Gain the technical and problem-solving skills to build AI systems, work with data, research new applications, develop responsible approaches to AI and apply intelligent technologies to real-world problems.
Artificial intelligence is already changing how we diagnose disease, detect fraud, move goods, understand customers, design products and make decisions. That means a degree in artificial intelligence prepares you for more than just one job, or even one industry.
You don’t necessarily need to work somewhere with ‘AI’ in the company name. These skills are increasingly being applied across technology, professional services and other areas of the Australian economy. Jobs and Skills Australia (JSA) has found demand concentrated in technical fields, while also identifying AI skills in roles outside traditional ICT and data occupations.
What does an AI degree prepare you for?
AI might look like magic when you only see the finished product. Studying it means learning what’s up the magician’s sleeve.
Depending on your course and specialisation, you’ll develop capabilities across areas such as programming, mathematics, statistics, data handling, machine learning and computational problem-solving. You’ll learn how intelligent systems are designed and trained, how to work with large and complex datasets and how to evaluate whether the solutions you create actually work.
Of course, technical capability is only part of the picture. AI increasingly raises questions about ethics, privacy, bias, transparency and accountability. Understanding when and how AI should be used can be just as important as knowing how to build it.
You’ll also develop transferable capabilities such as:
- analytical and computational thinking
- problem-solving
- working with and interpreting data
- designing, testing and evaluating technical solutions
- communicating complex ideas to different audiences
- collaborating on technical projects
- critically evaluating AI outputs and limitations
- considering the ethical and responsible use of technology.
The result is a foundation that can take you in several directions rather than training you for a single job title.
What jobs can you get with an AI degree?
There isn’t one standard ‘AI career’. Depending on your interests, you might want to build the technology itself, use it to make sense of data, research what’s possible next or help organisations decide how AI should be used. Here are some potential options:
Build and engineer AI
If you like the idea of making things work, you could pursue roles that design, build and deploy AI-powered systems.
Potential roles include:
- AI engineer
- machine learning engineer
- software engineer
- data engineer
- AI architect.
AI engineers, for example, develop the tools, systems and processes that allow AI to be applied to real-world problems. JSA identifies ‘AI engineer’ as an emerging role in Australia’s labour market, currently accounting for 41.1% of Australian job titles explicitly containing ‘AI’ or ‘Artificial Intelligence’.
That doesn’t mean 41.1% of all AI-related jobs are AI engineers – plenty of jobs requiring AI skills have completely different titles – but it does show how prominent engineering is among explicitly AI-labelled roles.
Research what’s next
Some people are less interested in applying today’s AI than discovering what tomorrow’s might be capable of. Research and applied science roles can involve developing new models, methods and applications or solving complex problems in areas such as computer vision, machine learning, robotics and intelligent systems.
Potential roles include:
- AI researcher
- research scientist
- computer vision engineer
- machine learning researcher.
This pathway can be particularly attractive if you enjoy experimentation, advanced mathematics and asking questions where the answer isn’t already known.
Turn data into decisions
AI and data science are deeply connected. Organisations generate enormous amounts of data, but collecting it isn’t the useful bit. People who can analyse it, identify patterns and turn those findings into meaningful insights can support decisions across business, government, science and many other fields. Potential roles include:
- data scientist
- data analyst
- business intelligence developer
- data engineer.
JSA’s analysis of Australian job advertisements from 2018 to 2023 found ‘data scientist’ was the most common job title among advertisements requiring AI skills, illustrating just how closely the two fields intersect.
Help organisations use AI responsibly
Not every AI career involves spending your day elbow-deep in prompts. As organisations adopt AI, they also need people who understand its risks, limitations and responsibilities. AI governance can involve developing policies and frameworks, assessing risk and helping organisations make informed decisions about how AI is developed and used. Potential roles include:
- AI governance officer
- responsible AI specialist
- AI policy and risk roles.
This is an emerging area where technical understanding can intersect with governance, ethics, law, policy and business.
Build specialised intelligent systems
AI can also become part of something much bigger – sometimes literally. Robotics, autonomous systems and other specialised technologies combine AI with areas such as engineering, computer vision, sensors and control systems.
