Top 10 AI Programming Languages You Must Learn in 2026

The sudden demand for Artificial Intelligence has led to the need for more and more engineers, researchers and programmers to work in the field. It is difficult to imagine life without the influence or contribution of AI. From job searches to spam mail detection, from ride sharing to social media connections, Artificial Intelligence is everywhere and helping our lives get better and easier.

Yet, it is pointless to say that without the tireless work and research in this field by the experts, it would not have been possible to have our "smart"-phones, eCommerce. The banking and financial sector is another huge platform where the role of AI is indispensable.

AI and Programming are the masters that work behind the curtains to establish this make-believe world of wonders. So how do they do it? Artificial Intelligence is a vast field with applications in almost every industry; to use AI in the applications, engineers working in the field need to feed instructions to the systems to become "intelligent" and behave in a certain way. These instructions are fed through AI programming languages and we will see the top ones nowadays.

Top 10 AI Programming Languages in 2026

1. Python

What is Python Used for in AI?

Python is the most widely used programming language for Artificial Intelligence because of its simple syntax, flexibility and huge ecosystem of ML and deep learning tools. It’s used for building end-to-end AI workflows from data cleaning and modelling to deploying intelligent systems. Python powers applications such as predictive analytics, recommendation engines, robotics, NLP models, computer vision systems and neural networks.

Its readability and low learning curve make it ideal for researchers, students and professionals who want to focus more on AI logic rather than complex programming rules.

Python AI Packages and Libraries

Python has the richest collection of AI and ML libraries, including-

This vast library ecosystem is the biggest reason Python dominates AI development globally.

AI Roles That Use Python

Python is the primary language used across most AI-based roles, including-

• Machine Learning Engineer
• Artificial Intelligence Engineer
• Data Scientist
• Deep Learning Specialist
• Computer Vision Engineer
• NLP Engineer
• AI Research Scientist
• Robotics Engineer
• Data Analyst (AI-driven analytics)

2. Java

What Is Java Used for in AI?

Java is widely used in AI development for building large-scale, production-ready applications. Its stability, platform independence and robust performance make it ideal for enterprise-level AI systems such as fraud detection platforms, recommendation engines, chatbots and distributed machine learning pipelines. Java is also popular for AI-driven Android applications and big data solutions.

Java AI Packages and Libraries

Popular Java libraries for AI include-

AI Roles That Use Java

Java is preferred in AI roles such as-

• AI Software Engineer
• Machine Learning Engineer
• Big Data Engineer
• NLP Engineer
• Android AI Developer
• Enterprise AI Architect

3. LISP

What Is LISP Used for in AI?

LISP (List Processor) is one of the oldest AI programming languages designed specifically for Artificial Intelligence. It is widely used for symbolic reasoning, expert systems, natural language understanding and rapid prototyping of AI solutions. Because LISP treats code and data in the same way, it excels in AI tasks where systems must manipulate symbols, logic and dynamic structures such as planning, theorem proving and knowledge-based reasoning.

Historically central to early AI research, LISP remains relevant today for projects requiring high flexibility, dynamic typing and fast experimentation.

LISP AI Packages and Libraries

LISP supports several AI-focused tools and libraries, including-

Because LISP is highly extensible, many AI researchers create custom libraries tailored to specific reasoning or symbolic-processing tasks.

AI Roles That Use LISP

LISP is commonly used in niche and research-oriented AI roles, including:

• AI Research Scientist
• NLP Research Engineer
• Cognitive Computing Researcher
• Symbolic AI Engineer
• Expert System Developer
• Academic Researcher in AI/ML

4. C++

What Is C++ Used for in AI?

C++ is used in AI for systems that demand high speed, real-time processing and efficient memory management. It powers performance-critical applications such as autonomous vehicles, robotics, gaming AI, reinforcement learning environments, computer vision and high-frequency trading algorithms. C++ is also used under the hood by many deep learning frameworks.

C++ AI Packages and Libraries

Popular C++ libraries include-

AI Roles That Use C++

C++ skills are essential in-

• Robotics Engineer
• Autonomous Systems Engineer
• Computer Vision Engineer
• Reinforcement Learning Engineer
• AI Systems Developer
• High-Performance Computing Specialist

5. Julia

What Is Julia Used for in AI?

Julia is a high-performance language designed for numerical computing, making it ideal for AI applications that demand speed, scalability and intensive mathematical computation. It is widely used for deep learning research, scientific computing, probabilistic modelling, time-series forecasting and large-scale data processing.

Because Julia combines Python-like simplicity with C-like speed, it is especially popular in advanced AI fields such as optimisation, simulation-based modelling and high-performance machine learning.

Julia AI Packages and Libraries

Julia offers several powerful AI libraries, including-

These libraries make Julia a strong competitor to Python and R in high-performance AI environments.

AI Roles That Use Julia

Julia is preferred in technical and computation-heavy AI roles such as-

• Machine Learning Engineer
• Deep Learning Researcher
• AI Scientist (Mathematics-focused)
• Data Scientist (High-performance computing)
• Quantitative Researcher
• Simulation & Modelling Engineer
• Computational Scientist

6. PROLOG

What Is PROLOG Used for in AI?

PROLOG (Programming in Logic) is one of the earliest AI programming languages and is widely used for building systems that rely on logic, symbolic reasoning and rule-based decision-making. It is especially useful in natural language processing, expert systems, automated theorem proving, cognitive modelling and search-based AI applications.

Because PROLOG is declarative, developers focus on defining facts and rules rather than writing step-by-step instructions. This makes it effective for solving problems that require logical inference, pattern matching and backtracking.

PROLOG AI Packages and Libraries

PROLOG supports a range of tools, libraries and implementations used in AI, such as-

Although several advanced languages have come into existence after PROLOG, it remains a favourite with many Machine Learning practitioners.

