In 2025, the construction, infrastructure, and energy sectors will reach a pivotal turning point. The rise of modular AI platforms and Model-Based Systems Engineering (MBSE) is driving major advances in efficiency, integration, and resilience. Organizations that strategically combine these technologies not only resolve persistent challenges in project execution and asset management, but also lay a solid foundation for sustainable growth and competitive strength.
The Netherlands is at the forefront with initiatives such as the collaboration between TNO and BAM, where modular AI is applied for predictive maintenance of bridges and tunnels. By integrating flexible AI modules into existing asset management systems, organizations are able to reduce maintenance costs and enhance safety. European projects like EIT Digital - AI4Buildings demonstrate that plug-and-play AI tools are rapidly being adopted in smart buildings and energy networks.
MBSE is at the core of digital transformation for organizations like ProRail and TenneT. By comprehensively modeling and simulating complex systems, organizations gain deeper insight into risks and enhance collaboration across disciplines. Cloud-native MBSE tools enable real-time cooperation, spanning from design through to operational phases.
The digital twin of the Port of Rotterdam stands as a leading example of how real-time monitoring and scenario analysis elevate asset management to a higher level. Alliander leverages digital twins to optimize the electricity grid and predict failures. European smart city initiatives, such as those in Amsterdam, demonstrate how digital twins contribute to energy management and climate adaptation.
The lack of standardized data and open APIs between BIM, MBSE, and AI platforms remains an ongoing challenge. Initiatives such as the Digital Twin Consortium NL and European standardization projects are accelerating the development of open, federated data models that facilitate collaboration.
Many organizations still use outdated SCADA or asset management systems. Middleware and adaptation layers are essential to integrate these systems with modern AI and MBSE platforms. VolkerWessels and Siemens demonstrate that cloud-native solutions bring scalability and flexibility without the need to replace existing IT systems.
Increased integration also brings greater cyber risks. Strict data governance and continuous training are therefore crucial. Workforce upskilling, through organizations like the Energy Academy Europe and NL Digital, ensures staff can work safely and effectively with new technologies.
With modular AI and digital twins, organizations can accurately predict and plan maintenance, resulting in fewer disruptions and lower operational costs. Companies like Siemens Energy and Royal HaskoningDHV are already demonstrating the effectiveness of this approach, from wind farms to energy networks.
By embedding sustainability directly into MBSE models, organizations can optimize their use of materials, energy, and water—perfectly aligning with both Dutch and European sustainability objectives.
AI-driven compliance monitoring and MBSE-based documentation enable real-time adherence to laws and regulations, speeding up audits and reducing risk.
Digital skills are essential. Educational programs and pilot initiatives—such as those at the Energy Academy Europe and through the Bouwagenda—focus on AI, MBSE, and cloud-native technologies. Multidisciplinary teamwork is becoming the standard.
Leading organizations are shifting from linear to cyclical processes, where MBSE and AI play a central role. Change management and strong leadership are essential to overcome resistance and embed digital tools effectively.
How is your organization preparing for the next wave of digital transformation? What opportunities and challenges do you foresee? Basewise is ready to help you think ahead. Get in touch to discover how we can accelerate your digital transformation.