{"id":1242,"date":"2025-07-25T11:47:00","date_gmt":"2025-07-25T11:47:00","guid":{"rendered":"https:\/\/worktransition.eu\/?p=1242"},"modified":"2026-02-06T11:58:36","modified_gmt":"2026-02-06T11:58:36","slug":"preparing-for-the-labour-market-challenges-of-ai-in-commerce-and-mechanical-engineering-in-hungary","status":"publish","type":"post","link":"https:\/\/worktransition.eu\/ro\/preparing-for-the-labour-market-challenges-of-ai-in-commerce-and-mechanical-engineering-in-hungary\/","title":{"rendered":"Preparing for the Labour Market Challenges of AI in commerce and mechanical engineering in Hungary"},"content":{"rendered":"\n

EN<\/strong><\/p>\n\n\n\n

Artificial Intelligence (AI) is expected to profoundly reshape labour markets and working practices across Europe. While AI has the potential to enhance productivity and organisational efficiency by automating routine tasks, its most significant impact lies in the transformation of job content and skill requirements. Rather than replacing human work, AI increasingly supports employees in performing analytical, creative, and decision-making tasks that require adaptability, judgement, and social intelligence. At the same time, certain occupations and tasks face higher exposure to automation, making proactive workforce preparation essential.<\/p>\n\n\n\n

Within the Hope4AI project, a dedicated research initiative was undertaken to examine how AI is affecting employment structures, skills demand, and organisational practices in Hungary, with a particular focus on the commerce and mechanical engineering sectors. The study analyses the current and expected use of AI technologies, the degree of task-level exposure across occupations, and the readiness of employees and employers to adapt to technological change. Special attention is given to leadership attitudes, employee perceptions, and the institutional conditions shaping successful AI adoption.<\/p>\n\n\n\n

The findings indicate that AI does not lead to large-scale job losses but instead drives a fundamental reconfiguration of work. Roles characterised by routine and standardised tasks face higher transformation pressure, while occupations requiring complex human skills, contextual judgement, and cooperation remain more resilient. The research highlights the growing importance of continuous upskilling, AI literacy, and soft skills such as critical thinking, flexibility, and collaboration.<\/p>\n\n\n\n

Overall, the study demonstrates that the economic and social benefits of AI depend on strategic governance, effective change management, and investment in human capital. By fostering cooperation between technology and human expertise, AI can contribute to sustainable productivity growth, improved job quality, and increased competitiveness, provided that the transition is actively managed and supported by coherent education and labour market policies.<\/p>\n\n\n\n