RESEARCH · GLOBAL
Competitive edge in enterprise AI shifts from model choice to serving infrastructure
MIT Technology Review reports that enterprise AI success now hinges less on which foundation model (GPT, Claude, etc.) you choose and more on the operational layer around it—serving, caching, latency optimization, and integration. This mirrors infrastructure maturation in data engineering.
WHY IT MATTERS
Banks will see diminishing ROI from model-hopping. Instead, invest in production-grade serving stacks: vector DBs, guardrails, caching, and integration with core banking systems. Vendor lock-in shifts from models to operational infrastructure.