Guest: Simon Ritter (LinkedIn)
Company: Azul 
Show: Java Reloaded
Topic: Cloud Native

For years, the perception has been that AI development belongs to Python. But Java, a cornerstone of enterprise software, is quietly redefining its role in the AI ecosystem. In this clip from his conversation with Swapnil Bhartiya, Simon Ritter, Deputy CTO at Azul, explains how JDK 25 and Project Panama are bringing Java closer to data-intensive and AI-driven workloads.

Project Panama plays a crucial role in bridging Java with other languages, especially C, C++, and Python. This interoperability allows developers to call native libraries directly from Java, eliminating barriers that once made cross-language integration cumbersome. As Ritter points out, this means enterprises can now leverage AI models built in Python while running them within scalable, high-performance Java applications.

He also highlights the role of the Scoped Values and Vector API—two evolving features that enhance how Java handles memory and data operations in AI and high-throughput scenarios. Together, they make Java more efficient for the kinds of tasks increasingly found in machine learning and inference workloads.

But Ritter emphasizes that Java’s role in AI is not about competing with Python head-on. “AI on its own doesn’t really add value,” he explains. “It’s when you combine it with enterprise systems that you unlock real potential.” Java’s strength lies in what it has always done best—building robust, scalable, secure systems that can integrate complex processes, including AI.

That’s where Java has an advantage. Once an organization develops AI models using Python, they often need to deploy those models within existing enterprise architectures. Java’s RESTful web services and scalability make it ideal for production environments where performance and reliability matter as much as model accuracy.

This hybrid approach—Python for experimentation and Java for deployment—is becoming a pragmatic model across industries. Thanks to Panama and JDK 25’s performance optimizations, Java now has the tools to make that integration smooth and cost-effective.

Ultimately, JDK 25 signals that Java isn’t just surviving in the AI era—it’s adapting and thriving. By connecting enterprise reliability with AI innovation, it’s ensuring that the world’s most trusted language remains at the core of modern software development.