Institutional real estate investing has outgrown static dashboards and now requires an AI-first, data-centric mindset built on business context. In part five of the firm’s five-part series, NTrust CSO Mike Harrison explains how traditional, application-centric data models and one-size-fits-all dashboards fail to provide the contextual understanding AI systems need to operate effectively. He argues that business-centric ontologies and knowledge graphs should form the foundation of modern DaaS platforms, enabling both humans and AI to understand relationships between assets, leases, tenants and risks. A key emphasis is that true data quality for AI is not just accuracy or timeliness, but completeness. Without it, critical gaps emerge that undermine trust, automation and decision making.
To read part 5, click here.
To read part 4,
