What can you do with an Artificial Intelligence degree?

If you’re considering studying Artificial Intelligence (AI), one of the first questions you’re likely to ask is: what can you actually do with an Artificial Intelligence degree?

The answer is more expansive than ever. The World Economic Forum's Future of Jobs Report 2025 identifies AI and Machine Learning Specialists among the fastest-growing roles globally, with projected net growth of 82% by 2030. In the United States alone, AI-related job postings increased from 1.4% of all postings in 2023 to 1.8% in 2024, whilst demand for generative AI skills grew by almost a factor of four year-on-year. Download the Stanford HAI AI Index Report 2025 (PDF).

These figures reflect a profound shift: Artificial Intelligence careers are no longer confined to computer science departments or technology companies. They span healthcare, finance, sustainability, engineering, public policy and beyond. Graduates work in roles that design intelligent systems, apply AI to real-world problems and shape how organisations use data and automation responsibly.

An Artificial Intelligence degree can lead to a wide range of careers, from technical and data-focused roles to applied, interdisciplinary and strategic positions. The right path depends on how you want to use AI. This could be:

• building AI systems 
• applying them in context 
• guiding their responsible use.

What careers can an Artificial Intelligence degree lead to?

Artificial Intelligence careers are more diverse than many people expect. Rather than leading to a single job title, studying AI opens pathways into different types of roles, depending on your interests and strengths.

Technical AI roles

These roles focus on building and improving AI systems:

• Artificial Intelligence engineer 
• machine learning engineer 
• data scientist 
• AI researcher.

They typically involve working with algorithms, data and models to develop intelligent solutions. 

Many roles evolve over time, and job titles often differ between organisations. The underlying skills and ways of working are more important than specific labels. 

Applied and interdisciplinary roles

These roles apply AI within specific sectors or problems:

• AI specialist in business or finance 
• healthcare or biomedical AI analyst 
• AI roles in sustainability, energy or transport 
• robotics and automation roles.

Here, technical knowledge is combined with domain expertise to solve practical challenges.

You can explore specific examples of roles in more detail in our guide to the top jobs in Artificial Intelligence. 

Strategic and leadership-oriented roles

As careers progress, AI graduates may move into roles such as: 

• AI consultant or advisor 
• technical product manager 
• AI strategy or innovation lead.

These positions focus less on day-to-day coding and more on decision-making, ethics and organisational impact. 

Industries that hire AI graduates

AI skills are used far beyond the technology sector. Graduates work across a wide range of industries, including:

• technology and software: developing intelligent products and platforms
• business and finance: support decision-making, automation, and customer insight, as explored in how Artificial Intelligence is changing business
• healthcare: supporting diagnostics, research, and patient care
• sustainability and environment: modelling systems and optimising resources, including how Artificial Intelligence can enable a sustainable future
• engineering and manufacturing: improving automation and complex systems.

This breadth means Artificial Intelligence careers are often shaped by where and how you want to apply the technology, not just by technical preference. 

How AI careers develop over time

AI career paths typically evolve rather than follow a fixed trajectory:

• Early career: applying technical skills, working with data and supporting AI projects. 
• Mid-career: specialising in a sector or method or taking ownership of systems and solutions.
• Later career: influencing strategy, leading teams or shaping how AI is used responsibly at scale.

Studying AI provides a foundation that supports long-term progression, not just entry-level roles. As the World Economic Forum reports, 69% of organisations globally plan to hire new people with skills to design AI tools, whilst 62% are hiring those skilled in working alongside AI (WEF Future of Jobs Report 2025). This demand spans technical implementation and strategic oversight alike.

Understanding AI degree types and career paths

Not all Artificial Intelligence degrees are the same. The level of qualification you pursue influences both the depth of your learning and the Artificial Intelligence career paths available to you.

