AI Bubble and Technological Transformation: Analysis of a Multi-Speed Reality

The debate about the actual transformative nature of artificial intelligence is no longer merely an academic dispute: it primarily concerns how the ecosystem moves across different levels. There is a complex dynamic in which wrapper companies, foundation models, and infrastructure feed off one another, but they do not share the same business logic or the same risk profile. In this light, the AI Bubble is not a single event, but a layered process that requires targeted analysis at each level.

Layer 3: The Wrapper Companies

The most exposed segment is that of wrapper companies, startups that do not develop proprietary models but repackage third-party APIs, adding user interfaces and some elements of prompt engineering. Many have monetized the hype quickly, demonstrating that it is possible to generate meaningful revenues in short order, as in the Jasper.ai example.

However, this model shows structural fragility: adoption by big tech, rapid commoditization of base models, and the absence of switching costs for users compress margins at a pace difficult to justify by current valuations. At this level, the AI Bubble is not a future prospect, but an ongoing process that could manifest more clearly between 2025 and 2026.

Layer 2: Foundation Models Between Innovation and Compression Risk

Companies developing large language models find themselves in an intermediate position: they possess technical expertise, access to compute, and partnerships that represent real technological moats. On the other hand, the gap between invested capital and expected revenues raises questions about medium-to-long-term economic sustainability.

The main risk is not so much a sudden collapse, but a gradual transformation of foundation models into low-margin utilities

In this context, competition is shifting more and more from training models to inference engineering, memory optimization, and infrastructural efficiency. The AI Bubble at this level could translate into a phase of consolidation, rather than a traumatic burst.

Layer 1: Infrastructure, Beyond the AI Bubble

The infrastructural layer represents the most resilient part of the entire ecosystem. Despite figures that at first glance seem typical of an AI Bubble, chips, data centers, memory and storage systems maintain value independently of the applications that will emerge as winners.

The history of the dot-com bubble offers a clear precedent: infrastructure built ahead of real demand is not wasted, but has powered the digital economy of the following decades. Similarly, current AI infrastructure will enable future workloads today that are only partially visible.

More than a single AI Bubble, it is accurate to speak of a series of overlapping bubbles, with different timings and impacts

A Multi-Speed Bubble

Rather than a single bubble, it is prudent to consider a series of bubbles that move at different paces and with varying impacts. The wrapper companies could be among the first to disappear, followed by a consolidation phase among model providers. The infrastructure, instead, will go through a normalization phase without losing its strategic role.

For startups and founders, the lesson is clear: the real risk is not operating in AI, but doing so without control over workflow, data, and distribution. Understanding which segment of the AI Bubble you are building in is today one of the most important decisions to survive the imminent shake-out.

Fonte startup-news.it