Συντάχθηκε 18-07-2025 10:27
Τόπος:
Σύνδεσμος τηλεδιάσκεψης
Έναρξη: 24/07/2025 12:00
Λήξη: 24/07/2025 13:00
ΠΟΛΥΤΕΧΝΕΙΟ ΚΡΗΤΗΣ
Σχολή Μηχανικών Παραγωγής και Διοίκησης
Πρόγραμμα Μεταπτυχιακών Σπουδών
Διοίκηση της Τεχνολογίας και της Καινοτομίας
ΠΑΡΟΥΣΙΑΣΗ ΜΕΤΑΠΤΥΧΙΑΚΗΣ ΕΡΓΑΣΙΑΣ
Πέμπτη, 24 Ιουλίου 2025, 12:00
https://teams.microsoft.com/l/meetup-join/19%3ameeting_YjcwMmI1ZDQtZDM4MC00YjYxLWFlYzAtNzU2Y2NkOTdlNDk0%40thread.v2/0?context=%7b%22Tid%22%3a%22b8940084-7e60-46ee-b148-0fcec483d833%22%2c%22Oid%22%3a%22840c232b-4930-4132-ae81-b88bded4c471%22%7d
Ονοματεπώνυμο: ΚΑΛΗ ΣΟΦΙΑ
Θέμα:
Title: Impact of automation and artificial intelligence in the future of work: A strategic perspective
Εξεταστική Επιτροπή
- ΜΟΥΣΤΑΚΗΣ ΒΑΣΙΛΗΣ, Καθηγητής (επιβλέπων)
- ΤΣΑΦΑΡΑΚΗΣ ΣΤΕΛΙΟΣ, Αναπληρωτής Καθηγητής
- ΖΟΠΟΥΝΙΔΗΣ ΚΩΝΣΤΑΝΤΙΝΟΣ, Καθηγητής
Περίληψη
The Fourth Industrial Revolution is transforming the global economy through the rapid proliferation of automation and artificial intelligence (AI). These technologies are no longer confined to theoretical exploration but are embedded in practical, strategic applications across diverse sectors. This thesis investigates the multifaceted impact of AI and automation on the future of work, adopting a strategic perspective that integrates technological, organizational, ethical, and labor market dimensions. The research begins by tracing the evolution and typology of AI, from narrow, task-specific systems to emerging concepts of general and superintelligence. Through an extensive literature review, it highlights how AI is increasingly embedded in enterprise decision-making, operational optimization, and customer engagement. Technologies such as Robotic Process Automation (RPA), natural language processing, and predictive analytics are displacing routine tasks while simultaneously generating demand for new skills and job roles. A central focus of the study is the strategic integration of AI in organizational contexts, especially in human resource management. AI-driven systems are now employed in talent acquisition, performance evaluation, employee training, and succession planning. While these tools enhance efficiency and personalization, they also raise significant ethical concerns, including algorithmic bias, data privacy, and the erosion of human oversight in decision-making. The thesis emphasizes the importance of inclusive and transparent governance frameworks that align AI deployment with organizational values and broader societal expectations. The thesis further explores the labor market implications of automation and AI, particularly job displacement, skill transformation, and the need for continuous reskilling. Drawing on economic and sociological theories, the research outlines how low- and mid-skilled occupations are increasingly vulnerable to automation, while new roles emerge in data science, cybersecurity, and AI ethics. It argues that a shift from job-based to skill-based workforce planning is essential for future competitiveness and resilience. The role of diversity, equity, and inclusion (DEI) is also addressed, with evidence showing that AI adoption can exacerbate existing inequalities if not managed ethically and inclusively. Methodologically, the study adopts a quantitative approach, utilizing a structured questionnaire administered to 123 employees across various sectors in Greece. Data analysis, performed using SPSS, reveals significant trends in perceptions toward AI, attitudes about job security, and willingness to participate in reskilling initiatives. The findings show moderate levels of trust in organizational ethics regarding AI deployment and highlight the need for stronger communication and leadership engagement in digital transformation processes. Respondents largely recognized the efficiency benefits of automation but expressed concerns about transparency and ethical oversight. Gender, educational background, and work experience were found to influence attitudes toward AI adoption and ethical concerns. The final chapters synthesize the study’s theoretical and empirical contributions, offering strategic recommendations for business leaders and policymakers. These include the need for proactive reskilling strategies, participatory AI governance, sector-specific regulatory frameworks, and a holistic approach that views AI not merely as a technological upgrade but as a transformative shift requiring cross-functional alignment. In conclusion, this research underscores that the future of work under AI and automation will be shaped not only by the pace of technological innovation but by the strategic, ethical, and human-centered decisions organizations make today. Through strategic foresight, inclusive leadership, and continuous learning, AI can serve as a catalyst for sustainable growth, innovation, and