Bachelor degree (BSc) in Artificial Intelligence

A Bachelor degree provides foundational knowledge in AI principles, programming, mathematics and data science. It typically takes three to four years of full-time study and prepares graduates for entry-level technical roles such as junior data analyst, AI developer or software engineer with an AI focus.

Bachelor programmes emphasise breadth: students learn core concepts across machine learning, algorithms and ethics, alongside transferable skills in problem-solving and critical thinking. Graduates often begin their careers supporting AI projects or working within larger teams.

Masters degree (MSc) in Artificial Intelligence

A Masters degree offers advanced, specialised training in AI methods and applications. It typically takes one to two years (or longer if studied part-time) and is suited to those seeking deeper technical expertise, career progression or a shift into AI from another field.

Masters programmes focus on depth: students engage with topics such as deep learning, neural networks, reinforcement learning and the ethics of Artificial Intelligence. Many programmes include a substantial research project, enabling graduates to apply their learning to complex, real-world challenges.

An MSc can lead to mid-level and senior Artificial Intelligence jobs such as machine learning engineer, AI specialist or technical lead. It also provides a pathway to doctoral research for those interested in advancing in the field academically.

Conversion programmes and Postgraduate Certificates

For professionals without a traditional computing or mathematics background, conversion programmes and Postgraduate Certificates offer a route into AI. These shorter qualifications (often six to twelve months) provide essential technical skills and can serve as a stepping stone to a full Masters degree or direct entry into AI careers.

The choice of degree depends on your current experience, career ambitions, and how quickly you wish to enter or advance within the field. For those already working, part-time or online options provide flexibility without disrupting employment.

Is an Artificial Intelligence degree worth it?

For many learners, this is the key question, particularly when considering time, effort and long-term career value.

An AI degree can be valuable because:

• the demand for AI-related skills continues to grow across industries 
• skills developed in AI, such as data analysis, problem-solving and systems thinking, are transferable 
• AI knowledge supports both technical and leadership career paths.

That said, its value depends on your goals. AI study suits those who are curious, analytical and interested in how technology shapes decisions and systems, rather than those seeking a single, narrowly defined job.

For learners considering whether an Artificial Intelligence degree is worth it, its value depends on how well it aligns with their interest in data, systems and long-term problem-solving. 

Do you need a technical background to study AI?

Not all learners come to AI from the same background.

While some AI roles are highly technical, studying AI also develops: 

• data literacy 
• logical and critical thinking 
• the ability to apply AI tools responsibly in context.

Many programmes support learners from related disciplines, helping them build technical confidence alongside conceptual understanding. 

Responsible and ethical AI careers

As AI becomes more influential, responsible and ethical use is increasingly important.

Many Artificial Intelligence careers now involve: 

• considering bias, transparency and accountability 
• ensuring AI systems are used fairly and safely 
• balancing innovation with social and organisational responsibility.

Understanding ethics and responsible AI usage is a core part of working in AI, particularly in leadership and decision-making roles.

What to do next

If you’re exploring a future in Artificial Intelligence:

• learn more about specific AI job roles and how they differ 
• understand the key skills required for different AI career paths 
• explore how AI is applied in your industry or the industries you’d like to go into
• consider how structured study can support your transition into AI-related work.

These steps can help you decide how an Artificial Intelligence degree fits your ambitions. 

Study AI online with the University of Leeds

The University of Leeds offers a flexible, rigorous online MSc in Artificial Intelligence, designed for professionals who recognise AI's growing impact across sectors.

Delivered 100% online over 24 months (part-time), the programme is taught by expert academics from the School of Computer Science - ranked among the top institutions globally and a partner of the Alan Turing Institute, the UK's national institute for data science and AI.

The curriculum covers essential and advanced topics including:

• machine learning
• neural networks and deep learning
• deep learning for computer vision and natural language processing
• reinforcement learning and modern learning paradigms
• ethics of Artificial Intelligence.

You'll also complete an independent AI project, applying your knowledge to real-world challenges under academic supervision.