For years, Python has been treated as the only language that powers Artificial Intelligence – but that is no longer the case.
Today, AI is bigger, faster, and more complex than ever before. Organisations are no longer hiring professionals who only know one language; they want people who can combine creativity with a technical range, using different languages to build smarter, stronger AI systems.
According to recent global research, more than 70% of developers already use or plan to use AI in their workflow. Python remains the most mentioned language for AI programming, but other languages are rapidly rising in demand.
At Lorien, we’ve been studying this shift closely. With decades of experience in digital and technology recruitment specialist, we’ve identified the top 7 AI programming languages that employers value most.
Whether you’re starting your career in AI, exploring a role change, or leading a team that’s building the future, these programming languages will help you stay ahead of the curve.
Top 7 AI programming languages you should know
Artificial Intelligence isn’t built on a single foundation. Each language plays a unique role in shaping the systems that power automation, learning, and intelligent decision-making.
Here’s a look at the languages driving the AI revolution - what makes each one valuable, and how they fit into the future of intelligent technology.
1. Python:
Python remains the favourite of developers and data scientists around the world. It’s simple, readable, and supported by an enormous collection of libraries such as TensorFlow, PyTorch, and Scikit-learn, which make AI development faster and easier.
While Python still leads the way, employers now expect more than surface-level knowledge. Knowing how to optimise, deploy, and scale AI models using Python is what separates professionals who experiment from those who deliver results.
Pairing your Python skills with AI tools like ChatGPT can also help you practice interview questions, draft technical summaries, and make your job search more efficient
2. R:
R is the language that thrives on logic and precision. It’s built for deep data exploration, statistical modelling, and AI research.
When the goal is to uncover patterns or make predictions based on complex data, R remains unmatched.
Its popularity in industries such as healthcare, academia, and finance comes from its ability to turn raw data into practical, decision-ready insights.
3. Java:
Java continues to dominate large-scale, enterprise-level AI development. It’s secure, stable, and perfectly suited for projects that demand reliability over experimentation.
From fraud detection systems to intelligent logistics platforms, Java delivers consistent performance.
It integrates seamlessly with enterprise systems, making it one of the most trusted choices for building AI solutions that need to operate at scale.
Across the UK, we’re seeing increasing demand for Java developers with AI integration experience, especially in fintech and data analytics.
4. C++:
When AI needs to think fast, C++ takes the lead. Its strength lies in precision and speed, making it ideal for real-time decision-making in robotics, autonomous vehicles, and computer vision, skills increasingly sought after in infrastructure and DevOps recruitment.
C++ is the language behind many of the AI frameworks that other languages rely on.
It ensures that the most complex operations run with maximum efficiency, powering some of the most advanced intelligent systems in the world.
5. Julia:
Julia is rapidly gaining attention among AI researchers and engineers. It combines the simplicity of Python with the power of compiled languages.
It’s designed for numerical computing, simulations, and complex model building.
Julia’s performance makes it a perfect fit for industries that depend on data-heavy computation, such as finance, scientific research, and advanced analytics.
6. JavaScript:
JavaScript brings AI into everyday digital experiences. With frameworks such as TensorFlow.js and Brain.js, AI now operates inside browsers, creating smarter, more interactive user interfaces.
From intelligent chatbots to adaptive dashboards, JavaScript is what connects AI with people.
It turns data-driven intelligence into practical, user-friendly interaction.
In the UK market, JavaScript remains one of the most in-demand skills for front-end developers and product teams integrating AI into customer platforms
7. Scala:
Scala is the quiet force behind large-scale AI projects. It works in perfect harmony with Apache Spark to manage and process the massive data streams that fuel AI models.
It excels in scalability and efficiency, making it essential for organisations that rely on continuous, data-driven intelligence.
Scala powers the infrastructure that helps AI make smarter, faster decisions across industries.
Suggested Read: Most in-demand tech skills
The future of AI programming
The era of single-language expertise is over. Employers now look for adaptability, versatility, and curiosity.
From our work with leading UK tech employers, we’re seeing growing demand for multi-language fluency - particularly in roles that combine AI development, data science, and automation.
Understanding how these languages work together gives professionals an edge and helps businesses build AI systems that think faster and perform better.
We are experts at Lorien, we connect this world of evolving skills with the companies that need them most.
As experts in digital and tech recruitment, our specialist AI recruitment consultants help businesses find exceptional AI talent and guide professionals towards roles that shape the future of intelligent technology.
If you are looking to build a career in AI, now is the perfect time to explore the opportunities available through Lorien’s network.
Because in AI, success begins with the right people and the right languages - and connecting them is what we do best.
