Andrés Fernández-Miguel

Smart manufacturing demands adaptive, scalable, and human-centric solutions for predictive maintenance. This paper introduces the concept of Agentic AI, a paradigm that extends beyond traditional multi-agent systems and collaborative AI by emphasizing agency: the ability of AI entities to act autonomously, coordinate proactively, and remain accountable under human oversight. Through federated learning, edge computing, and distributed intelligence, the proposed framework enables intentional, goal-oriented monitoring agents to form self-organizing predictive maintenance ecosystems. Validated in a ceramic manufacturing facility, the system achieved 94% predictive accuracy, a 67% reduction in false positives, and a 43% decrease in unplanned downtime. Economic analysis confirmed financial viability with a 1.6-year payback period and a €447,300 NPV over five years. The framework also embeds explainable AI and trust calibration mechanisms, ensuring transparency and safe human–machine collaboration. These results demonstrate that Agentic AI provides both conceptual and practical pathways for transitioning from reactive monitoring to resilient, autonomous, and human-centered industrial intelligence.

This paper introduces cognitive adaptivity as a novel framework for addressing human factors in cybersecurity during the Industry 5.0–6.0 transition, with a focus on hard-to-abate industries where digital transformation intersects sustainability constraints. While the integration of IoT, automation, digital twins, and artificial intelligence expands industrial efficiency, it simultaneously exposes organizations to increasingly sophisticated social engineering and AI-powered attack vectors. Traditional resilience-based models, centered on recovery to baseline, prove insufficient in these dynamic socio-technical ecosystems. We propose cognitive adaptivity as an advancement beyond resilience and antifragility, defined by three interrelated dimensions: learning, anticipation, and human–AI co-evolution. Through an in-depth case study of the ceramic value chain, this research develops a conceptual model demonstrating how organizations can embed trust calibration, behavioral evolution, sustainability integration, and systemic antifragility into their cybersecurity strategies. The findings highlight that effective protection in Industry 6.0 environments requires continuous behavioral adaptation and collaborative intelligence rather than static controls. This study contributes to cybersecurity literature by positioning cognitive adaptivity as a socio-technical capability that redefines the human–AI interface in industrial security. Practically, it shows how organizations in hard-to-abate sectors can align cybersecurity governance with sustainability imperatives and regulatory frameworks such as the CSRD, turning security from a compliance burden into a strategic enabler of resilience, competitiveness, and responsible digital transformation.

This study advances toward establishing the theoretical foundations of Industry 6.0 by developing a comprehensive framework that integrates artificial intelligence (AI), decentralized control systems, and cyber–physical production environments for intelligent, sustainable, and adaptive manufacturing. The research employs a tri-modal methodology (deductive, inductive, and abductive reasoning) to construct a theoretical architecture grounded in five interdependent constructs: advanced technology integration, decentralized organizational structures, mass customization and sustainability strategies, cultural transformation, and innovation enhancement. Unlike prior conceptualizations of Industry 6.0, the proposed framework explicitly emphasizes the cyclical feedback between innovation and organizational design, as well as the role of cultural transformation as a binding element across technological, organizational, and strategic domains. The resulting framework demonstrates that AI-driven decentralized control systems constitute the cornerstone of Industry 6.0, enabling autonomous real-time decision-making, predictive zero-defect manufacturing, and strategic organizational agility through distributed intelligent control architectures. This work contributes foundational theory and actionable guidance for transitioning from centralized control paradigms to AI-driven distributed intelligent manufacturing control systems, establishing a conceptual foundation for the emerging Industry 6.0 paradigm.

This study investigates how AI-driven innovations are reshaping manufacturing value chains through the transition from Industry 4.0 to Industry 6.0, particularly in resource-intensive sectors such as ceramics. Addressing a gap in the literature, the research situates the evolution of manufacturing within the broader context of digital transformation, sustainability, and regulatory demands. A mixed-methods approach was employed, combining semi-structured interviews with key industry stakeholders and an extensive review of secondary data, to develop an Industry 6.0 model tailored to the ceramics industry. The findings demonstrate that artificial intelligence, digital twins, and cognitive automation significantly enhance predictive maintenance, real-time supply chain optimization, and regulatory compliance, notably with the Corporate Sustainability Reporting Directive (CSRD). These technological advancements also facilitate circular economy practices and cognitive logistics, thereby fostering greater transparency and sustainability in B2B manufacturing networks. The study concludes that integrating AI-driven automation and cognitive logistics into digital ecosystems and supply chain management serves as a strategic enabler of operational resilience, regulatory alignment, and long-term competitiveness. While the industry-specific focus may limit generalizability, the study underscores the need for further research in diverse manufacturing sectors and longitudinal analyses to fully assess the long-term impact of AI-enabled Industry 6.0 frameworks.

