Infrastructure and compute: Enterprises are buying AI compute for speed while flying blind on what it costs

The AI gold rush just hit its "light the engines, count the money later" phase. According to a new survey of 170 enterprises, two-thirds are running AI in production and 30% are at scale, but cost accounting has been left in the dust. This is like building the world’s fastest race car and refusing to look at the fuel gauge. Here’s the tension: performance and GPU availability now outrank total cost of ownership, and reliability beat price in success metrics. For any ops team drowning in production pressure, that rational prioritization makes perfect sense. But it's the same blind spot that sparked the original cloud spend fiasco—burn first, bill later. This is a signal worth watching. Every era of frenzied build-out creates a shadow ecosystem of tools to clean up the aftermath. For startups, the opportunity isn't selling the compute; it's building the material layer—the FinOps for AI—that explains what the hell you just spent. The need is latent, but it will be sudden and seismic. Right now, buyers are flying blind at full throttle. Remember, the first trillion dollars of AI value will be created on someone else's balance sheet—and right now, nobody knows whose. That's not a bug; it's the next billion-dollar disclaimer. {"key_insight":"Enterprises have traded cost visibility for production speed, creating a massive future opportunity in AI-specific FinOps and cloud cost intelligence.","confidence":0.88}