"The development of AI is producing multiple winners and losers among programming languages. The best-known languages in datasets regularly produce better, more consistent AI-generated code. This is one of several explanations for the continued growth of Java. This is despite problems surrounding Oracle's revenue model for the programming language, which seems to be driving the popularity of Java-compatible alternatives. Python was ahead of other programming languages: as the most popular language before the AI hype, it has remained at a lofty height."
"Sixty-two percent of the more than 2,000 Java professionals surveyed use Java for AI development, significantly more than the 50 percent who indicated this last year. The exact variant does differ, however. It is more accurate to say that the Java Virtual Machine dominates production AI, not the Java language itself. Scala (47 percent), Groovy (43 percent), Kotlin (39 percent), and Clojure (28 percent) are all used, while Java itself (19 percent) has become a niche."
AI development produces multiple winners and losers among programming languages, with languages well represented in training datasets yielding better, more consistent AI-generated code. Java's growth reflects this dataset advantage despite Oracle's costly licensing changes driving interest in Java-compatible alternatives. Python remains dominant for AI research and prototyping, while the Java Virtual Machine ecosystem, including Scala, Groovy, Kotlin, and Clojure, dominates production AI services because of performance, security, and reliability requirements. A 2026 survey of over 2,000 Java professionals found 62% use Java for AI development, and JDK 21 will lose free support in September.
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