AI infrastructure discussions still focus on GPUs, models, and cloud scale. As organizations move from experiments to production, a different constraint is emerging. AI success is increasingly limited by data platforms, not algorithms.
In a recent Future of Data Platforms discussion, Rob Strechay and Frederic Van Haren shared what they see across enterprises as they scale AI. Frederic is the CTO and Founder of HighFens. The conversation drew on survey data from 436 AI, data, and platform leaders. More importantly, it reflected what is failing in real-world AI operations.
As AI moves into production, data platforms are becoming the primary bottleneck. They are more limiting than models, GPUs, or cloud infrastructure. Survey results and enterprise experience show many platforms are unprepared. They struggle with AI-scale growth, higher data quality demands, and hybrid deployments.
AI systems quickly outgrow infrastructure choices made even a year earlier. Simple data storage is no longer sufficient. Enterprises now need platforms that can efficiently process, govern, and interpret data. Focus is shifting toward metadata, data efficiency, and trust. The future of AI infrastructure depends on smarter, AI‑ready data platforms.
How is your organization approaching the transformation of its data platform for AI?