B2B Token Demand vs. Infrastructure Buildout: A Reality Check

The Big Insight

The infrastructure buildout isn't a bubble—it's undershooting demand. GPU utilization is running at 90-100% across all NVIDIA generations, with Blackwell, H100, and H200 sold out a full year in advance (Report 6). Meanwhile, enterprise gen AI spending jumped 3.2x in a single year—from $11.5B to $37B (Report 8, Menlo Ventures data). The "bubble" fear gets the causality backwards: companies like Anthropic are doubling revenue every six months not because of hype, but because enterprises can't get enough tokens fast enough.

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1. Total Market Estimate

Trailing-12-month B2B token spend (excluding OpenAI consumer): $45-55B

Segment	Revenue Estimate	Source
Anthropic B2B (85% of $9B run-rate)	~$7.7B	Report 4
Foundation APIs total (Menlo data)	$12.5B	Report 8
AI coding tools (Copilot, Cursor, etc.)	$4B departmental	Report 8
Enterprise gen AI apps total	$19B	Report 8
Enterprise gen AI infra total	$18B	Report 8

The Menlo Ventures data from Report 8 provides the most comprehensive view: $37B in enterprise gen AI revenue in 2025, split roughly evenly between applications ($19B) and infrastructure ($18B). Foundation model APIs—the pure token-selling layer—represent $12.5B of the infrastructure spend.

Breaking down the application layer (Report 8):
- Coding tools: $4B (55% of departmental AI)
- Copilots/horizontals: $7.2B (86% of horizontal spend)
- Verticals (healthcare, legal, etc.): $3.5B
- Other departmental: $4.3B

Key individual players with disclosed or estimated revenue:
- Anthropic: $9B run-rate end-2025, with $18B forecast for 2026 (Report 4)
- Lovable: $300M ARR as of January 2026, up from $17M in early 2025 (Report 3)
- Harvey: >$100M ARR from 700 enterprise clients (Report 2)
- Cursor: $100-200M estimated annualized (Report 1)
- GitHub Copilot: $500-700M annualized by 2026 (Report 1)

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2. Market Segmentation

Largest Segments by Revenue

1. Foundation Model APIs: $12.5B (Report 8)
This is the purest "token-selling" layer. Anthropic alone represents roughly $7.7B of B2B API revenue, with 9 enterprise customers each spending >$100M annually—exceeding OpenAI's seven such customers (Report 4). Microsoft alone is on pace for $500M+ in Anthropic spend.

2. Coding Tools: $4B (Report 8)
The coding segment dominates departmental AI at 55% share. Individual players:
- GitHub Copilot: 1M+ paid seats, $500-700M revenue (Report 1)
- Cursor: ~$100-200M, raised at 30x revenue multiple (Report 1)
- Codeium/Tabnine combined: $80-160M (Report 1)
- CB Insights pegs the total coding AI copilots market at $4B with top-3 players holding 70%+ share (Report 1)

3. Copilots/Horizontals: $7.2B (Report 8)
This 86% share of horizontal AI spend reflects the enterprise adoption of ChatGPT-style assistants and productivity tools.

4. Verticals: $3.5B (Report 8)
Healthcare alone represents nearly 50% of vertical AI spend (~$1.5B) and tripled YoY. Legal AI (Harvey, CoCounsel) represents a smaller but high-margin slice at 40-80x revenue multiples (Report 2).

Fastest-Growing Categories

Category	Growth Rate	Evidence
Lovable/dev tools	17x in 9 months ($17M → $300M)	Report 3
Anthropic	2x in 6 months ($4B → $9B run-rate)	Report 4
Healthcare vertical	3x YoY	Report 8
Enterprise gen AI total	3.2x YoY ($11.5B → $37B)	Report 8
Departmental AI	4.1x YoY ($1.8B → $7.3B)	Report 8

The "vibe coding" segment (Lovable, Bolt, v0) shows the most explosive growth—Lovable went from $17M ARR in early 2025 to $300M by January 2026 at a $6.6B valuation (Report 3). This represents ~17x growth in under a year, though it's building on a small base.

