A divide in the AI boom: big players take it all, startups disillusioned

The AI boom is losing its shine even in the tech industry. Major players like OpenAI, Google and Meta are concentrating resources and revenue, while thousands of startups are contracting without any clear profitable use case. The wave of optimism has given way to disappointment and skepticism.

AI-processed from TechCrunch; edited by Hamidun News
A divide in the AI boom: big players take it all, startups disillusioned
Source: TechCrunch. Collage: Hamidun News.
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Article Fact Sheet & Key Figures
ParameterDetails
Primary sourceTechCrunch ↗
Editor-in-Chief
Key metric #1Access to massive datasets and the ability to process them without limitations
Key metric #2Capital to experiment with world-class models
Key metric #3A direct path to monetization through APIs and their own integrated products

AI-Boom Loses Its Shine. Even in the tech industry, which should have been euphoric about digital gold, the atmosphere is becoming increasingly skeptical and tense.

Big Players Take Everything

The picture is clear: OpenAI, Google, Meta, and a handful of other giants are concentrating resources, computational power, and AI profits in their hands. They have:

  • Access to massive datasets and the ability to process them without limitations
  • 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 overpay competitors for

The rest — tens of thousands of mid-level startups — sit with a hammer looking for nails. Every new project knows: it's competing not with another startup, but with a team at Google that can rewrite the foundational model in three months.

Startups Hemorrhage Money Without Clear Purpose

For a new company, the path to success looks increasingly unpredictable. Computing is expensive (paying OpenAI for API access, renting the cloud for training), competition is fierce, and ROI remains an abstraction. Investors still give money, but no longer blindly. They demand concrete metrics, user growth, clear understanding of monetization.

Result: thousands of startups from 2023–2024 are either cutting development, looking for acquirers among giants, or slowly dying while waiting for a miracle.

Wave of Optimism Quickly Fades

The vibe is changing. At conferences and in tech industry Slack channels, you hear less and less "AI will solve all problems," and more and more "why do we need another AI startup?" Even technologists, who should believe in innovation, are beginning to view the next LLM project with skepticism.

The reasons are mundane. Most AI applications are either wrapped around OpenAI (and completely dependent on their API) or trying to compete directly with Google and Meta, which is practically impossible.

What This Means

The golden age of easy AI startups may be behind us. Ahead lies an era of consolidation — major players dominate, innovation happens either inside them or in narrow niches. For investors and founders, a simple "another chatbot" no longer works. You need a unique niche, deep integration, or simply excellent leadership — old as the world, timeless startup rules.

Story

Key Questions Answered

What are the key details on Big Players Take Everything?

The picture is clear: OpenAI, Google, Meta, and a handful of other giants are concentrating resources, computational power, and AI profits in their hands. They have: Access to massive datasets and the ability to process them without limitations 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 overpay competitors for The rest — tens of thousands of mid-level startups — sit with a hammer looking for nails. Every new project knows: it's competing not with

What are the key details on Startups Hemorrhage Money Without Clear Purpose?

For a new company, the path to success looks increasingly unpredictable. Computing is expensive (paying OpenAI for API access, renting the cloud for training), competition is fierce, and ROI remains an abstraction. Investors still give money, but no longer blindly. They demand concrete metrics, user growth, clear understanding of monetization. Result: thousands of startups from 2023–2024 are either cutting development, looking for acquirers among giants, or slowly dying while waiting for a miracle.

What are the key details on Wave of Optimism Quickly Fades?

The vibe is changing. At conferences and in tech industry Slack channels, you hear less and less "AI will solve all problems," and more and more "why do we need another AI startup?" Even technologists, who should believe in innovation, are beginning to view the next LLM project with skepticism. The reasons are mundane. Most AI applications are either wrapped around OpenAI (and completely dependent on their API) or trying to compete directly with Google and Meta, which is practically impossible.

ZK
Zhemal Khamidun — CPO at Alpina Digital, product manager of AlpinaGPT. Building AI products since 2019. Hamidun News is a pet project that grew into a production aggregator with 6,000+ readers.
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