How to Get a Job in AI: The Skills, Education and Experience You Need

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Artificial intelligence is far from the niche field reserved for researchers and tech giants it once was. Marketing, health care, finance, customer service and many other industries are embracing AI, and it is reshaping the way businesses operate. 

This embrace is driving growing demand for professionals well-versed in AI. Understanding how to get a job in AI can feel overwhelming at first, especially when you don’t know where to start. Do you need a degree? What skills matter, and how much experience do you need? 

The good news is that there are multiple routes into AI, and anyone can get involved in the rapidly growing field. 

What AI Jobs Actually Involve

AI is a broad field that is constantly evolving. AI has added over 1 million new jobs according to LinkedIn data, and this figure is expected to increase. There are numerous AI-focused roles, with these being among the most common:

• Data scientist: Analyze data and develop models to generate insights.
• AI engineer: Integrate AI models into systems and applications.
• Machine learning engineer: Build and deploy models that allow systems to learn from data. Even low-paid machine learning engineers can earn around $124,000 per year. 
• AI product manager: Oversee the development of AI-driven products from a business perspective.

The Core Skills You Need

You don’t need to master everything at once to get a role in AI, but there are a few integral areas you should build a foundation in. 

Technical Skills

Programming skills are essential. Python is the most widely used language in AI thanks to its strong ecosystem and ease of use. 

It is also important to learn how to work with data, such as processing and analyzing datasets. Machine learning is an integral part of AI, so it’s necessary to grasp its core concepts, such as basic algorithms and model evaluation. You don’t need to start building a cutting-edge model from the get-go, but you should develop an understanding of how models are used and trained. 

Familiarity with tools and libraries like TensorFlow and PyTorch is also beneficial. 

Mathematical Foundations

AI relies on mathematics, but the level of knowledge you need depends on the role. A basic understanding of statistics is important, though, as it underpins how models handle uncertainty and make their predictions. 

Linear algebra and probability are other concepts you may encounter and should be studied accordingly.

Soft Skills

Technical skills alone aren’t enough to land you a job in AI, and the same applies to countless other types of work across all industries. Employers tend to value candidates with strong communication skills and a self-motivated, professional approach to work. 

Work on these soft skills, along with your critical thinking, time management, teamwork and other non-technical traits to give yourself the best chance of standing out beyond what is written on your application.  

Do You Need a Degree?

A traditional degree in computer science, data science or a related field can help you get a job in AI and boost your CV’s chances of standing out. However, earning a degree is not the only route to getting a role in AI. Online courses and bootcamps offer structured programs to help you gain theoretical and practical skills. 

Employers are more concerned about what you can do than where you learned to do it, so focus more on building a strong portfolio of projects that prove experience and expertise. If you do decide to go the degree route, still build a portfolio of practical experience alongside it. 

How to Gain Experience Without a Job

Even entry-level AI jobs can require some experience. It’s best to be proactive about this in the following ways.

Conduct Personal Projects

Personal projects, such as predicting house prices using historical datasets or building a simple sentiment analysis model for customer reviews, can showcase your abilities. Try solving realistic problems, such as creating a report detailing insights from publicly available datasets you’ve analyzed. 

These projects don’t have to be perfect. They just need to showcase your processes and what you’ve learned. 

Contribute to Open-Source

Open-source projects are a great way to collaborate with others and gain experience working with them on real codebases. Even small contributions can help you understand industry practices, improve your coding skills and show potential employers what work you can do in a team environment. 

Participate in Competitions

Data science and machine learning competitions that simulate real-world challenges can help sharpen your skills. They are also good for learning from others and building a track record of practical work that you have done. Any awards or prizes you win in these competitions can be added to your CV. 

Seek Other Jobs That Use AI 

AI was used in at least one business function by 88% of organizations in 2025, an increase from 78% in 2024. Furthermore, the percentage of employees using AI day-to-day has risen to 12% from 10%, according to a 2026 report. 

Consider getting a job that uses AI daily to build hands-on experience if you’re struggling to get an AI-specific role.

How to Stand Out to Employers

Standing out to employers is an important part of landing a job in any industry, particularly AI, as more people seek jobs in what is seen as the future of work. It is important to tailor your application to each employer you’re applying to. Many people simply apply to as many places as possible, treating applications like a numbers game. 

Aiming for quality over quantity with your applications is worth the effort, as an employer is more likely to take it to the next stage if you gear the application toward what they’re looking for and if they can see you’ve put in extra effort. Hiring managers often have to sift through countless applicants, so they will appreciate someone who proactively demonstrates that they can offer what the role requires.

Show a desire to keep learning, too. Employers aren’t hiring you for what you’ve done before, but for what you’ll do with them. Find ways to show your interest in AI and any personal goals you have in the field that you can achieve alongside your potential employer. 

A Proactive Approach to Getting a Job in AI

Getting a job in AI is more accessible than ever before, thanks to the breadth of opportunities now available. There is no single defined path to getting a job in the field, and you can start gaining experience anytime from the comfort of your home. 

Choose a path that is right for you, develop a portfolio and be sure to learn and demonstrate soft skills along the way. Tailor your applications to each employer, and you’ll be well placed to start securing interviews.