AI, digital twins and blockchain drive global shift to Industry 5.0

A major new study published in Applied System Innovation charts the transformation of industrial research from the technology-driven era of Industry 4.0 to the human- and sustainability-focused paradigm of Industry 5.0. Their findings highlight a clear shift in global scholarship and innovation priorities over the past two decades.

The paper, “Digitalisation in the Context of Industry 4.0 and Industry 5.0: A Bibliometric Literature Review and Visualisation,” draws on a comprehensive analysis of 1,441 academic papers indexed in Scopus between 2005 and 2025, applying bibliometric mapping and network analysis to uncover how industrial priorities are being reshaped.

How does Industry 5.0 redefine the role of humans in digitalisation?

The study shows that Industry 4.0 was largely defined by technological breakthroughs such as the Internet of Things, artificial intelligence, big data, and automation. The focus was on efficiency, productivity, and the integration of cyber-physical systems into global supply chains.

On the other hand, Industry 5.0 pivots toward human-centricity. Buri and Kiss reveal that emerging literature increasingly stresses human–machine collaboration, worker safety, and the social implications of digitalisation. Concepts such as human digital twins, collaborative robots (cobots), and adaptive workplaces are central to this new vision. Instead of displacing humans, machines are being reimagined as partners designed to support and enhance human decision-making.

This shift, the authors argue, represents more than an evolution. It is a reframing of industrial goals: technology remains central but is deployed in service of people and sustainability, not just output and cost efficiency.

How are AI and digital twins advancing sustainability in Industry 5.0?

Artificial intelligence and digital twins emerge as the dominant technologies bridging Industry 4.0 and Industry 5.0. The analysis shows that AI is now being embedded into decision-making systems that incorporate not only economic but also environmental and social criteria. This means AI models are increasingly being used to optimize energy consumption, reduce waste, and support circular economy practices.

Digital twins, virtual models of machines, processes, and even human operators, are identified as a fast-rising research trend, particularly since 2020. They allow real-time monitoring, predictive simulation, and sustainability optimization across industries. Human digital twins, for example, can be applied to occupational safety, personalized training, and adaptive workforce planning.

The study highlights how digital twins have moved from being tools of operational efficiency under Industry 4.0 to becoming enablers of green digital sustainability under Industry 5.0. This transition is reinforced by keyword burst analysis, which shows “digital twin” as one of the fastest-growing terms in the field.

How do blockchain and resilient supply chains fit into the transition?

Supply chains have been under increasing stress from global disruptions such as pandemics, geopolitical tensions, and climate impacts. Buri and Kiss find that blockchain technology, once primarily used for transparency and traceability, is now being reconceived as a tool for resilience and decentralization.

The analysis shows that blockchain is increasingly coupled with digital supply chain twins (DSC-Twins), which simulate and manage disruptions in real time. These combinations make global networks more flexible and adaptive while supporting sustainability reporting and equitable value distribution.

The research underscores that in Industry 5.0, supply chains are no longer optimized solely for speed and cost reduction. Instead, they are being redesigned to balance resilience, inclusivity, and sustainability - values that reflect broader societal and environmental demands.

A roadmap for the future of industrial transformation

Industry 5.0 is not merely a continuation of Industry 4.0 but a fundamental realignment of industrial priorities. Their review provides a roadmap for managers, policymakers, and researchers:

• Embrace human–machine collaboration through cobots and human digital twins.
• Deploy AI and digital twins to align productivity with sustainability and circular economy goals.
• Integrate blockchain and supply chain twins to manage global disruptions and support resilience.

At the same time, the study acknowledges limitations. The review is constrained by Scopus indexing and English-language bias, while bibliometric clustering requires subjective interpretation. Despite these caveats, the analysis provides a robust benchmark for understanding how industrial research and practice are evolving.