It’s reasonable to say that the age of generative AI has arrived, and it’s fast transforming the way we work. According to the World Economic Forum’s 2023 Future of Jobs Report, more than 75% of organizations intend to embrace technologies such as AI in the next five years, so it’s no wonder that job prospects in the field are expanding, particularly for developers.
But which programming language is leading the way?
Python is without a doubt the most popular language for AI development. However, a competent programmer can work with AI in almost any programming language, including Java, R, JavaScript, and, of course, C++.
The true challenge is to look beyond the buzz and headlines to determine which language best suits your skill set and hobbies, leaving you well-positioned to meet rising market demand. Continue reading to learn about the languages you should choose if you want to pursue a career in artificial intelligence.
Mastering AI using Python
While all AI-related abilities have witnessed a significant increase in demand, Python stands out as one of the ten most in-demand specialized skills for AI employment, according to a 2022 report from Stanford University.
Why is Python so popular?
It’s simple and intuitive to use, allowing for rapid iterative development. Python is very strongly integrated into the AI ecosystem, with several AI frameworks, tools, and platforms written in the language. It is a popular programming language among data scientists and engineers, as well as in machine learning and robotics.
As a free, open-source programming language, it is also quite accessible; you can learn or study it in depth, and there is lots of community assistance in the form of tutorials, courses, resources, and forum posts.
Rapidly shifting terrain
However, the AI environment is rapidly changing, and many industry experts believe that when it comes to jobs in the area, soft skills such as ethics and communication will be equally as important as technical ones.
According to a recent poll of 692 business leaders from Europe and the United States, 78% say that integrity is one of the most significant abilities to have while dealing with AI and will become even more relevant in the future.
A position such as Lead Machine Learning Scientist at SAP Berlin, for example, requires not only Python proficiency and experience with machine learning frameworks, but also exceptional teamwork abilities, strong leadership and strategic thinking skills, and the ability to collaborate cross-functionally (Interested in the role? You can apply here.
And, while Python is undeniably prominent in the AI sector, the majority of positions will demand you to have expertise working with other languages.
For example, Experian’s Senior Machine Learning Engineer position in London requires advanced Python expertise as well as familiarity with languages such as Java, JavaScript, C++, Go, or C#, as well as solid cloud skills with AWS and Azure.
C++ powers the core infrastructure of AI
While Python is great for top-level dabbling, C++ is commonly used under the scenes. If Python allows you to build quickly and fluidly, the blocks you’re using were most likely created with C++.
Almost every AI framework’s core is written in C++. In fact, if you look at major open-source machine learning packages like TensorFlow and PyTorch (developed by Google and Meta, respectively), you’ll notice that C++ is heavily used.
So, what should you use? It all depends on your work style, talents, and interests – do you like to ship features and experiment with new ideas? When looking into AI careers, you’ll most likely be inclined towards Python.
Or do you prefer to work with outstanding low-level, high-performance technology? Then you’ll have plenty of possibilities with C++, and C++ developers will be welcome on most AI teams.
For example, the AI Frameworks Engineer position at Intel (hybrid, working from Romania, Ireland, or Poland) requires excellent C++ skills, a strong production software engineering background, architecture experience, and a track record of contributing to large-scale, multi-component software systems.
The good news is that chances abound for anyone with a growth mentality and the correct mix of soft skills, regardless of their programming experience.