Potential roles include:
- robotics engineer
- computer vision engineer
- autonomous systems specialist.
If you’re interested in the point where software starts interacting with the physical world, this could be your corner of AI.
Is demand for AI skills actually growing?
AI is changing the Australian workforce, but the story is more nuanced than ‘every job is becoming an AI job’.
JSA’s earlier analysis of more than 7 million Australian online job advertisements from 2018 to 2023 found AI skills were concentrated particularly strongly in data and technology occupations. Machine learning and deep learning were among the skills experiencing high demand.
More recent JSA research gives us an important piece of the puzzle. Its national study of generative AI found that the technology is more likely to augment human work than simply replace it. Routine tasks may increasingly be automated, while AI also changes how existing jobs are performed and the skills workers need.
In other words, the opportunity isn’t limited to becoming an ‘AI specialist’ – knowing how AI works (and how to use, evaluate and govern it effectively) can become valuable within careers that already exist.
Which industries hire AI graduates?
Almost any industry that uses large amounts of data, automation or digital technology has potential applications for AI. Here’s a non-exhaustive list.
Healthcare: AI can support areas such as medical imaging, data analysis, diagnostics, research and the development of health technologies.
Finance: Banks, insurers and financial technology companies use AI and machine learning for applications including fraud detection, risk analysis, forecasting and customer services.
Retail: AI can help retailers understand customer behaviour, forecast demand, personalise experiences and manage increasingly complex supply chains.
Transport and logistics: From route optimisation and demand forecasting to autonomous systems, AI can help organisations move people and goods more efficiently.
Digital marketing: AI can be used to analyse audiences, identify patterns in customer behaviour, personalise content and support marketing decision-making.
Government and the public sector: Government agencies can use AI and data-driven technologies to analyse information, improve services and support planning and policy decisions.
Do I need an undergraduate or postgraduate AI degree?
Undergraduate study
If you’re beginning your university studies, an undergraduate degree can give you the broader technical foundations you’ll need before specialising. Depending on the degree you choose, this can include programming, mathematics, statistics, data science, algorithms and machine learning alongside broader computing skills.
In other words, you don’t need to arrive already knowing how to build a neural network.
At RMIT, undergraduate options allow you to build AI capability through areas such as data science and computing. For example, the Bachelor of Data Science develops skills across programming, statistics, mathematics, machine learning and data wrangling, with AI available as an area of specialisation.
Postgraduate study
Already have a degree? Postgraduate AI study can help you change direction, add specialised AI capability to an existing career or deepen technical knowledge you’ve already developed.
RMIT’s Master of Artificial Intelligence develops advanced knowledge in designing and implementing AI systems, with project and research pathways available.
For graduates coming from outside computing, the Master of Data Science and Artificial Intelligence is specifically designed as a conversion degree. You can enter from disciplines including business, science, engineering, health, economics and the social sciences, to build your foundations in programming, data analysis, computational thinking and AI.
So postgraduate AI isn’t necessarily about doing more of the same. It can also be the bridge between what you already know and where you want to go next.
Why study AI at RMIT?
#7 in Australia and top #100 universities globally for Data Science & Artificial Intelligence*.
*QS World University Rankings by Subject 2026
Build practical experience
RMIT’s AI courses emphasise practical skills through real-world projects, cloud platforms and authentic assessments, connecting technical knowledge with the problems you’ll encounter beyond university.
Connect with industry
WIL opportunities are available across AI and related disciplines, with projects ranging from 120–240 hours and internships from 120 hours up to 40 weeks, depending on the course and opportunity.
Work with AI, not just use it
RMIT’s approach extends beyond technical specialisation to developing practical and responsible AI capability, including critical thinking, ethical understanding and applied problem-solving.
Where could an AI degree take you?
The better question is: what problems do you want to solve?
You could build machine learning systems, analyse complex datasets, develop robots, research new technologies or help organisations use AI responsibly. You could work in technology, healthcare, finance, government, retail, logistics or an industry currently discovering what AI means for it.
Job titles and technology will change, but a strong AI education gives you something more durable: the technical foundations, critical thinking and practical experience to understand what the technology is doing, what it could do next and where you can take it.
