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The Great Power Redistribution: AI Startups vs. Big Tech in the Attention Economy

Everyone says AI concentrates power in Big Tech. The data says the opposite. Startups went from 3% to 86% of Big Tech's AI coverage in five years. What the narrative got wrong.

MMNTM Research
12 min read
#Research#AI Trends#Startups#Big Tech#Market Analysis

The Narrative

The conventional wisdom: AI concentrates power in Big Tech. Only companies with massive compute, proprietary data, and billions in capital can compete. Startups are either acqui-hired or crushed.

The data tells a different story.

Startup Coverage Ratio

3% → 86%

AI startups vs Big Tech AI coverage (2020 → 2025)

We analyzed AI coverage across 77,000 Techmeme articles. In 2020, AI startups received 3% of the coverage that Big Tech's AI efforts received. By 2025, that ratio hit 86%. Near parity.

The power isn't concentrating. It's redistributing.


The Data

Coverage Ratio Over Time

FeatureYearAI Startup ArticlesBig Tech AI ArticlesRatio
20202020154560.03x
20212021164550.04x
20222022385070.07x
202320233968710.45x
202420245969900.60x
202520259741,1390.86x

The Inflection Point: 2023

The ChatGPT launch (November 2022) triggered the inflection. Startup coverage went from 38 articles (2022) to 396 articles (2023)—a 10x increase in one year.

Big Tech AI coverage also grew, but only 1.7x. The gap closed because startups grew faster.

Q4 2025: Approaching Crossover

The most recent quarter shows the trend accelerating:

  • AI Startups: 289 articles
  • Big Tech AI: 325 articles
  • Ratio: 0.89x

At current trajectory, startup coverage will exceed Big Tech AI coverage within 2-3 quarters.


What's Driving It

1. The Application Layer Opened

Foundation models became APIs. You no longer need to train your own GPT—you call OpenAI, Anthropic, or Google's API. This collapsed the barrier from "billions in compute" to "credit card and good ideas."

The vertical agents winning thesis plays out here: specialized applications on top of foundation models capture value that the foundation model providers can't.

2. The Enterprise Buyer Arrived

Enterprise AI share grew from 29% (2023) to 43% (2025). Enterprise buyers want solutions, not platforms. They buy from startups who understand their workflows.

Sample headlines showing enterprise traction:

"Anthropic and Accenture sign three-year deal to sell AI services to businesses" — 2025-12-09

"Snowflake and Anthropic announce $200M deal for Claude models" — 2025-12-04

"ServiceNow says it plans to acquire agentic AI company Moveworks for $2.85B" — 2025-03-11

Big Tech builds platforms. Startups build solutions. Enterprise buys solutions.

3. The Talent Distribution

The best AI researchers don't all work at Google anymore. They founded Anthropic, Character.AI, Mistral, Cohere, Adept. The "brain drain" headlines of 2022-2023 were leading indicators:

"Anthropic, a new startup from former GPT-3 researchers that aims to build large-scale, general AI systems, raises $124M Series A" — TechCrunch, May 2021

"Paris-based Mistral AI raised a €105M seed led by Lightspeed, sources say at a €240M valuation, to take on OpenAI" — TechCrunch, June 2023

"A profile of nine-month-old Mistral AI, which wants to be the 'most capital-efficient company in the world of AI', has raised $500M+, and is valued at $2B+" — Wall Street Journal, February 2024

The talent redistribution preceded the coverage redistribution by 1-2 years.


The Contrarian Case

Why the "Big Tech Wins" Narrative Persists

Compute moats are real but narrowing. Yes, training frontier models requires massive compute. But:

  • Inference costs dropped 90%+ in 18 months
  • Open weights models (Llama, Mistral) democratized capability
  • Specialized fine-tuning beats general scale for vertical applications

Data moats are overrated. The best AI applications aren't built on proprietary training data—they're built on proprietary workflow integration. Harvey doesn't win because it has more legal documents. It wins because it's embedded in BigLaw's workflow. See Harvey Deep Dive.

