Open research questions in Digital Transformation in Industry

What the literature leaves open

• Regarding Research Question 3, the reviewed evidence indicates that autonomy and human control should be adapted to consequence severity, uncertainty, reversibility, intervention effectiveness, and time-to-harm, with stronger human authorization and control required as risk increases.

  Digital Twins and Agentic AI: Applications, Risks, and Governance Frameworks · 2026 · DOI

• The effective integration of MLOps in the manufacturing industry represents a paradigm shift that transcends mere software tool adoption, constituting a systemic challenge that requires reconciling the agility of data science with the determinism of operational technology (OT) systems.

  Towards a Reference Architecture for Machine Learning Operations · 2026 · DOI

• The results are also in line with earlier work indicating that KM is widely recognized as strategically important, but is still insufficiently embedded in organizational practice.

  Knowledge Management in Manufacturing: Current Practices, Barriers, and Automation Potential for LLM-Supported Systems · 2026 · DOI

• However, because the framework has not yet been empirically validated, its proposed structure and relationships should be examined in future expert and SME-based studies.

  A Human-Centered Competency Framework for Industry 5.0 Transformation in Manufacturing SMEs: A Literature-Based Conceptual Study · 2026 · DOI

• Future research should address these limitations through several strategic priorities. Additionally, further research is required to address cybersecurity, ethical governance, and data privacy challenges, particularly in the context of human-centered monitoring systems and AI-driven decision-making.

  Mapping the Industry 5.0 Landscape: Enabling Technologies, Human-Centered Systems, Sectoral Applications, and SDG Alignment—A PRISMA-ScR Review · 2026 · DOI

• Currently, there are several open questions to be addressed in future work: What software and hardware platform will enable communication with the system being developed in its entirety? The evolution of DT is carried out in conjunction with the evolution of SMR.

  Digital Twin-Based Lifecycle Methodology for Ensuring Safety of NPP/SMR I&C Systems · 2026 · DOI

• Future research should focus on the following aspects: 1. Future research should focus on integrating the information sets of this method with richer ontological description languages, such as W3C OWL, and developing automated semantic matching and validation tools to promote broader interoperability.

  Hierarchical Decoupling Digital Twin Modeling Method for Topological Systems: A Case Study of Water Purification Systems · 2026 · DOI

• Future research should investigate the applicability of the I5-OPTIMA framework to various industrial sectors, especially small and medium-sized enterprises, and evaluate the long-term viability of AI-based sustainability forecasting and blockchain-based transparency systems.

  Industry 5.0-enabled sustainable transformation: a multi-objective and probabilistic influence framework for industrial strategy optimization toward achieving sustainable development goals · 2026 · DOI

• They do not constitute a full operational validation of a continuously synchronized digital twin, since live shop-floor data acquisition and automated execution of the selected plans were not demonstrated in the present study. The -constraint method produced a diverse set of Pareto-optimal solutions, each representing a distinct trade-off between workforce deployment, inventory, and demand satisfaction.

  Digital twin-based advanced planning and scheduling system for SMEs: conceptual framework and industrial-data-based proof of concept · 2026 · DOI

• The relative novelty of I4.0 technologies implies limited empirical evidence regarding their real impacts, which undermines the reliability of criteria weighting and scoring. Small and medium-sized enterprises face pronounced barriers in the early stages of digital transformation within the I4.0 context, frequently due to limited knowledge, resources, and uncertainty regarding implementation pathways and outcomes.

  Mapping and prioritizing industry 4.0 technologies: an analysis based on patent and scientific publication networks · 2026 · DOI

• The study does not seek to replace firm-specific assessment. The proposed approach faces limitations in the context of I4.0 technologies, such as the relative novelty of these technologies. The study requires further empirical validation. The combinatorial potential of distinct technologies is not fully understood.

  Mapping and prioritizing industry 4.0 technologies: an analysis based on patent and scientific publication networks · 2026 · DOI

• Future research should build upon this study’s conceptual framework by developing formal computational models and simulation environments to test and validate digital twin strategies for climate-responsive urban development.

  Digital Twins for Climate-Responsive Urban Development: Integrating Zero-Energy Buildings into Smart City Strategies · 2025 · DOI

• Future research could explore the role of organizational culture and employee perceptions in shaping HRD and technological readiness, offering a more comprehensive understanding of Industry 4.

  Strategic Human Resource Development for Industry 4.0 Readiness: A Sustainable Transformation Framework for Emerging Economies · 2025 · DOI

• Future work should focus on quantifying and minimizing deviations between simulated and actual traffic flow dynamics, using continuous real-world validation to refine DT models. DT systems rely on integrating data from multiple sources, but without standardized data exchange protocols, interoperability between different platforms is limited.

  AI-Enabled Digital Twin Framework for Safe and Sustainable Intelligent Transportation · 2025 · DOI

• This study has explored the pivotal role of digital twins in enhancing building energy efficiency, focusing on their applications, enabling technologies, and associated challenges.

  Leveraging Digital Twins for Enhancing Building Energy Efficiency: A Literature Review of Applications, Technologies, and Challenges · 2025 · DOI

• Future research should focus on breakthroughs in model optimization, data fusion, and intelligent decision support, driving further advancements in SHM technologies.

  Current Status and Prospects of Digital Twin Approaches in Structural Health Monitoring · 2025 · DOI

• Importantly, the gestation of the DT using a combination of agile engineering and IT change management eventually delivers a platform for unified change management, one of the top-priority digital solution areas that are currently lacking appropriate tool support.

