Engineering Education for Industry 5.0: A Systemic Approach to AI-Driven Talent Development

Ehud Menipaz (), Natalia Bukhshtaber and Ben Bulmash
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Ehud Menipaz: Holon Institute of Technology (HIT)
Natalia Bukhshtaber: Holon Institute of Technology (HIT)
Ben Bulmash: Holon Institute of Technology (HIT)

A chapter in Proceedings of the International Conference on Industrial Logistics (ICIL) 2025, 2026, pp 27-36 from Springer

Abstract: Abstract Industry 5.0 is reshaping industrial ecosystems through human–machine collaboration, advanced analytics, and sustainable, human-centric practices. As skilled personnel are the main asset of this transformation, higher education plays a pivotal role in preparing graduates who combine technical expertise with adaptability, ethical awareness, and innovation. Artificial Intelligence, as a disruptive technology, is transforming both industrial operations and educational processes. This paper examines the integration of AI into learning activities in engineering programs at the Holon Institute of Technology (Israel) within a structured institutional research and development initiative. Using a large-scale student survey grounded in validated theoretical frameworks, we analyzed how such integration influences AI-specific, general cognitive, and specialized professional capabilities, as well as self-perceived employability. Subgroup comparisons, mediation analysis, and regression modeling mapped the interrelationships between AI integration, capability development, and employability, and identified the effects of moderating factors such as AI proficiency, program level, employment status, and workplace AI use. Findings show that employability gains are driven mainly by reinforcing feedback loops linking the three capability domains, with their strength shaped by key background conditions. The weak direct link between AI integration and employability underscores the importance of aligning AI-integrated pedagogy with applied, real-world engagement to sustain capability growth. The study addresses a gap in the literature on AI integration in education by modeling it as a dynamic, complex adaptive system and provides a framework for designing effective, scalable, and contextually grounded AI implementation in higher education—supporting the alignment of graduate skills with evolving Industry 5.0 workforce needs.

Keywords: AI Integration in Engineering Education; Industry 5.0 Skills Development; System Dynamics in Higher Education (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-14489-8_3

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