For decades, Moore’s Law shaped IT expectations. Performance improvements were assumed to offset rising cost and complexity. Even when individual components became more expensive, efficiency gains smoothed the curve.
“Cost per unit of compute now matters more than raw performance.”
Technologists have long acknowledged that the pace predicted by Moore’s Law has slowed, fundamentally changing the economics of computing. MIT Technology Review captured this inflection point clearly in its analysis of why transistor-level scaling no longer delivers automatic efficiency gains.
What has replaced it is more complex. Delivering additional compute increasingly requires larger, more power-hungry systems, along with rising investment in memory and storage. As a result, cost per unit of compute now matters more than raw performance.
Industry analysts increasingly emphasize that IT strategy must account for cost structures that no longer self-correct through innovation alone, particularly as AI infrastructure pulls resources away from traditional enterprise workloads.