Career guide
How to start a career in artificial intelligence
Artificial intelligence work ranges from building machine learning models to helping teams use AI tools safely and well. Some roles are deeply technical, while others focus on automation, testing outputs, writing prompts or explaining AI to non-specialists.
Because the field changes quickly, employers often look for people who learn fast, check their results carefully and understand the limits of AI. A mix of programming, data skills and good judgement is a strong foundation for most paths.
What the work looks like
- Preparing and labelling data for training or evaluation
- Building, testing and improving models or AI-powered workflows
- Writing and refining prompts for language models
- Checking AI outputs for errors, bias and unsupported claims
- Documenting how a system works and where it should not be used
First roles
- Junior machine learning or AI engineer
- AI automation or prompt specialist
- Data analyst with a focus on AI tools
- AI evaluation or quality assurance assistant
How to start
- Learn Python and basic data handling; the Python test helps you check your level.
- Understand core machine learning ideas, then prove them with the machine learning test.
- Practise using AI tools at work and learn how to check what they produce with the guide to verifying AI output.
- Build small projects, such as a document summariser or an automated report, and explain their limits honestly.
- Learn the principles of responsible AI use, including privacy and fairness.
- Present projects and tools clearly in a CV made with the CV builder.
Skills employers look for
Your CV for each market
Articles
Common questions
- Do I need a master's degree or PhD to work in AI?
- For research roles, advanced degrees are common. For many applied roles, such as automation, evaluation or building products on existing models, employers often focus on practical skills, projects and the ability to learn quickly.
- Is AI only for programmers?
- No. Many roles involve using AI tools within marketing, customer service, operations or writing. Knowing how to write good prompts and check outputs is useful across a wide range of jobs.
- How do I keep up with such a fast-moving field?
- Focus on fundamentals that change slowly, such as data, statistics and clear evaluation. Then follow a few reliable sources and try new tools on small, real tasks rather than chasing every announcement.