Grounding, not models, will define your AI advantage

Building competitive advantage in AI lies not in owning proprietary models—which are rapidly commoditizing and depreciating assets—but in developing robust data grounding and retrieval pipelines that connect general-purpose models to enterprise-specific information and institutional knowledge. IT organizations should redirect resources from expensive model development toward investing in data quality, governance, and retrieval infrastructure (such as RAG systems), which compound in value over time and remain proprietary and defensible regardless of which model sits on top. This strategic shift will enable enterprises to remain competitive as model capabilities become cheaper and more commoditized, while positioning them to quickly adopt superior models as they emerge.