  Agile Construction Digital Twin Engineering · 2025 · DOI

• The previous section has listed some of the challenges in the agricultural DT. The following one will provide some research directions for these challenges and explores the potential of integrating FMs and DTs. Introducing deep learning to crop modelling: Future research may focus on integrating deep learning techniques with crop imagery to generate high-accuracy 3D models with minimal manual input.

  A Comprehensive Review of Digital Twins Technology in Agriculture · 2025 · DOI

• Despite the DT-FieldPheno system demonstrating promising results in constructing a closed-loop framework for sensing, computation, decision-making, and execution, several limitations remain to be addressed.

  Research on Intelligent Control Technology for a Rail-Based High-Throughput Crop Phenotypic Platform Based on Digital Twins · 2025 · DOI

• The research was limited to a specific time range (2021–2025) to ensure technological relevance; however, this may have excluded longitudinal studies or earlier foundational projects that could offer insights into the long-term evolution of digital twins.

  Digital Twin in Territorial Planning: Comparative Analysis for the Development of Adaptive Cities · 2026 · DOI

• The inclusion of AI and DT technology in facilities management for mega-facilities shows significant capabilities for streamlining operations, improving decision-making and cost-saving.

  Optimizing Facilities Management Through Artificial Intelligence and Digital Twin Technology in Mega-Facilities · 2025 · DOI

• Future research could focus on establishing standardized evaluation frameworks, systematically comparing the effects of different LLM knowledge-based governance models, exploring core experience design for cross-platform adaptation, incorporating accessibility and inclusiveness as central elements of the system design process, and treating post-deployment operation and continuous iteration as fundamental…

  An Integrated Product Service System Framework for On-Site Digital Human Guide Systems · 2026 · DOI

• The top 10 challenges of AI-DT in mining field identified were: Data Integration and Heterogeneity, Real-Time Data Processing and Synchronization, Limited/Poor Data Quality and Availability, Modeling Complexity and Accuracy, Interoperability and System Integration, Computational Complexity and Scalability, Sensor and Infrastructure Limitations, Harsh/Uncertain Mining Environments, Predictive Maintenance and Fault…

  AI-Driven Digital Twins in Mining Operations: A Comprehensive Review · 2026 · DOI

• Metaheuristic algorithms for PID controller parameters tuning: Review, approaches and open problems. Machine learning applications in internet-of-drones: Systematic review, recent deployments, and open issues.

  Integrating Artificial Intelligence into Mechatronics: A Comprehensive Study of Its Influence on System Performance, Autonomy, and Manufacturing Efficiency · 2026 · DOI

• Future research could focus on the reconstruction of occupational identity, the evolution of technological perceptions, and the development of motivational mechanisms among these groups, systematically examining the institutional support and empowerment strategies needed to facilitate their inclusion in the AI-driven transformation of the construction industry, thereby providing stronger support for inclusive…

  From Skilled Workers to Smart Talent: AI-Driven Workforce Transformation in the Construction Industry · 2025 · DOI

Most-cited papers in Digital Transformation in Industry

• Digital Twin: Enabling Technologies, Challenges and Open Research · IEEE Access · 2020 · 2,889 citations
• Industry 4.0 and Industry 5.0—Inception, conception and perception · Journal of Manufacturing Systems · 2021 · 2,376 citations
• Digital Twin: Values, Challenges and Enablers From a Modeling Perspective · IEEE Access · 2020 · 1,886 citations
• Review of digital twin about concepts, technologies, and industrial applications · Journal of Manufacturing Systems · 2020 · 1,751 citations
• Industry 5.0: A survey on enabling technologies and potential applications · Journal of Industrial Information Integration · 2021 · 1,267 citations
• Industry 4.0 technologies assessment: A sustainability perspective · International Journal of Production Economics · 2020 · 1,212 citations
• Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? · Technological Forecasting and Social Change · 2019 · 1,083 citations
• Digital Twins: A Survey on Enabling Technologies, Challenges, Trends and Future Prospects · IEEE Communications Surveys & Tutorials · 2022 · 1,014 citations
• Digital Twin: Origin to Future · Applied System Innovation · 2021 · 953 citations
• Servitization and Industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective · Technological Forecasting and Social Change · 2019 · 950 citations

Most recent work

• Agentic digital twins: bridging model-based and AI-driven decision-making support for a new era of supply chain and operations management · International Journal of Production Research · 2026
• Integrating agentic AI and digital twins for intelligent decision-making systems · Array · 2026
• Multi-scale digital twins for personalized medicine · Frontiers in Digital Health · 2026
• Large Language Models for manufacturing · Journal of Manufacturing Systems · 2026
• Leveraging large language models for smart manufacturing: Reviews, enablers, challenges, and opportunities · Journal of Manufacturing Systems · 2026
• AI-driven optimization techniques for smart sustainable manufacturing in Industry 5.0 ecosystem: A comprehensive review · Alexandria Engineering Journal · 2026
• From Data Mirror to Smart Copilot: A Survey on NextG Semantic Communication for Propelling Digital Twin World Into Cognitive Stage · IEEE Communications Surveys & Tutorials · 2026
• A literature review on the artificial intelligence in manufacturing systems under industry 5.0 · International Journal of Production Research · 2026
• Human-in-the-loop and large language models in smart manufacturing: Current applications, challenges, and perspectives · Journal of Manufacturing Systems · 2026
• Exnovation as a strategic enabler: Unlocking technological innovation through ambidexterity and capability reconfiguration · International Journal of Innovation Studies · 2026

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