How to get a role in AI: key skills and career paths
According to the World Economic Forum, AI has created a huge number of new job opportunities, including 1.9m new roles in AI engineering and AI-enabled data centres.
That’s not to mention the huge amount of other roles that now involve integration of AI to drive greater productivity and innovation.
In this guide, we explore the state of the AI job market and how individuals and organisations can promote careers in AI.
The impact of AI on job opportunities
Boston Consulting Group recently reported that over the coming years, around 50 to 55% of jobs in the United States will be changed by AI. Not replaced but reshaped.
Not only are there direct work opportunities created by artificial intelligence, such as AI governance, AI engineering and AI security, but also hundreds of roles where AI is now an integral competency skill.
From product managers to data analysts and project managers to marketing executives, the number of roles that can benefit from and regularly utilise AI tools is growing by the day.
It is thought that by 2030, 170m jobs will be created across the globe by AI.
The most in-demand roles In AI
There are specific job types that are highly sought after by companies due to an increasing number of businesses adopting AI technology. The PwC 2026 Global AI Jobs Barometer found that there are significantly more jobs available with requirements for AI knowledge compared to other employment opportunities, and they also offer much higher wages.
Below are the most in-demand areas of AI across all sectors of industry:
AI engineering and machine learning
AI engineers and machine learning specialists design, develop, and implement the algorithms and models used in developing AI-powered applications. They utilise programming languages including Python, along with application development frameworks such as TensorFlow and PyTorch.
Although these roles will require advanced problem-solving abilities and statistical knowledge, the availability of pre-built models has reduced barriers to entry.
As the desire for AI solutions grows, so will the need for trained professionals who can build and deploy them.
AI In product management
Product managers of AI-powered applications determine which capabilities or features get developed and why, and make sure that product development teams focus on creating value for users.
People who understand how to connect technological teams to commercial goals and can see what AI can accomplish without being able to write code would be ideal candidates for these positions.
Data science and data engineering
Every AI system relies heavily on data. Data engineers create data pipelines, while data scientists analyse that data to identify patterns. These two areas have a consistent demand for talent and represent a logical next step for individuals looking to specialise within an area.
One effective method of acquiring skills relevant to both of these areas is through participating in a data apprenticeship programme, where you learn by doing on the job.
Cyber security and AI governance
AI is now being used in many systems and often in different ways across a business. Organisations therefore require people to make sure they use this technology safely and responsibly.
This requires two types of specialists: cyber security specialists who will prevent attacks on AI, and those who specialise in AI governance, which is ensuring that all AI is developed fairly, with transparency and compliance. Both of these roles have been increasing rapidly over the last few years.
AI advocates
It can be easy to see AI as dedicated technical roles, however this doesn't mean we should overlook the role that AI plays in the role of every employee.
Organisations also need individuals who can share their knowledge and support others with adopting and onboarding AI. These advocates are likely to be AI enthusiasts who can then play a huge role in highlighting the benefits of AI and helping others to make the most of the AI tools at their disposal.
Effective use of AI champions can often be the difference between a successful and failed AI adoption programme.
How apprenticeships help to launch careers in AI
An AI apprenticeship is one of the easiest ways to begin a career in AI, offering opportunities for school leavers and career changes to enter the industry without further education qualifications.
For example, the Digital and AI Support Level 3 programme is the perfect entry-point for those wanting to kickstart a career in AI. This programme is also highly suitable for those already in a role, who want to develop their AI skills and capabilities.
For those with more experience, there are other strong training options. The AI Automation Level 4 programme is ideal for learners that want to specialise in developing automated workflows and AI systems integration, while the AI Engineer Level 6, is a technical role designed for those that want to build and deploy generative AI and machine learning solutions.
Top AI skills for every role
Whatever path you choose, a common set of skills serves you well: knowing how AI and machine learning function, comfort with data and basic statistics, familiarity with common AI tools, and an understanding of responsible use. Communication matters too, as much of the value comes from explaining results clearly.
Where to get started with AI Skills
The best way to get started is to build experience with different AI tools and develop essential AI literacy skills. Building AI literacy is the first step to becoming fluent in AI language, and then developing effectiveness in AI for your role.
Develop your AI capabilities today by exploring our wide range of AI courses and learning programmes.
AI roles - frequently asked questions
How many roles need AI skills?
A rapidly rising number. More than just the obvious AI jobs, almost every role in marketing, finance, ops, health care, and law requires basic knowledge of how to use or think about AI. It’s going to be most of the workforce.
What does the future of AI roles look like?
There are going to continue to be lots of jobs that require both technical skill and human skill. They’re not mutually exclusive. There will also be new areas of specialisation related to the safe development and deployment of AI systems as well as their governance and oversight.
What are the most important human skills for working with AI?
Blending AI and human skills is going to be a critical skill for workers going forward. This means utilising human creativity with the productivity benefits that AI can bring. Critical thinking, clear communication and using good judgement are all absolutely key when working closely with AI systems.
What are the best AI tools for productivity?
The most frequently used tools are generative AI systems like Microsoft Copilot, Claude, Google Gemini and ChatGPT. However, there are now thousands of AI tools available for a variety of different roles.
It's important to identify the tools that only meet the needs of your role, but the tools that offer a secure platform and an affordable token system.
What tools do data analysts use?
Data analysts use a range of tools, including SQL, Python, Tableau, and Power BI.
Are data analysts in demand?
Yes, there is a strong demand for data analysts in 2026 and beyond. This is because there is a great need for those (data analysts) who can collect, analyse and parse data insights.
AI courses and training programmes
AI role guides
AI skills. Built in.
Microsoft Copilot in all apprenticeship programmes
AI is for everyone, not just technical teams. Every QA apprenticeship includes Microsoft Copilot training for every learner, at no extra cost, delivering AI readiness that benefits your entire organisation.
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