Why AI in AEC/O Must Work Across Portfolios, Not Just Flagship Projects

Artificial intelligence is no longer a fringetopic in the Architecture, Engineering, Construction, and Operations (AEC/O) industry. It is rapidly becoming a defining force in how we design, build, and operate the environments that shape everyday life. What began as theoretical exploration and high-profile demonstrations has now entered a new phase, one in which AI must prove its value through practical, scalable application. The question is no longer whether AI can work, but how it can deliver measurable impact across entire portfolios of assets, not just within isolated showcase projects.

At Nemetschek, we believe the true promise of AI is not demonstrated by a single spectacular case study. It is proven through consistent, enterprise-wide outcomes. And that represents a fundamentally different challenge.

Flagship projects, iconic buildings, digital twin demonstrations and generative design experiments, play an important role. They capture imagination and help professionals understand what is possible. But real transformation in AEC/O will not come from isolated excellence. It will come from systemic performance improvement, applied across thousands ofassets, multiple market segments, and the full lifecycle of the built environment.

Most organizations do not manage one bespoke project at a time. They manage portfolios: combinations of commercial buildings, public infrastructure, industrial facilities, campuses, and housingstock. These portfolios represent the greatest opportunity for AI, and also its greatest test.

To unlock that opportunity, AI must move beyond novelty and become a reliable, embedded, and repeatable capability. It must support leaders in answering questions that matter at scale: which projects consistently underperform, where investment should be prioritized, how design, engineering, scheduling, materials and staffing can be improved across many sites, and which risks can be anticipated rather than addressed reactively. These are not project-level questions; they are portfolio-level decisions.

Portfolio workflows are essential to unlocking meaningful AI value in the AEC/O industry. Unlike traditional project-based workflows that focus on a single building or asset, portfolio workflows treatan organization’s entire asset base as a connected system. This shift is critical, because AI delivers its greatest value when it can identify patterns, relationships, and opportunities across scale, not in isolation.

The difference between analyzing one building and analyzing an entire portfolio is not simply a matter of data volume. It is about context, comparability, and strategic relevance. Portfolio-level AI allows organizations to benchmark performance, detect recurring issues, and uncover trends that remain invisible when assets are assessed individually. This broader view turns fragmented information into insight that supports confident, organization-wide decision-making.

By embedding AI into portfolio workflows, organizations move from isolated data points to strategic intelligence that drives consistent improvement across all assets. Portfolio-level AI makes it possible to identify systemic inefficiencies and deliver improvements that compound over time, creating lasting organizational value rather than one-off success stories.

For AI to be effective at scale, it must integrate seamlessly into the tools, workflows, and decision processes that AEC/O professionals rely on every day. This requires interoperable data environments that connect design, BIM, construction, and operations; explainable and trustworthy AI outputs that can be acted upon with confidence; and governance frameworks that ensure consistency, accountability, and scalability.

When these elements come together, AI moves beyond experimentation. It becomes a core enabler of operational performance, long-term resilience, and strategic foresight.

When portfolio-level AI systems are implemented thoughtfully, the results are tangible and enduring. Organizations see consistent efficiency gains across dozens or hundreds of sites, faster and more informed retrofit planning, improved occupant comfort and safety at scale, and clearer alignment with regulatory and reporting frameworks. Just as importantly, leaders gain stronger foundations for capital planning, riskforecasting, and long-term decision-making.

These are not abstract benefits. They directly influence financial performance, operational stability, and the ability of organizationsto manage complexity with confidence.

The AEC/O industry is complex, dynamic, anddeeply interconnected. No single technology, vendor, or pilot project canaddress its challenges in isolation. Real progress and real leadership require solutions that are scalable and repeatable, grounded in real operational data, integrated across portfolio workflows, and aligned with strategic businessgoals.

This perspective guides how Nemetschek developsand deploys AI across its product ecosystem. Our focus is on delivering meaningful, measurable value at scale. We are building AI systems that help organizations not just do things differently once but do things better everywhere.

Flagship projects can point the way. But true impact happens when AI works across every building, every facility, and everyasset in a portfolio. That is where the future of the AEC/O industry lies.