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How is AI influencing job roles and skill requirements?

In this article, Lina Kramer explores how AI is creating new jobs, and changing existing roles and skill requirements.

In the previous step, you reflected on how AI transforms the employment landscape. In this step, you will learn about AI’s influence on job roles and skills.

AI’s influence on job roles and skills: a data-driven perspective

As you have learned so far, in the ever-evolving landscape of technology, artificial intelligence (AI) is a powerful driver and tool. Unsurprisingly, it also has a significant impact on job roles and skill requirements across industries and sectors. AI creates new opportunities for us and can help us transition into new roles that are more adapted to the changing needs of the market. According to a report by McKinsey, by the year 2030, up to 375 million workers worldwide will switch occupational categories and learn new skills due to the impact of AI and automation [1]. However, AI also poses challenges, such as displacing jobs and requiring constant reskilling. Let us delve into the profound changes AI has brought about in the employment landscape, including the transformation of traditional roles through augmentation and the changes in skill requirements.

AI as a creator of new job roles and skill requirements

One of the main aspects of AI’s influence on job roles is that it is creating new job roles that require a combination of technical and human skills. Positions that were unheard of a few years ago have now become integral parts of the workforce [2].

Roles such as those below have emerged driven by the need to develop and manage AI systems:

  • AI Ethics Specialists
  • Data Scientists
  • Machine Learning Engineers
  • Robotics Process Automation (RPA) Developer
  • AI Product Manager
  • AI Trainers.

These new roles can offer exciting opportunities for those who are interested in working with cutting-edge technologies. Naturally, the establishment of these new job roles has led to a shift in skill requirements. Traditional skill sets are being supplemented with AI-specific proficiencies. New jobs not only demand a deep understanding of AI algorithms and technologies, but also require expertise in programming, data analysis and domain-specific knowledge. Programming skills have expanded to include languages like Python and R, which are widely used in AI development. Data analysis now encompasses proficiency in data preprocessing, feature engineering and algorithm selection for machine learning models. Moreover, a strong grasp of statistical concepts and mathematical foundations has become crucial for understanding the intricacies of AI algorithms. Finally, possessing domain-specific knowledge in addition to a good understanding of machine learning is an imperative requirement for roles such as AI Ethics Specialist and AI Trainer. You will need to acquire these competencies and qualifications if you wish to enter these new job roles.

Evolving skill requirements for existing job roles

AI’s influence is not confined to new job roles alone. Many traditional job roles are being augmented by AI technologies to enhance efficiency and effectiveness. To give you an estimate, a PwC survey highlights that 77% of CEOs intend to increase investments in digital transformation initiatives in the coming three years, indicating the growing prevalence and integration of AI into various business operations [3].

Predictably, in these augmented roles, the skill requirements have also evolved. According to the World Economic Forum, the skill sets for jobs have changed by around 25% since 2015 and by 2027 that number is expected to double [4]. While human qualities such as empathy and critical thinking remain important, there is now an added emphasis on understanding AI systems to effectively collaborate with them. Marketing professionals now require skills in AI-driven data analysis tools to glean insights from consumer behaviour patterns. Traditional manufacturing jobs have evolved into roles where employees collaborate with AI-powered robots, necessitating skills in robotics and automation. Even creative fields like graphic design have seen the need for AI familiarity to work with AI-assisted design tools.

However, so far, companies frequently experience difficulties in filling AI and data science job openings. They attribute these challenges primarily to skills shortages (see graphic below). Hence, I recommend developing the capacity to effectively work with AI systems; this entails recognising their limitations and biases. This does not necessitate becoming AI experts, but rather acquiring AI literacy to make well-informed decisions. For instance, healthcare professionals leverage AI for diagnosing medical conditions but must possess advanced medical knowledge to interpret AI-generated insights accurately. Furthermore, effective communication skills play a pivotal role in facilitating collaboration between technical and non-technical teams, ensuring that AI solutions align harmoniously with organisational goals and values.

Top 5 barriers to filling AI-related vacancies: lack of technical skills 65 per cent, lack of work experience 40 per cent, lack of industry knowledge 25 per cent, salary demand too high per cent, location/poor transport links 17 per cent. Graphic: Barriers to filling vacancies in the UK in 2020 [5]

AI as a facilitator of skill transition and career discovery

Considering these diverse skill requirements, a multidisciplinary approach is pivotal. In addition, adaptability and rapid learning are indispensable traits, especially considering the constant advancements in AI technologies. Luckily, AI can also function as a facilitator for skill transitions and career discovery. For instance, a pilot study conducted by the World Economic Forum in collaboration with Unilever, Walmart, Accenture and SkyHive used AI to map individuals’ skills and match them to emerging job roles [6]. The study found that we often underestimate our skill sets due to inherent bias. However, when AI assessed the skills, the number of identified skills more than tripled [6]. AI has the potential to also unveil previously unexplored career opportunities for you.

Furthermore, AI can offer personalised learning recommendations. The study also found that it would only take six months for people to be reskilled for new roles in completely different functions [6]. This shows how AI can help us transition into new roles by providing a more accurate picture of our skills and potential. AI can be a valuable ally in crafting your career path and aid in closing the skills gap within the workforce.

AI’s potential impact on worker well-being

Conversely, there is a need to recognise the potential negative impact of AI on workers and their well-being. For example, a survey conducted by PwC also found that 37% of workers expressed concerns about job loss due to automation [7]. This highlights that AI can engender pessimism about the future and potentially lead to burnout as we try to keep up with the continuous learning requirements. Building and nurturing a supportive and inclusive work environment is crucial in addressing these concerns and ensuring our well-being in an AI-augmented world.


To sum up, AI’s influence on job roles and skills has led to the creation of novel positions and an evolution of existing ones. New jobs have emerged, demanding expertise in AI technologies, data analysis and domain-specific knowledge. Skill requirements for traditional roles have evolved with a growing emphasis on AI literacy and collaboration with AI systems. As AI continues to advance, it is imperative for individuals and organisations to stay adaptable and prioritise continuous learning to be prepared for the future of work.

Now that you have completed this step, you have gained insights into how AI impacts jobs and skill requirements. In the next step, you will learn to navigate faster-changing careers.


  1. Manyika J, Lund S, Chui M, Bughin J, Woetzel J, Batra P, Ko R, Sanghvi S. Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages. McKinsey Global Institute. 2017 Nov 28.
  2. World Economic Forum. AI skills gaps and the future of jobs. 2023 May 1.
  3. PwC. 24th Annual CEO Survey. 2020.
  4. World Economic Forum. Here’s why the world of work urgently needs to put skills first. 2022 Mar 29.
  5. Department for Digital, Culture, Media & Sport. 9 key findings from Understanding the UK AI labour market: 2020 report. 2021. May 18. Contains public sector information licensed under the Open Government Licence v3.0.
  6. World Economic Forum. Jobs, work, skills: How to prepare for the future of automation and AI. 2021 Jun 2.
  7. PwC. Workforce of the future: The competing forces shaping 2030. 2018. Available from:

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