Why Python Still Leads: AI’s Impact on Language Rankings

AI‑Assisted Coding Changes Language Usage

AI‑assisted coding tools have become popular, and this shift does affect the frequency with which programmers use different languages.

IEEE Spectrum Top Programming Languages 2025

IEEE Spectrum released its annual "Top Programming Languages" ranking for the 12th consecutive year. The results show that Python remains the undisputed leader .

In the overall Spectrum ranking (weighted by IEEE member interest), Python has held the top position for ten consecutive years and continues to do so.

JavaScript experienced the biggest change, dropping from third place last year to sixth this year. As the dominant language for web development, its relative popularity decline may be linked to the penetration of AI tools in web development, such as the rise of "Vibe Coding".

In the "Jobs" ranking, which focuses on employer demand, Python achieved a milestone by taking the first place, pushing SQL down to second. Despite this, SQL skills remain a strong resume booster.

Historical Trends

Looking back, early rankings showed Java, C, C++, and Python almost tied. In 2016, C briefly overtook Java, and Python only rose to the top in 2017. The gap has widened: in the 2024 Spectrum list, Python scores 1.0 while Java scores only 0.4986.

Older languages are fading. For example, MATLAB fell from the top ten in 2014/2015 to 20th place this year, with its index dropping from 0.724 to 0.0957.

Overall, 19 languages now have an index above 0.1, up from 15 last year. JavaScript’s index fell from 0.4451 to 0.2872, the largest drop.

In the "Trending" ranking, Python still leads, with Java second (0.6777) and C++ third (0.4458).

How the Rankings Are Built

IEEE combines data from multiple sources: Google search trends, GitHub activity, IEEE Xplore paper counts, and IEEE Career Builder job data. Different rankings weight these sources differently; the "Job Demand" ranking is the most direct reflection of the employment market.

AI Reduces Reliance on Traditional Metrics

Programmers now rely less on public metrics. Instead of searching books or Stack Exchange, they converse with large language models (LLMs) like Claude or ChatGPT. AI assistants such as Cursor dramatically reduce the need to ask programming questions; weekly Stack Exchange posts in 2025 are only 22% of those in 2024.

This weakening of public signals makes tracking language popularity across languages harder. New metrics or direct programmer surveys may be needed.

Will Strong AI Assistants Render Language Abstractions Unnecessary?

Princeton researchers created Dall‑EM, a generative AI that designs RF and electromagnetic filters directly from input‑output specifications, bypassing traditional expert‑driven design.

Analogously, future AI might skip human‑readable high‑level languages, translating prompts into intermediate code that compilers execute. Code could become a black box, yet remain modular, testable, and quality‑controlled, shifting programmer work from bug fixing to prompt engineering.

Human Expertise Remains Crucial

Despite AI advances, architects and algorithm designers are still needed to decide on path‑finding methods, system integration, and overall design—tasks AI struggles to fully automate.

Thus, the most valuable skill will be understanding underlying logic and system design rather than sheer lines of code.

Future of Language Rankings

IEEE asks whether a "Top Programming Language" list will still exist in 2026. Their answer: programming is undergoing its biggest transformation since the advent of compilers in the 1950s. Even if AI hype fades, history shows each bubble leaves lasting tools, and AI‑generated code is likely one of them.

Consequently, we may need to rethink how we measure "popularity"—perhaps focusing on AI prompt usage rather than search volume or job demand.

Source: https://spectrum.ieee.org/top-programming-languages-2025