Bloomberg: the AI market still lacks the “secret sauce” of the 1990s internet boom

On Bloomberg This Weekend, senior editor of Bloomberg News Chris Ensti compared the current wave of interest in AI with the internet boom of the 1990s, but pointed out an important difference. In his view, the market has already received the hype, investments, and attention of corporations, but has not yet found that very element that transforms a technological surge into a sustainable mass market.

Parallels with the 90s

The comparison with the internet era of the late twentieth century is no accident. Back then, the market also lived on expectations: companies promised a new economy, investors rushed to invest, and users were just beginning to understand how the network would change everyday life. Today, AI shows the same set of signs — huge rounds of funding, infrastructure race, chip shortage, and constant announcements of new models.

The difference is that the internet fairly quickly found clear use cases for millions of people: search, email, browser, online stores. AI has it more complicated so far. The technology is already able to write code, summarize documents, help with customer support, and automate routine tasks, but for the mass market it still often looks like a set of impressive demos.

A user sees the power of the model, but doesn't always understand where daily indispensability begins — something that both individuals and companies are willing to pay for without experimenting for the sake of experimentation itself. So far this is the key barrier.

What's Missing

This is exactly what Bloomberg calls the missing ingredient. Not another more powerful model and not another investment record, but a combination of a clear product, sustainable economics, and the user habit of returning to it every day. In the language of the internet boom, it's not about proving that technology works, but about showing why life and work are now uncomfortable without it.

• Simple scenarios that are understandable without lengthy onboarding
• Stable quality so results don't need to be double-checked every time
• Clear pricing that justifies use outside of test mode
• Integration into familiar products, not separate AI showcases

The "secret sauce" is still lacking.

This explains the current market contrast well. On one hand, the largest players are building data centers, buying up GPUs, and competing on release speed. On the other hand, business is still searching for the formula in which an AI service becomes not a one-time function, but a systemic layer of the product. It is at this moment that it will become clear which companies are generating temporary noise and which are building the foundation of the next platform. There is no answer yet.

Where the Turnaround Will Come

Most likely, the turning point will not be in the model itself, but at the level of packaging. The internet won not because users fell in love with protocols and servers, but because they received convenient interfaces and services with obvious benefits. For AI, such a turnaround could come from assistants within office software, search, customer support, e-commerce, and development — places where the system saves hours, reduces costs, or brings revenue, rather than simply answering questions beautifully.

Hence the main question for the coming years: who will be able to turn AI from expensive computing power into an everyday tool with measurable effect. The winners will probably not be those with the loudest brand, but those who better integrate models into workflows, reduce friction, and show concrete ROI. If this happens, the market will get its own version of a browser, search engine, or cloud service — that is, a product after which the industry will stop looking like an endless beta test.

What It Means

Bloomberg's commentary effectively cools down inflated expectations: the technological revolution has already begun, but its commercial form has not yet settled. For the market, this is a signal to look not only at models and startup valuations, but at products that establish habit, provide predictable results, and become daily infrastructure.