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Engineering Sector in Transition - Skills, AI, and Recruitment Trends
7 minutes | Hays Experts | Article | | Recruiting
The engineering sector accounts for nearly a fifth of the UK workforce, and there is a strong demand for skilled professionals – according to our 2025 Salary & Recruiting Trends Guide, 98% of engineering employers faced skills shortages in the last 12 months. So how can employers bridge the skills gap? And with more than half of employees planning to change roles in the year ahead, which skillsets should they develop to stand out from the crowd?
Read on to discover the most in-demand roles, the impact of current trends such as AI on manufacturing and engineering, essential skills for employees and how employers can expand their talent pool.
With the continued growth of AI tools and technology, the importance of sustainable projects and greater investment in nuclear energy, the engineering sector shows no signs of slowing down – but what roles are the most sought after? And how can professionals move between them to make the most out of their skills?
Project managers, design engineers and project engineers are the most in-demand roles across the main sectors of the industry. These roles are interconnected, with many transferable skills that allow professionals to transition between them, with the sector valuing professionals who can adapt and transfer their skills across different roles.
For example, a project engineer's strong technical background and project management experience make them well-suited for transitioning into project management roles. Similarly, project managers with a solid understanding of technical principles can effectively oversee engineering projects, making them valuable in technical sectors. Design engineers, with their technical proficiency and innovative mindset, can also move into project management roles, where their ability to coordinate and drive innovation is highly beneficial.
Employers who are struggling to find and hire for these roles may want to consider these transferable skillsets to help broaden their search for suitable candidates.
Artificial intelligence (AI) is also influencing skills requirements within the engineering and manufacturing industry. The positives of investing in AI are numerous, for example, within the manufacturing space, benefits include improving operational efficiencies and supporting in product design.
With AI helping to reshape the manufacturing landscape, smarter, data-driven decisions are more likely to be implemented, with things like predictive maintenance helping to speed up processes and reduce the cost of machine failure through the use of historical and real-time data from different parts of an operation to anticipate issues before they arise.
AI can also enhance design and prototyping processes and enable engineers to explore a wide range of design options quickly and efficiently. This reduces turnaround time and helps accelerate innovation, allowing for more creative solutions to be found.
AI-powered systems can also autonomously adapt to changes, enhancing overall efficiency and responsiveness. For example, within factories, AI-driven systems can help reduce production defects and downtime, leading to higher productivity and better quality products.
Uptake of AI across engineering can present several challenges. High initial implementation costs, the need to integrate with existing systems and the requirement for specifically skilled personnel are significant barriers organisations must overcome.
To help alleviate these challenges, employers can adopt phased implementation strategies, to help demonstrate value before scaling up. Investing in training programs to upskill employees is also crucial. Our UK Employment Trends - 2025 Spring Update research shows that less than half (47%) of organisations across all industries are currently offering AI training, despite 39% not having access to the right skills to make the best use of this technology.
With our research showing that over half (56%) of employers are recommending the use of AI tools in the workplace, companies that invest in AI training and development can gain a competitive edge by leveraging advanced technologies to drive innovation and productivity.
The importance of programming languages cannot be understated when it comes to AI. Languages like Python, Java and R are crucial for AI development due to their ease of use, extensive libraries, and strong community support. They enable efficient integration with other systems, offer robust performance and scalability, and provide flexibility across various AI tasks, making them indispensable tools for developing, deploying, and maintaining AI applications.
Working in AI-focused teams also requires a blend of technical and soft skills. Key soft skills include being open to learn and upskill, the ability to effectively adopt change, critical thinking and problem-solving. These skills are crucial for interpreting AI-generated insights, providing creative solutions, and ensuring clear communication across different departments.
According to our research, 76% of engineering employers plan to hire in 2025, presenting an opportunity for those considering changing jobs this year. But with skills shortages being widespread across the industry, what steps can employers take to secure the professionals they need?
Attracting a diverse range of candidates is a key way to expand talent pools, and brings the added benefits of fostering innovation and creativity due to the different perspectives of a diverse team. Strategies include using inclusive job descriptions, broadening recruitment channels, and highlighting diversity initiatives to attract a wider scope of professionals.
Skills-based hiring is also effective, as it focuses on candidates’ abilities rather than formal qualifications, helping employers tap into a broader talent pool, so the most qualified individuals are selected for the job.
AI and data analytics are transforming recruitment by streamlining processes and enhancing decision-making. AI tools can quickly identify top candidates, optimise job descriptions, and improve the candidate experience, and by leveraging these technologies, employers stay competitive and attract the best talent. When it comes to working professionals, optimising their CV for applicant tracking systems (ATS) can make the difference between getting a role or not. Optimise your CV for AI recruitment tools by using clear, concise language, incorporating relevant keywords from job descriptions, and structure your CV in a straightforward format, to ensure compatibility with AI algorithms.
Visit our market insights page to learn more about how we can support your recruitment and talent management strategies, or get in touch with us for your next role in engineering.
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