AI boom splits in two: big players take everything, startups are disillusioned
The AI boom is losing its shine, even inside the tech industry. Big players such as OpenAI, Google and Meta are concentrating resources and revenue, while thousands of startups shrink without a visible profitable use case. The wave of optimism has given way to disappointment and skepticism. *Meta is designated an extremist organization and banned in Russia.
AI-processed from TechCrunch; edited by Hamidun News
The AI boom is losing its shine. Even in the tech industry, where euphoria over digital gold was supposed to reign, the atmosphere is turning increasingly skeptical and tense.
The big players take everything
The picture is clear: OpenAI, Google, Meta and a few other giants hold the resources, the computing power and the profits from AI. They have:
- Access to enormous datasets and the ability to process them without restrictions
- Capital to experiment with world-class models
- A direct path to monetization through APIs and their own integrated products
- The best scientists and engineers, whom they can afford to overpay relative to competitors
Everyone else, tens of thousands of mid-tier startups, is holding a hammer and looking for nails. Every new project knows it is competing not with another startup but with a team at Google that can rewrite a base model in three months.
Startups bleed money with no visible goal
For a new company, the path to success looks increasingly unpredictable. Compute is expensive (paying OpenAI for API access, renting cloud capacity for training), competition is brutal, and ROI remains an abstraction. Investors still write checks, but no longer blindly. They demand concrete metrics, user growth and a clear understanding of monetization.
The result: thousands of startups from 2023–2024 are either scaling back development, looking for buyers among the giants, or slowly dying while waiting for a miracle.
The wave of optimism is fading fast
The vibe is changing. At conferences and in the tech industry's Slack channels, you hear "AI will solve all problems" less and less, and "why do we need yet another AI startup?" more and more. Even technologists, who are supposed to believe in innovation, are starting to look skeptically at the next LLM project.
The reasons are mundane. Most AI applications are either wrappers around OpenAI (and depend entirely on its API) or try to compete directly with Google and Meta, which is practically impossible.
What this means
The golden age of lightweight AI startups may be over. An era of consolidation lies ahead: the big players dominate, and innovation happens either inside them or in narrow niches. For investors and founders, a simple "one more chatbot" no longer works. What it takes is a unique niche, deep integration or simply excellent leadership, the old-as-time rules for startups.
*Meta is designated an extremist organization and banned in Russia.
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Key Questions Answered
What are the key details on The big players take everything?
The picture is clear: OpenAI, Google, Meta and a few other giants hold the resources, the computing power and the profits from AI. They have: Access to enormous datasets and the ability to process them without restrictions Capital to experiment with world-class models A direct path to monetization through APIs and their own integrated products The best scientists and engineers, whom they can afford to overpay relative to competitors Everyone else, tens of thousands of mid-tier startups, is holding a hammer and looking for nails. Every new project knows it is competing not w
What are the key details on Startups bleed money with no visible goal?
For a new company, the path to success looks increasingly unpredictable. Compute is expensive (paying OpenAI for API access, renting cloud capacity for training), competition is brutal, and ROI remains an abstraction. Investors still write checks, but no longer blindly. They demand concrete metrics, user growth and a clear understanding of monetization. The result: thousands of startups from 2023–2024 are either scaling back development, looking for buyers among the giants, or slowly dying while waiting for a miracle.
What are the key details on The wave of optimism is fading fast?
The vibe is changing. At conferences and in the tech industry's Slack channels, you hear "AI will solve all problems" less and less, and "why do we need yet another AI startup?" more and more. Even technologists, who are supposed to believe in innovation, are starting to look skeptically at the next LLM project. The reasons are mundane. Most AI applications are either wrappers around OpenAI (and depend entirely on its API) or try to compete directly with Google and Meta, which is practically impossible.
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