QuadReal’s Chief Technology Officer shares insights on AI adoption, scaling AI across the enterprise, and building operating models that create long-term value.
Scaling AI beyond the pilot stage
The conversation around AI has shifted. It’s no longer about whether to adopt, it’s about why so many organizations are still stuck at the pilot stage, and what it actually takes to move beyond it.
At this year’s Realcomm IBCon QuadReal’s Chief Technology Officer Marcel Marra joined a cross-section of CIOs to share insights on the real work around scaling AI.
Marcel spoke about a topic he is navigating every day: making AI an operating model, not just a technology layer.
As organizations move beyond experimentation, questions around governance, ownership, and value realization are becoming increasingly important. Below, Marcel shares QuadReal’s perspective on the challenges and opportunities shaping the next phase of AI adoption.
Q: Why do so many AI pilots fail to scale?
We see failure because pilots are designed to prove a concept. Operating models are designed to sustain value. The gap between them isn’t technical, it’s organizational. Scaling requires governance, ownership, and support structures that most teams haven’t built yet.
Q: Who should be leading AI adoption—IT or the business?
In practice, neither extreme work. Centralize everything and the business disengages – AI becomes someone else’s thing. Decentralize everything and you fragment fast: different teams solving similar problems in different ways. The right model lives in the tension between the two.
Both IT support and buy-in from the business are integral for adoption. Centralized enablement creates the foundation: standards, platforms, guardrails, but business-led execution is what drives real adoption. The organizations winning at AI have figured out how to run both tracks simultaneously. At QuadReal we have created an AI Community of Practice (CoP), led by the AI & Digital Innovation team, the CoP brings together colleagues from across our organization to share insights, explore new capabilities and apply AI in their business units.
Q: What does “scaling AI” actually mean in practice?
It means stopping the cycle of one-off use cases and starting to build reusable capabilities and patterns. When every team is solving the same problem independently, you’re scaling effort, not intelligence. The leverage comes from shared infrastructure that any team can build on.
Q: What’s IT’s role in all of this?
At QuadReal, the role of IT is as an integrator. IT sits at the intersection of business needs, data assets, and technology capability, and that’s not a support role, it’s a strategic one. The organizations that treat IT as a pure service function are leaving enormous value on the table.
Q: What’s the part of AI adoption nobody talks about enough?
The operational side, including risk management and value realization. Who owns what when something breaks and how you measure ROI beyond the pilot dashboard. These aren’t glamorous topics, but they’re the difference between AI that transforms the business and AI that looks good in a deck.
Why this matters
As technology and AI continue to shift and change, strategic agility and operational strength are critical for long-term success.
QuadReal’s approach to AI reflects a commitment to innovation, resilience, and delivering value across our global business. This work complements our broader technology initiatives which helps create smarter, more connected environments across our portfolio.
