AI’s integration with BIM could usher in a new generation of future-ready healthcare facilities, writes Manish Sharma, chief product officer in the Build & Construct Division at Nemetschek Group
For healthcare organizations and hospitals worldwide, addressing rising costs and operational challenges tied to growing demand, strained capacity, and increasing regulatory and crisis management pressures has become a serious concern.
Making matters worse, many efforts to solve these issues through strategic construction and renovation have been repeatedly thwarted by abnormally high material costs, persistent labour shortages and other pressures affecting the global AEC/O landscape.
Whether dealing with new or existing facilities, these challenges highlight the urgent need for hospital operators and their AEC/O partners to adopt intelligent, modernised construction and building management solutions.
Fortunately, while the transformation required is complex and spans all project phases, it coincides with rapid advancements in artificial intelligence (AI).
AI’s integration with Building Information Modelling (BIM) and other supportive technologies promises to accelerate modernisation and usher in a new generation of resilient, future-ready healthcare facilities – for the benefit of patients and providers worldwide.
Centralising data and optimising management across the building lifecycle
One major challenge in building, renovating and maintaining hospitals is managing the vast amount of critical data generated across the lifecycle. Without a truly unified data management solution, collaboration among stakeholders becomes difficult, often resulting in higher costs, avoidable errors and unreliable decision-making.
This longstanding issue has plagued AEC/O professionals for decades. The Nemetschek Group has worked to address it through solutions like dRofus, a cloud-based planning and data management platform that centralises all project data and provides real-time visibility across the building lifecycle. Even early versions of this technology have significantly improved efficiency and collaboration, especially in constructing new healthcare facilities.
A prime example is Glasblokkene Trinn 2, a 50,000 sq m children’s hospital in Bergen, Norway, designed and built using a digital twin created from dRofus’ master database.
By leveraging the digital twin from the earliest planning stages, stakeholders could access all relevant data when needed, improving collaboration and avoiding costly delays and errors common with fragmented documentation.
The benefits realised in this project reflect what we call Building Lifecycle Intelligence – an approach that bridges data gaps, preserves information value throughout design and construction and enhances long-term operations.
With continued AI and machine learning integration, these benefits will only grow – deepening insights, improving predictive accuracy and expanding automation across the entire lifecycle.
Revolutionising hospital safety and regulatory compliance
Another critical challenge facing modern healthcare facilities is the need to design and build unique safety and regulatory standards. More than most built environments, hospitals must meet and consistently maintain extraordinarily strict building requirements to safeguard patients and care providers. Ensuring compliance with all regulations can be incredibly costly and time-consuming for construction and maintenance teams.
Whether ensuring the reliability of fire walls, ventilation or alarm systems, traditional risk identification and mitigation processes remain inefficient and overly reliant on manual inspection. However, this issue is now being addressed by innovative, digital-first solutions like Imerso, which leverages a combination of BIM, reality capture and AI technologies to automate construction oversight and safety inspections.
For example, Imerso’s AI-powered software has been an invaluable tool for the construction and engineering teams at Nyt Hospital Nordsjælland outside Copenhagen, who used the technology to streamline fire wall construction and compliance across the entire facility.
By incorporating Imerso, they’ve been able to automate multiple key processes related to the hospital’s fire walls, including quality monitoring, risk identification, system testing and even proactive safety validation during the planning phase.
As a result of these critical modernisation efforts, Nyt stakeholders dramatically reduced construction time while increasing productivity and completed the project with an estimated cost savings of €5.2m.
Moreover, the team reports that continued use of Imerso has increased monitoring capacity by 15x compared with previous methods, while using only 7% of the resources.
Supporting healthcare’s rapid evolution
As impressive as these early use cases may be, the true potential of these technologies lies in the ability of AI-powered systems to learn and improve through continued development and adoption. Rather than being limited to niche applications, AI is rapidly expanding to support a wide range of trends within the healthcare industry’s broader evolution.
For example, improving sustainability to combat climate change has become a major priority, with hospitals and care facilities responsible for roughly 5% of global carbon emissions each year. This issue is especially pronounced in the United States, where hospitals account for about 8.5% of annual emissions.
In response, several regulatory mandates and incentives have emerged to address the industry’s environmental impact, such as the UK’s Sustainability & Transformation Plan (STP) and the International Joint Commission’s Healthcare Sustainability Certification.
This is an area where AI-based solutions are already showing strong potential. By integrating AI and machine learning into design and construction planning, teams can run virtual simulations to proactively assess environmental impacts and identify strategies for maximising sustainability. In operations, AI monitoring and predictive maintenance tools help optimise energy usage and reduce waste.
Another notable trend is the growing demand for decentralised care, seen in the construction of smaller, community-based facilities and modular care units that expand capacity and improve infrastructure flexibility. In addition to enabling fast, efficient construction of new care centres, the renovation and modular augmentation of existing facilities can benefit greatly from tools like Imerso, dRofus and similar technologies – especially for space optimisation and regulatory compliance.
Finally, the global healthcare industry is now on an accelerated, long-overdue path toward digital transformation – and it’s clear that AI is becoming essential to ensuring hospital infrastructure can keep pace with complex demands and rapid innovation. As the global healthcare ecosystem evolves, and the AEC/O sector deepens its integration of these tools, AI is expected not only to transform how hospitals are designed, built and operated but also to dramatically enhance access and quality of care for patients worldwide.
*Please note that this is a commercial profile.
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