The Pivot to the Plumbing: Why Private Investment is Betting Big on AI Infrastructure

In the current AI landscape, the real winners are not the apps trending on your social media feed. They are the companies you never see, humming quietly in the background of a data center.

In late 2022, ChatGPT’s release triggered an overnight gold rush, reaching 100 million users in just two months and spawning a wave of AI startups almost instantly. Venture Capital firms responded by pouring billions into application-layer companies built entirely on top of existing models. By 2023, a startup like Jasper AI could command a $1.5B valuation by simply building writing tools dependent on outside tech.

But just two years later, the landscape has changed significantly. Investors are realizing that the sustainable value in AI lies in compute capacity rather than creative use cases. As a result, the capital is shifting away from apps and into infrastructure. The most valued companies today are those providing the chips, cloud systems, and raw processing power that make AI feasible.

The Rise and Fall of AI Applications

In the early days of the AI boom, it was far easier to build products using OpenAI’s API than to invest in the multi-billion dollar hardware required to power it. This gave rise to several “AI wrapper” companies. Jasper AI raised $125M in 2022 at a $1.5B valuation, at the height of the AI wrapper hype.

However, the same low barrier to entry that birthed these apps also made them indefensible to investors in an increasingly crowded space. Apps built on public APIs are easily replicated, and every major model update can render features obsolete overnight. The release of GPT-4 in March 2023 eliminated the need for many features in application-layer startups. Jasper was one of these companies, with its main writing features being made redundant as the base models became more capable.

If a model provider introduces a feature that imitates your product, your startup essentially becomes a UX layer, forced to differentiate on price rather than technology. This realization is what caused private investment to pivot sharply from flashy apps to the foundational infrastructure.

The Shift Towards Infrastructure

As shown in the figure above, the capital never moved away from AI, it has simply moved deeper into infrastructure. CoreWeave, a GPU cloud provider, saw its valuation grow from $2B in 2023 to $19B in 2024. Several AI startups rely on CoreWeave’s compute, and VC/PE firms now see the value in this sort of dependence. Even tech giants like NVIDIA, Microsoft, Amazon, and Google are spending aggressively in order to secure a piece of the infrastructure pie, recognizing that compute is the new oil.

The main driver behind the rise of infrastructure is the same force that triggered the fall of applications: barriers to entry. Infrastructure requires billions in capital and years of dedicated R&D. The cost of entry into this layer includes securing massive data centers, power contracts, and a reliable hardware supply. This makes it nearly impossible for new players to compete with the giants on capacity or price.

From an investment perspective, infrastructure presents a far more attractive value proposition over time. While individual AI apps only capture a tiny fraction of the market, GPU clouds earn a “fee” from every training run that takes place on their hardware. This demonstrates how infrastructure companies can profit from the growth of the entire AI ecosystem simultaneously.

Analysts expect this gap to only widen further as the industry matures. Infrastructure players like CoreWeave benefit from fixed costs and a highly scalable user base, while application-layer startups face steep customer acquisition costs and limited pricing power. Ultimately, the past two years have served as a market correction, shifting the focus from experimental apps to what is now the industry’s most valued asset.

Where the Value in AI Will Lie

Despite cloud computing and hardware companies dominating AI funding, some applications will survive. Industries such as healthcare, finance, and defense have access to datasets that these foundational models cannot replicate.

To succeed, future application-layer startups must integrate their product with proprietary data. The next cycle of applications will not just be wrappers on OpenAI. They will likely look more like mini‑infrastructure companies inside industries, controlling specific datasets and the processes behind them.

In ten years time, we will view the industry’s initial reaction during the honeymoon phase following ChatGPT’s release as being naive. Because within just a couple of years the market came to realize that the significant AI companies are the ones that we barely see in our day-to-day lives. The real winners are the companies that have spent enormously up-front to develop the systems that support AI.

In that sense, the real question for investors during this AI boom is not “What is the next unique AI app” but rather, “Who owns the architecture that these apps cannot exist without?”

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Lead Editor of The GTVC Publication: Sash Vijayakumar