Distribution is the real moat—and startups can build it. Cursor didn't beat GitHub Copilot with better AI. It beat Copilot with better UX and faster iteration. See Cursor Deep Dive.

What Big Tech Actually Has

  • Infrastructure: Cloud, chips, data centers
  • Existing distribution: Billions of users for consumer products
  • Capital: Ability to sustain losses longer

These matter for platform competition. They matter less for application competition. And applications are where the value capture is happening.


The Acquisition Signal

If startups were irrelevant, Big Tech wouldn't be buying them.

FeatureAcquisitionBuyerPriceDate
wizWizAlphabet$32B2025-03
groqGroqNvidia$20B2025-12
moveworksMoveworksServiceNow$2.85B2025-03
casetextCasetextThomson Reuters$650M2023-06

The Christmas 2025 Nvidia-Groq deal is the symbolic capstone:

"Nvidia agrees to a licensing deal with Groq; CEO Jonathan Ross and other top executives will join Nvidia" — Bloomberg, December 2025

"Alphabet acquires NYC-based cybersecurity startup Wiz for $32B cash, its largest acquisition yet" — The Verge, March 2025

Big Tech is paying premium prices to acquire what startups built.

The Paradox: If Big Tech had insurmountable advantages, they'd build rather than buy. The acquisition premiums prove the startups created value Big Tech couldn't replicate internally.


The Two-Pizza Thesis Validated

The two-pizza agent team thesis: small teams of senior engineers with AI assistance outproduce large teams.

The coverage data validates it. Small teams are capturing disproportionate attention—and attention precedes value capture.

Why Small Teams Win in AI

  1. Faster iteration: Ship daily, not quarterly
  2. Direct customer contact: Founders doing support calls
  3. No coordination overhead: Decisions in minutes, not committees
  4. AI leverage: The AI-assisted engineering playbook favors small teams

The why small wins analysis quantified the "friction coefficient"—SMBs deploy agents 9x faster than enterprises. The same dynamic applies to building AI companies.


What This Means

For Founders

The window is open. Startup coverage approaching Big Tech parity means the market is receptive. You can compete for attention, talent, and customers.

But the window is closing. The 2023-2025 redistribution won't last forever. Consolidation follows distribution. The Nvidia-Groq deal shows the endgame: Big Tech will acquire what it can't build.

Build fast. Build deep. Build defensible.

For Investors

The coverage signal is leading. Startups that capture attention before capture revenue are the ones to watch. The 0.03x → 0.86x shift happened in coverage before it showed up in market share.

Vertical > Horizontal. The startups gaining coverage are vertical specialists, not horizontal platform plays. See vertical agents winning.

For Big Tech

The acqui-hire playbook is expensive. $20B for Groq. $32B for Wiz. The talent and capability that left is only getting more expensive to buy back.

Platform plays are defensive. Google, Microsoft, and Amazon are building AI platforms. But the application layer—where value gets captured—is fragmenting across thousands of startups.


The Arc

PhaseYearsDynamic
Concentration2017-2022Big Tech dominated AI research and coverage
Inflection2023ChatGPT opened the application layer
Redistribution2024-2025Startups approached coverage parity
Consolidation2026+Acquisitions accelerate, winners emerge

We're in the redistribution phase. The question isn't whether startups can compete—they already are. The question is which ones will be acquired vs. which will become the next Big Tech.


Methodology

Dataset: 77,000 Techmeme articles (2017-2025) Classification: Articles tagged by entity mention (startup vs. Big Tech) and AI-adjacency score Big Tech defined as: Google, Microsoft, Apple, Amazon, Meta, and their AI subsidiaries AI Startups defined as: Companies founded after 2015, AI-native, not acquired by Big Tech

For full methodology, see The AI Infiltration Effect.


See also: Why Small Wins for the friction coefficient analysis, Two-Pizza Agent Team for team structure, and Vertical Agents Winning for market positioning.

The Great Power Redistribution: AI Startups vs Big Tech