The European Union (EU) is fundamentally transforming sustainability governance by developing dual approaches that extend far beyond traditional environmental policy. This study explores how EU institutions integrate strategic sustainability, which embeds environmental goals within economic security and geopolitical frameworks, with systemic sustainability, which emphasizes circularity, stakeholder engagement, and long-term resilience. Using hermeneutic methodology, the research analyzes key policy documents including the European Green Deal, Circular Economy Action Plan, and Carbon Border Adjustment Mechanism to reveal how sustainability narratives align with strategic autonomy and economic resilience. The findings demonstrate that sustainability governance now operates as a multi-dimensional paradigm balancing sovereignty, competitiveness, and inclusiveness. The study introduces the Neo-Sovereign Strategic Management (NSSM) framework, conceptualizing sustainability as a strategic field where economic security, geopolitical influence, and environmental objectives converge. This dual strategic–systemic approach represents a paradigm shift from standalone environmental goals toward integrated governance that positions sustainability as both economic driver and geopolitical asset. The research contributes to the sustainability governance literature by providing actionable insights for policymakers navigating the complex intersection of environmental objectives, economic security, and strategic autonomy in contemporary EU governance. Unlike existing models such as multi-level governance or resilience theory, the frameworks conceptualize sustainability as a strategic field where sovereignty, competitiveness, and legitimacy converge.

In the contemporary era of Industry 5.0, characterized by the integration of digital technologies and human‐centered approaches, the assessment of social sustainability remains a critical challenge. Corporate responsibility and Environmental, Social, and Governance compliance are being reshaped by these developments. This paper aims to address the gap between industrial development and social impact by exploring the transformative potential of Social Life Cycle Assessment within the stakeholder framework established by the United Nations Environment Program. The proposed methodology is both standardized and data‐driven, employing advanced techniques such as Principal Component Analysis and sigmoid normalization to minimize subjectivity and enhance comparability. It is validated through a case study in the Italian ceramic industry, utilizing internal organizational data aligned with Social Organizational Life Cycle Assessment guidelines. The findings highlight the urgent need for reliable, data‐driven social impact assessments to support regulatory compliance, strengthen Environmental, Social, and Governance strategies, and foster long‐term corporate sustainability. Furthermore, the results demonstrate how integrating Social Organizational Life Cycle Assessment into Industry 5.0 frameworks can improve stakeholder engagement, drive social innovation, and contribute to sustainable business practices.

This seminal study explores systemic sustainability within the Industry 5.0 paradigm, using the strategic lens of geoanthropology to shape the emerging concept of Industry 6.0. A transdisciplinary approach is adopted, integrating geoanthropological insights into the analysis of the Italian ceramic district. Seven key factors are considered: resource consumption, production dynamics, innovation, environmental impact, social impact, market dynamics, and economic impact. Historical events such as changes in Italian industrial policy, market slowdowns, and the COVID-19 pandemic are identified as significant for the sector. A contingent analysis tailored to the unique characteristics of the ceramic district provides an in-depth understanding of its challenges and opportunities. The incorporation of geoanthropology provides a transdisciplinary perspective that allows for an in-depth examination of the complex interactions between people and their environment in an industrial setting. The study highlights the central role of innovation, digitalization, and government policies in driving positive changes in production efficiency, market dynamics, and economic impact. Nevertheless, challenges remain, including the delicate balance between environmental sustainability and resource consumption, as well as the effective management of the social impacts of digitization. To address these challenges, a systemic sustainability index derived from geoanthropological insights is proposed as a pragmatic tool to measure and guide the development of sustainability initiatives in the ceramic district. The results of this study not only pave the way for new horizons in sustainability assessment but also provide valuable insights for industrial district managers to formulate strategies that foster organizational flexibility and resilience.