The Inference Boom and the Rise of the "Good Enough" Cloud
There is a turning point happening in artificial intelligence that often gets lost beneath the headlines about ever-larger models and frontier breakthroughs. The real story of this year is not training; it is inference. As AI becomes cheaper and cheaper to use, and as it gets baked into the existing ecosystems of software and services we already rely on, demand is set to go through the roof. This is the inference boom, and it is exactly the kind of shift that rewards investors who recognize it early.
Why Inference Changes Everything
For a long time, the narrative around AI was dominated by the cost and complexity of building and running the most advanced systems. But the economics have flipped. When the cost of using AI collapses, the constraint stops being capability and starts being volume. Suddenly, the question is not whether you can afford to run a model, but how many places you can embed it. That is what drives an inference boom: not a single dramatic launch, but the relentless multiplication of AI workloads across every product and workflow.
Agentic AI gave this trend the final push it needed. Autonomous agents that can carry out tasks on their own dramatically expand the number of times models get called, turning the inference picture from a steady climb into something genuinely explosive. The lesson is simple: this is here now, it is accelerating, and you had better be prepared for it.
Looking Beyond the Big Tech Bubble
Once you accept that inference is going to explode, the natural next question is who benefits most. Everyone already knows the dominant names in the compute space; those positions are crowded and widely owned. The more interesting opportunity lies outside the big-tech bubble, among the companies that quietly provide the infrastructure underneath the boom.
Cloud computing is essential to this inference era, and that points toward providers that built their business as pure cloud plays. One such name stood out during the 2021–2022 period as essentially the only pure cloud computing company in the market. Revisiting that kind of business in the context of inference reveals a very different opportunity than it represented a few years ago.
A Sharper Balance Sheet and a New Conviction
What makes a company like this compelling now is not just the macro tailwind, but the specific moves it has made to position itself. Becoming more nimble on the balance sheet matters, because it gives a company the flexibility to invest aggressively into a fast-moving theme. Leadership matters too. A previous chief executive was not hostile to AI, but did not really treat it as the real, defining thematic it deserved to be. A new chief executive who is fully convinced that AI is real and that it is here changes the entire trajectory of the business.
The Case for "Good Enough"
The deepest insight in this whole shift is what I would call the rise of the inference cloud for agentic AI. In this new world, you no longer need the most elite, most powerful offerings to win. You just need a product that is good enough. Sometimes seventy percent of the absolute best is perfectly fine for a large share of customers.
The reason is in the nature of the work itself. A great deal of what agentic AI actually does is not the glamorous, research-driven stuff — not the complex models, the drug discovery, or the deeply demanding scientific tasks. Much of it is tedious, repetitive, almost dumb work that simply needs to get done. For those jobs, the highest quality is overkill. What matters is reliable, affordable capacity at scale. A provider that delivers "good enough" at the right price can capture an enormous and growing market precisely because so much of the demand sits at that level.
The Proof in the Earnings
The most convincing evidence that this thesis is working shows up in the numbers. Large customers with serious workloads — the kind one might have expected to outgrow a "good enough" provider and migrate to more elite platforms — are not leaving. They are staying, and they are spending substantially more. On top of that, the business is expanding into relationships with even larger customers.
That combination is what signals a genuine transformation. It demonstrates that the company can retain higher-value workloads rather than merely serving small or casual users, and that it is becoming increasingly important to the kind of companies that actually matter. When a business proves it can hold and grow serious customers in a booming market, the market notices. That is exactly why it is being rerated — and why the inference boom may end up rewarding the unglamorous, good-enough infrastructure providers far more than anyone expected.