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Will AI replace programmers?

A topic almost everyone is talking about lately

TL;DR: AI most likely won’t replace developers — at least not all of them and not anytime soon. What happens next remains to be seen. Generative models and autonomous agent bots are rapidly changing how developers work, but current forecasts mostly suggest a shift in tasks and required skills rather than the complete disappearance of the profession. The demand for skilled engineers is still growing, although junior developers are already feeling the pressure. Without proper reskilling, many routine positions may indeed disappear.

Quick stats before we get into details

76% of respondents in the Stack Overflow Developer Survey 2024 already use or plan to use AI tools, but only 43% fully trust the results — still a lot, though caution prevails

Developers are coding up to 55% faster with GitHub Copilot, according to several GitHub studies from 2023–2024

40% of jobs worldwide (up to 60% in developed economies) are exposed to AI — “exposed” meaning both risk of replacement and potential collaboration

17% – that’s the projected growth in software developer employment in the U.S. between 2023–2033 (BLS), much faster than the average for all occupations

How AI is changing developers’ daily work

1. Productivity

GitHub reports that copilots reduce task time by half. Developers mostly use that saved time to design systems, do code reviews, and improve their skills.

2. New skills

An OECD study across 10 countries shows that in AI-exposed professions (like developers and analysts), there’s a growing demand for business and management skills. 72% of job ads now require at least basic project management knowledge.

3. Smaller teams, higher expectations

Financial and telecom companies report they can hit the same goals with ~20% smaller teams thanks to Copilot. This mainly impacts junior and intern roles — in this case, yes, AI is replacing some developers, because if not for AI, those basic repetitive tasks would likely be done by juniors.

Risks and limitations

Code quality and security

The recent study “Secure Coding with AI – From Creation to Inspection” examined 1,586 code snippets in C/C++/C# generated in real ChatGPT conversations. After manual review, 32 vulnerabilities were found. 22 of them (69%) were introduced by the model itself, mostly involving CWE-79 (XSS) and CWE-330 (weak randomness). The authors stress that without static analysis tools and manual review, AI can produce code that seems correct but is actually vulnerable. In practice, this means teams need to integrate security linters into CI/CD pipelines and maintain secure coding expertise internally.

The “junior effect”

Automation of basic tasks puts the most pressure on entry-level positions. The SignalFire 2025 report shows that Big Tech’s hiring of fresh grads dropped by over 50% compared to 2019. New grads now make up just 7% of all new hires, with companies favoring mid/senior candidates who can handle prompt engineering and work autonomously. The result: bootcamps and universities need to emphasize practical AI tools more, and juniors must build portfolios through open-source, freelancing, or hackathons to show value beyond just writing routine code.

Lack of scientific consensus

Despite all the media noise, empirical research doesn’t offer a clear answer on whether AI creates or eliminates jobs. A meta-analysis of 371 estimates from 2019–2024 found no statistically consistent effect of AI on employment or wages. The outcomes heavily depend on how automation and exposure to AI are defined in each study. The authors call for better-standardized measures and comparable labor market metrics — until then, predictions about the “end of developers” are mostly speculation.

What this means for each experience level

Junior

There’s more competition for fewer jobs. As mentioned earlier, juniors are less in demand, although in the long run, the market can’t function without them — today’s juniors will eventually need to become tomorrow’s seniors. Still, many companies don’t plan that far ahead. They’re just optimizing for cheaper labor in the short term, and if AI gets the job done, they take that route.

Mid/Senior

There’s growing demand for domain-specific engineers and ML roles — like ML-Ops or AI roles in FinTech — and work with LLM APIs. So AI development is actually generating new jobs, especially in programming languages like Python.

In short

The real risk today is not an immediate job apocalypse, but the quality of AI-generated production code, fewer career paths for beginners, and high uncertainty in forecasts. Conscious teams are minimizing these risks by combining AI with strong security procedures, investing in junior development, and following academic research instead of media headlines.