey uncovered that 79 percent of respondents said AI skills will be essential for developers in the near future, and 76 percent said they'd be more likely to hire someone with AI expertise.

However, that shift doesn't mean AI is just replacing people as 80 percent of developers said they see AI as an enabler, not a threat. Most believe its biggest value lies beyond automation.

It's not just about doing the same tasks faster. It's about doing them differently, with new methods for debugging, testing, and prototyping that weren't practical before.

Still, there's a gap between using AI and understanding how it works. 59 percent of respondents admitted to relying on AI-generated code without fully understanding what it does.

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