AI chip executives tell CNBC demand remains 'almost unlimited'; enterprises pivot to 'valuemaxxing' from 'tokenmaxxing'
AI industry leaders pushed back against overcapacity concerns this week, with Pat Gelsinger (former Intel CEO, now partner at Playground Global) telling CNBC: 'I somewhat think of AI demand as almost unlimited, because how much economic value do you get for increased intelligence? Almost infinite across every industry imaginable.' Energy availability, not compute demand, is 'the only real limiter,' Gelsinger said.
Executives from Nebius (data center operator using NVIDIA GPUs), Cerebras Systems (AI chip startup; IPO earlier 2026), and Rebellions (Samsung/SK Hynix-backed Korean chip startup) all confirmed strong demand and full capacity. Lumentum, the photonics provider whose products sell out five years in advance due to data center connectivity bottlenecks, is at full utilization. However, enterprise spending patterns have shifted: instead of 'tokenmaxxing' (using AI tools indiscriminately), companies now focus on 'valuemaxxing'—ROI-driven AI spending where departments justify costs against measurable returns.
The shift away from frontier model dominance (OpenAI, Anthropic) toward open-source alternatives (DeepSeek, Alibaba) reflects this rationalization. Cerebras' CEO Andrew Feldman noted certain workloads will migrate to lighter models—'you don't need a giant bus to go to the grocery store'—but demand for premium inference for large-scale problems remains unmet. Meta and xAI's sales of excess capacity were framed as isolated cases, not signals of industry overcapacity.
For practitioners: Market consensus is clear—supply is constrained, demand is strong, but enterprise AI budgets are being rationalized. Implications: (1) frontier models command premium pricing to enterprises willing to pay for ROI; (2) open-source and cost-optimized inference workloads gain share; (3) data center capex continues unabated. Architects should expect commodity compute to become more price-competitive while enterprise-grade inference services command higher margins.