This Master’s Thesis examines the impact of artificial intelligence (AI) on the labour market and, specifically, on the logistics-energy sector, analysing how accelerated technological adoption reshapes tasks, roles, professional identities, and organizational dynamics. Using a mixed-method approach that integrates documentary review, comparative analysis, and qualitative field evidence, the study investigates how AI transforms not only the technical structure of work but also the frameworks for decision-making, coordination, and purpose within contemporary organizations. Findings indicate that technology alone does not determine the future of employment; rather, it is shaped by the human, organizational, and social conditions under which AI is adopted. While AI can augment human capabilities, it may also erode professional identity and create friction when introduced without clear criteria, transparent boundaries, or appropriate support mechanisms. The research highlights that the true competitive advantage in the AI era does not stem from access to sophisticated models—which are becoming increasingly standardized—but from the quality and maturity of the human system: how teams converse, coordinate, make decisions, and learn collectively. The most significant risks arise not from technological substitution itself but from the destabilization of human roles when AI is implemented without a sociotechnical and purpose-driven framework. The study puts forward recommendations for companies, public institutions, and workers. These include: adopting human-centred approaches to AI integration; redefining roles and responsibilities; strengthening interdepartmental coordination; fostering continuous upskilling and reskilling; prioritizing internal mobility over workforce displacement; and developing regulatory and educational measures that ensure a fair transition. The analysis also links these insights to the Sustainable Development Goals—particularly SDG 8 and SDG 9—arguing that technological sustainability requires human sustainability. The thesis concludes that the future of work will be shaped by today’s collective decisions. Organizations capable of integrating AI through an ethical, sociotechnical, and human-value-oriented approach will generate more resilient, inclusive, and sustainable environments. Technology will become standardized; humanity will not. Therefore, the key question is not which AI systems are implemented, but what kind of organization emerges through their implementation.
Ángel Ordóñez (Thu,) studied this question.