Important points
When working with AI, knowing the right language will help you adapt to the changes AI brings to different industries.
-
Common programming languages for AI development include Python, Java, C++, and Julia.
-
In AI, programmers write code to create tools and programs that can use data to “learn” and make useful decisions. In traditional coding, on the other hand, a programming language instructs a computer or other device to perform an action.
Explore some popular AI programming languages, find out the differences between traditional coding and coding for AI, and how AI is changing programming. If you’re ready to start building your AI development expertise, register. Gemini for Developers Specialization. In just one month, you can build essential skills for AI software development, including token management, AI agent architecture and deployment, and strategic model selection. By the end, you’ll have a shareable certificate for your resume or LinkedIn profile.
Why should I learn a programming language for AI?
The world of programming is undergoing major changes, and learning an artificial intelligence (AI) programming language seems more important than ever. According to Deloitte research, 34% of global companies have already started using AI to transform operations in 2025, 74% plan to deploy AI agents within the next two years, and adoption of physical AI such as robots and self-driving cars is expected to reach 80% within two years. [1].
AI is rapidly evolving. Similarly, AI jobs are steadily increasing, and in-demand positions such as machine learning engineers, data scientists, and software engineers often require being tech-savvy. If you’re considering working in AI or want to try your hand at it, knowing the right language and staying up to date with programming will help you navigate the changes AI brings to various industries.
read more: Learning how to code: A beginner’s guide
Which programming languages are most frequently used in AI development? Top AI programming languages
Depending on your use case, different programming languages will be ideal. Here we introduce four popular coding languages (Python, Java, C++, and Julia) that are suitable for AI-related applications and technologies.
1. Python
Python is a general-purpose object-oriented programming language that is popular among programmers. It is preferred for its simple learning curve, extensive support community, and variety of uses. The same ease of use and Python’s ability to simplify code has made it the go-to option for AI programming. It features an adaptable source code and works on a variety of operating systems. Developers often use it for AI projects that require processing large amounts of data or developing machine learning models.
2. Java
Java is typically longer and requires more lines of code than Python. Although Java’s community is smaller than Python’s, AI developers often rely on Java for its automatic removal of unnecessary data, security, and maintainability. This powerful object-oriented language also offers easy debugging and use on multiple platforms. Java’s libraries include important machine learning tools and frameworks that make it easy to create machine learning models, run deep learning functions, and process large data sets.
3.C++
Like Java, C++ typically requires code that is at least five times longer than what Python requires. It may be difficult to learn, but it allows for faster execution and efficient programming. These factors make C++ excellent for complex AI applications, especially those that require large amounts of resources. It’s a compiled, general-purpose language that’s perfect for building AI infrastructure and working on self-driving cars.
4.Julia
Julia excels at performing computation and data science, with benefits such as general-purpose use, fast and dynamic performance, and rapid execution capabilities. Excellent for use in machine learning, offering the speed of C and the simplicity of Python. Julia is a relatively new programming language, with its first iteration released in 2018. Julia supports distributed computing, an integrated package manager, and the ability to run multiple processes.
Which is better for AI: C++ or Python?
When working with AI, you can use both C++ and Python, but each language serves a different purpose. Most AI projects will prefer Python because it is easy to use, offers a wide variety of libraries, and has strong support across the AI and machine learning community. If you’re developing performance-critical applications, you can also use C++, but it’s not often used for everyday AI tasks.
How to program AI: AI and traditional coding
Coding is a must-have skill for anyone who wants to work in AI. The programming language may be the same or similar in both environments. However, the purpose of programming AI is different from traditional coding. With AI, programmers write code to create tools and programs that can “learn” from data and make useful decisions or develop practical solutions to challenges. In traditional coding, programmers use programming languages to instruct computers and other devices to perform actions.
Moreover, AI programming involves more than just using a language. You also need a framework and a code editor to design algorithms and create computer models.
How will AI-assisted programming change the industry?
As AI continues to expand, the programming landscape is also changing. But Leo Porter, a professor at the University of California, San Diego, believes AI will increase inclusivity and diversity in programming.
2022 saw the emergence of AI-assisted coding tools like GitHub CoPilot. Although the execution is not perfect, AI-assisted coding eliminates human syntax errors such as missing commas and parentheses. Porter believes the future of coding will be a combination of AI and human interaction, as AI will allow humans to focus on the advanced coding skills needed for successful AI programming.
Educators are updating their teaching strategies to include AI-assisted learning and large-scale language models (LLMs) that can generate code on demand. “We believe the LLM lowers the barrier to understanding how to program,” says Porter. [2].
It’s clear that AI will change the way programmers work. Developers will experience increased productivity and job satisfaction thanks to the assistance of AI.
Will AI replace coding jobs?
ChatGPT was released in 2022 and immediately surprised the coding community by successfully creating simple HTML websites using written instructions. The fear that coding would quickly become obsolete seemed like a natural progression. But like many jobs, AI will transform programming and collaborate with humans to accelerate development. Amazon’s former vice president of AI services told IEEE Spectrum, “I never believe that AI will replace human developers.” [3]
In the future, AI will take over repetitive and mundane tasks. This frees up human developers and programmers to focus on higher-level tasks and the creative aspects of their work.
What is the best programming language to learn for AI? How to choose
When choosing which AI programming language to learn, consider your current abilities, skills, and career aspirations. For example, if you’re new to coding, Python is a great starting point. Many developers start with this flexible and versatile programming language because it is relatively easy to learn and allows you to create complex applications. It also has a wide range of communities, including a rich community dedicated to using Python for AI.
From there, it helps to consider your career goals. For example, if you want to create AI-powered mobile applications, you might consider learning Java, which offers a combination of ease of use and simple debugging. Java is also a great choice for anyone interested in a career that involves implementing machine learning programs or building AI infrastructure.
If your professional interests center on data analysis, you may want to consider learning Julia. This relatively new programming language allows you to run multiple processes at the same time, making it useful for a variety of AI applications, such as data analysis and building AI apps.
However, if you want to work in areas such as self-driving cars or robotics, learning C++ is more beneficial as the language’s efficiency and speed make it suitable for these applications.
Your go-to library for career advancement
Explore career paths, assess skills, and connect with resume guidance while browsing our career resource hub. If you want to learn more about AI, check out these free resources:
Accelerate your career growth with a Coursera Plus subscription. Sign up for monthly or yearly options and gain access to over 10,000 courses.
