The Three Pillars Of AI Readiness
Techstrong.ai, September 17,2025
Fletcher Keister, Chief Product and Technology Officer at GTT, lays out what he calls the three pillars of AI readiness: infrastructure, data, and skills. Without these, he argues, organizations risk repeating the same mistakes seen in earlier technology waves.
On infrastructure, Keister emphasizes that AI workloads demand far more than traditional IT systems were built to handle. Networks must be robust, low-latency, and capable of handling unprecedented traffic patterns. For enterprises still operating with legacy platforms, this becomes a gating factor for deploying AI at scale.
The second pillar is data. AI is only as good as the data it's trained and run against. Keister points out that many organizations still struggle with fragmentation, governance, and quality. AI systems can't deliver value if the data feeding them is incomplete or unreliable. Establishing strong pipelines, ensuring compliance, and maintaining security are now strategic priorities rather than afterthoughts.