The AI Agent Gold Rush: Who’s Actually Winning (Feb 2026 Data)
This market is still growing very fast!
I spent the past week collecting data on the AI agent ecosystem. Not opinions. Not vibes. Actual numbers — revenue, funding rounds, GitHub stars, enterprise adoption rates, ROI case studies.
127 data points from 65 sources. And the picture they paint is different from what most people assume.
Here’s what I found.
The Market Is Bigger Than You Think
The AI agent market hit $7.84 billion in 2025. It’s projected to reach $52.6 billion by 2030 — that’s a 46% compound annual growth rate. For context, the entire SaaS market grew at about 18% during its fastest period.
But here’s the number that surprised me most: $238 billion in total AI funding in 2025 alone. That’s 47% of all venture capital deployed globally. Nearly half of every dollar investors put to work went into AI.
This isn’t a bubble forming. It already formed. The question now is who captures the value.
The Big 5 Race (Spoiler: Anthropic Is Winning)
I tracked revenue, valuation, and product launches for the major players. Here’s what the data shows:
Anthropic hit $9 billion ARR in January 2026. Claude Code alone reached $1 billion ARR just six months after general availability. They’re forecasting $18-26 billion for 2026. That’s not a typo.
OpenAI did $13 billion in 2025 (236% growth) with 700 million weekly ChatGPT users. But they’re still projecting $14 billion in losses for 2026. Scale matters, but so does unit economics.
Microsoft’s Copilot has 15 million paid seats (160% YoY), but only 3.3% of free users convert to paid. Salesforce’s Agentforce hit $500M+ ARR (330% growth). Google’s Gemini doubled its MAU to 650 million.
The pattern I see: the companies winning aren’t just building better models. They’re building better developer tools and protocols. Anthropic’s MCP protocol just got donated to the Linux Foundation — and OpenAI, Google, and Microsoft all adopted it. That’s a standards play, not just a product play.
The Framework Wars Are Consolidating
I tracked 12 major agent frameworks by GitHub stars, adoption, and enterprise usage. The landscape is consolidating fast:
AutoGPT still leads GitHub stars (182K) but is more community than enterprise
LangChain dominates integrations (700+) with 187M monthly PyPI downloads
Microsoft is merging AutoGen + Semantic Kernel into one Agent Framework (Q1 2026)
OpenAI deprecated Swarm and launched Agents SDK (Feb 6, 2026) — provider-agnostic, supports 100+ LLMs
The trend is clear: fewer frameworks, more standardization. If you’re picking a framework today, bet on the ones backed by companies with distribution — not just GitHub stars.
Where the Money Actually Goes
I collected ROI data from 7 major enterprise deployments. The average ROI on agentic AI is 171% (192% in US enterprises). That’s 3x higher than traditional automation.
The standout cases:
Klarna: $60M saved, replaced 700 agents, resolution time from 11 min to 2 min
JPMorgan: 360,000 hours saved annually (equivalent to 180 positions)
Customer service broadly: AI costs $0.25-0.50 per interaction vs $3-6 for humans — 85-90% cost reduction
The data suggests customer service and coding are the two beachheads. Finance (85% adoption) and manufacturing (77%) lead by industry.
Want the full dataset?
I compiled all 127 data points into a structured report with machine-readable files (JSON + CSV) you can load directly into your AI agent or analysis tools.
AI Agent Landscape Report (Feb 2026) — $4.99
Includes: Market data, framework comparison matrix, enterprise ROI breakdown, investment trends, and sources. Paid subscribers can get it for free.
What I Think This Means
After sitting with all this data, three things stand out to me:
1. Protocol wins over product. Anthropic’s MCP strategy might be the most important move of 2025-2026. Control the protocol, control the ecosystem.
2. The gap between adopters and non-adopters is accelerating. Finance at 85% adoption vs insurance at 34%. The laggards aren’t just behind — they’re falling further behind every quarter.
3. Developer tools are the real battleground. Claude Code ($1B ARR in 6 months), Devin ($155M ARR trajectory), GitHub Copilot. The companies that make developers productive with agents will own the next cycle.
I compiled all 127 data points into a structured report with charts, framework comparisons, and a machine-readable knowledge file you can feed directly to your AI agent.
Get the Full Data
This post covers the key findings. The complete AI Agent Landscape Report includes:
All 127 data points in machine-readable format (JSON + CSV)
Framework comparison matrix
Enterprise adoption heatmap
Investment trends analysis
Full sources and methodology
$4.99 — Get it here
Thanks for reading,
Pawel
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