AI Roles That Use PROLOG

PROLOG is commonly used in AI roles that rely on logic-based problem-solving, including-

• NLP Engineer
• Expert System Developer
• Cognitive Computing Engineer
• AI Research Scientist
• Knowledge Representation Engineer
• Multi-agent Systems Developer
• Theorem Proving Researcher

7. R

What Is R Used for in AI?

R is widely used in Artificial Intelligence for statistical modelling, numerical computing, predictive analytics and data-driven machine learning tasks. It is especially preferred by statisticians, researchers and data miners who rely on R’s analytical strength to build AI models that require heavy mathematical computation.

R is commonly used for applications such as recommendation systems, fraud detection, data forecasting, sentiment analysis and statistical learning. Its ability to integrate with other languages like C, C++, Java, Fortran and Python helps teams handle performance-intensive AI workloads efficiently.

R AI Packages and Libraries

R offers a strong set of AI and ML libraries, including-

This rich package ecosystem makes R powerful for AI tasks where statistical accuracy and mathematical depth are crucial.

AI Roles That Use R

R is widely used in AI and data-driven job profiles such as-

• Machine Learning Engineer (statistics-heavy roles)
• Data Scientist
• AI Research Analyst
• Statistical Modelling Expert
• Quantitative Analyst (Finance/Insurance)
• Business Intelligence Specialist
• Data Mining Engineer
• Predictive Analytics Engineer

8. JavaScript

What Is JavaScript Used for in AI?

JavaScript is used in AI to build intelligent web applications, browser-based ML models, interactive AI dashboards and client-side inference tools. It is increasingly popular due to its role in enabling lightweight, serverless or real-time AI experiences directly in the browser.

JavaScript AI Packages and Libraries

Key JavaScript AI tools include-

AI Roles That Use JavaScript

JavaScript is used in-

• AI Front-End Developer
• Full Stack AI Engineer
• Data Visualisation Engineer
• Web ML Developer
• AI Product Developer
• Human-AI Interaction Engineer

9. Scala

What Is Scala Used for in AI?

Scala is used in AI for large-scale machine learning, distributed computing and big data processing. Thanks to its integration with Apache Spark, Scala is widely used for building AI systems that handle massive datasets, real-time analytics, recommendation engines and enterprise ML pipelines.

Scala AI Packages and Libraries

Popular Scala tools for AI include-

AI Roles That Use Scala

Scala is widely used in-

• Machine Learning Engineer (Big Data)
• Data Engineer
• AI Software Developer
• Real-Time Analytics Engineer
• Distributed Systems Engineer
• Recommendation System Developer

10. Rust

What Is Rust Used for in AI?

Rust is used in AI for building safe, high-performance and memory-efficient systems. It is gaining momentum in 2026 for developing AI models that require reliability, security and low-level optimisation such as embedded AI, autonomous systems, high-speed inference engines and mission-critical robotics.

Its strong focus on memory safety makes it ideal for preventing bugs that could cause failures in AI operations.

Rust AI Packages and Libraries

Rust’s AI ecosystem is expanding with libraries such as-

AI Roles That Use Rust

Rust is increasingly used by-

• AI Systems Engineer
• Robotics Engineer
• Embedded AI Developer
• Autonomous Vehicle Software Engineer
• Inference Optimisation Engineer
• Machine Learning Infrastructure Engineer

Comparative Analysis of Best AI Programming Languages in 2026

The table below compares different AI languages. It highlights the usability of each language and the common AI applications where they are used with examples-

Why BML Munjal University Stands Out for AI-Ready Education

At BML Munjal University, we never stepped back from keeping ourselves in sync with the changing paradigms of science, technology, economy and the business world. That’s why the curriculum of our courses is exclusive “outside in”, which means we have integrated basic academic concepts with the industry's real needs and changing landscape of science, technology and management.

Through this course, we aim to prepare the engineers of today and tomorrow who specialise in this field, learn about Artificial Intelligence, deep learning, machine learning, programming and are then pulled into the skyrocketing demand in the industry.

Why BML Munjal University’s Courses Are the Best

• Industry-integrated curriculum

The syllabus blends core academic theory with live industry projects and expert mentorship, meaning you learn doing, not just listening.

• Global immersion and partnerships

Students benefit from exposure to top international institutions and cross-border research opportunities, adding global perspective to local expertise.

• Strong research & incubation culture

With dedicated centres for innovation, entrepreneurship and computational sciences, BMU ensures you have the infrastructure to ideate, build and scale your ideas.

• Multi-disciplinary schools and specialisations

From engineering to management, liberal studies to law, BMU offers a broad palette of programmes so you can tailor your AI education in context.

• Experiential learning focus

The learning model emphasises hands-on projects, real-world data, tools and platforms, preparing you not just to know AI, but to apply it.

• Strong credentials and recognition

Accredited and recognised for academic-industry collaboration, BMU holds national rankings for management and other disciplines that underscore credibility.

Choosing the right university is all about aligning with a place that allows you to lead rather than follow. At BML Munjal University, we fuse academic rigour, industry relevance and global exposure into a learning experience that empowers you to build the intelligent systems, smart applications and transformative ideas of tomorrow.

Ready to make your mark in AI? BML Munjal University is your launchpad.

Conclusion

Apart from the above languages mentioned, there are many other programming languages used in building AI systems. Some of the other popular ones are Java, Javascript, Haskell, C++, AIML, Rust, Scala, etc. Each of these languages has features that make AI engineers choose one above the other for specific purposes.

With further AI advancements, more languages will evolve that will be better suited to tackle ML problems and less complex. The current generation of engineers will certainly go forward and be the pioneers who will lead this change.