It's predicted that artificial intelligence (AI) will likely replace some jobs, but it'll also create new positions and become a valuable assistant for many professionals. To succeed in this new landscape, it's important to pick up the skills needed in AI and learn how to make them work for you.
AI needs humans as much as humans need AI—if not more. After all, who’s going to create the algorithms, train, and manage these applications? If you want to stay ahead in this new job market, keep reading.
What are AI skills, and why do they matter?
AI skills are the knowledge and abilities needed to develop, manage, or implement artificial intelligence software. While these skills are in high demand for tech professionals, they're not limited to the tech field—and that’s one of the key reasons they matter.
These applications are rapidly penetrating both society and companies, directly impacting the lives and jobs of many. According to Bloomberg research, the generative AI market is expected to explode and grow $1.3 trillion by 2032.
A 2020 World Economic Forum report estimated that by 2025 (yes, that’s now), 85 million jobs would be displaced due to automation, with employers expected to “divide work between humans and machines equally.” Needless to say, if you're not yet ready for retirement, it's crucial to become AI literate and understand how it could impact your industry—and where to go from there.
Read this next: Understanding the AI Impact on Jobs and What’s Next
7 AI skills to learn in 2025
Here's our list of top skills needed in AI you should consider learning this year—whether you're already in the tech industry or looking to make a career shift.
1. Programming languages
Programming languages are key skills to learn if you're considering shifting to the tech industry to work with AI. Python, R, C++, C#, and Julia are some examples of programming languages required by tech employers today, and they're often used to create, manipulate, manage, and implement AI models.
2. Machine learning (ML)
Often abbreviated as ML, machine learning is what equips AI to make predictions (and decisions) based on data. For example, in the finance industry machine learning is used to detect fraud and credit scoring, based on the consumers behavior and prior transactions. For this reason, ML is considered the core of AI and a relevant skill for those trying to get into this field.
3. Data modeling and processing
Data expertise is more valuable than ever, as it's an essential part of AI and everything we do or consume today (think Spotify Wrapped and Apple Music Replay). Data modeling and processing involves collecting, analyzing, and processing data to help AI algorithms to effectively learn and make decisions.
4. Intelligent user interface (IUI)
Do you have an Amazon Echo at your house? Did you install a ring doorbell in your front door recently? These are examples of intelligent user interfaces (or simply IUI), autonomous and interactive AI—powered machines. Companies that produce these technologies need workers who know how to prototype and evaluate their designs. Usually, UIU is under the umbrella of responsibilities of software engineers and machine learning specialists.
5. Natural language processing (NLP)
Most AI's nowadays are designed to produce human-like responses to prompts. This is possible due to natural language processing (NLP), one of the most important specific skills within AI. The scope of NLP includes sentiment analysis, evaluation, development, testing, and deploying new techniques for natural language understanding in multiple applications, such as chatbots and virtual assistants, for example.
6. AI ethics
The ethics around AI is a debate that shows no sign of ending soon. Issues like its impact on the environment, issues with bias, transparency, and concerns about AI stealing taking work away from humans are being highlighted in multiple media outlets. That's why understanding AI ethics is so important—companies will need professionals who can help them navigate the potential ramifications of developing and implementing AI in their businesses.
Besides tech professionals, this creates a new opportunity for lawyers who specialize in copyright and digital crimes. For example, artists like Billie Eilish, Stevie Wonder, and Jon Bon Jovi worry about AI being used to steal professional artists’ voices and signed an open letter against it in 2024, as reported by CNBC.
7. AI security
AI is everywhere, from social media to robo-advisors in finance. Because these technologies often keep critical information of the companies and the users, such as passwords, emails, and bank accounts, they're vulnerable to cyber attacks. This makes knowledge of AI security to mitigate or prevent these attacks a valuable skill from now on.
Read this next: 6 AI Skills Every Leader Should Have
How to learn AI skills
Now that you know the skills that you may need, here's a list of different ways you can develop them:
Online certification
If you're already familiar with the basics of technology, online courses and certifications are a simple and easy way to learn AI skills. With a quick search, you can find dozens of online teaching platforms, including Google Cloud which offers a machine learning and AI training course from beginner to advanced.
Bootcamp
Intense and often short-term, bootcamps have a hands-on approach to teaching. Basically, they teach you key skills needed in the job marked by making you work on real projects. When looking for one, be mindful to choose a platform highly rated in the tech industry.
College degree
If you want to get into the depths of computer science, programming, mathematics, and data science, a college degree might be worth considering. While some companies prioritize expertise and experience over formal education, a degree can give you an edge over other candidates in certain situations. However, keep in mind that a bachelor's degree typically takes around four years to complete.
Internship and apprenticeship programs
For students, internships and apprenticeship programs offer valuable hands-on experience with AI applications. These opportunities allow you to apply existing skills while also learning new ones. You'll not only sharpen your technical abilities but also develop soft skills like problem-solving and teamwork as you collaborate with other professionals.
Read this next: 6 AI Skills Every Entry-Level Worker Should Have
Industries that demand AI skills
AI jobs aren't limited to tech companies like Meta, Google, or Microsoft. Here are other industries to look into:
- Finance: The finance world (which includes banks, finance institutions, and finance-related apps, for example) often rely on AI for fraud detection and prevention, automated real-time calculations, predictions, and more.
- Manufacturing: This industry uses AI to optimize manufacturing processes and decision making. According to the World Economic Forum, the manufacturing industry also benefits from AI to predict maintenance, automate quality checks, and automate supply chains.
- Healthcare: Similarly to manufacturing, AI in healthcare can be used for data analysis and prevention. For example, healthcare systems powered with AI can analyze a patient's medical histories to find patterns pointing to a potential health risk.
- Sales or retail: AI is already being used in multiple forms in the sales and retail industry. From self-checkout machines to chatbots and virtual assistants that provide customer service and guidance to buyers.
Make AI work for you
AI is here to stay—and while it may replace some jobs, it’s also creating new opportunities. In order to survive, it's key to learn how you can adapt and reposition yourself as a professional. Learning AI skills is a good first step. After that, you can explore how to leverage AI for job search and interview prep.