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3. Supply-Demand Dynamics: Is This a Bubble?

The evidence strongly suggests demand exceeds supply, not the reverse.

Evidence FOR infrastructure justification:

GPU Utilization at Capacity (Report 6)
- All NVIDIA GPU generations running 90-100% utilization
- Blackwell, H100, and H200 variants sold out 12+ months in advance
- OpenAI committed to 10GW+ of NVIDIA systems
- Anthropic secured 1GW initial Grace Blackwell deployment
- xAI building 2GW Colossus facility
- Six years post-launch, A100 systems still at full utilization

Demand Growth Outpacing Supply Expansion
- Enterprise gen AI revenue grew 3.2x from 2024 to 2025 (Report 8)
- Anthropic's revenue doubled in 6 months (Report 4)
- Lovable grew 17x in 9 months (Report 3)
- KPMG survey: 67% of enterprise leaders committing $124M average AI spend over next 12 months, even in recession scenarios (Report 8)

Pricing Power Intact
- Revenue multiples expanding, not compressing: Cursor at 30x, Lovable at 33x, Harvey at 80x (Reports 1, 2, 3)
- Token resellers maintaining 50-85% gross margins at 4-15x markups on wholesale (Report 7)
- No significant price wars despite massive VC funding into the space

The Math Check

Report 7 and 8 provide the critical comparison:
- Hyperscaler capex for 2026: $527B, potentially rising to $600B in 2027
- Enterprise gen AI revenue 2025: $37B, growing 3.2x YoY
- Projected 2026 enterprise gen AI (if 3.2x holds): ~$120B

At these growth rates, enterprise AI revenue could reach $120B+ in 2026 and $380B+ in 2027. Against $527-600B in annual hyperscaler capex, this implies:
- Current revenue/capex ratio: ~7% (2025 revenue vs. 2026 capex)
- Projected 2027 ratio: ~60%+ (2027 revenue vs. 2027 capex)

This trajectory is consistent with historical tech infrastructure builds (fiber optic, cloud) where capex front-runs revenue by 2-3 years. The 24% CAGR projected for data center GPU spend from $48B (2026) to $1T+ (2040) aligns with Gartner's AI spending projections (Report 6, Report 8).

The Counterargument

The one caution from Report 8 (Sequoia): 2026 may be the "Year of Delays" for data centers and AGI, with 40%+ of agentic AI projects potentially cancelled by 2027. However, this risk is to experimental projects, not the core token-consumption business lines that are already generating tens of billions in revenue.

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4. Key Insights

1. Anthropic Is the Elephant in the Room

At $9B run-rate (85% B2B), Anthropic alone represents roughly 20% of all enterprise gen AI spending (Report 4, Report 8). Their $18B 2026 forecast would make them larger than the entire enterprise gen AI market was in 2024. This concentration—and their multi-gigawatt compute commitments—suggests infrastructure demand is being pulled by a handful of massive winners, not distributed speculation.

2. The "Token Reseller" Layer Is the Real Growth Story

Companies like Lovable, Cursor, and Harvey aren't building foundation models—they're reselling tokens with domain-specific value (Report 1, 2, 3). Lovable grew 17x in 9 months; Harvey commands 80x revenue multiples. The research shows 50-85% gross margins are achievable at 4-15x markups (Report 7). This suggests a sustainable arbitrage layer between foundation model providers and end-users that justifies significant infrastructure demand.

3. Coding Is the Killer App—$4B and Accelerating

Coding tools represent 55% of departmental AI spend and are the single largest identifiable application category (Report 8). The segment includes a clear market structure: GitHub Copilot at $500-700M leading, with Cursor, Codeium, and others filling a $4B+ market growing at 50%+ annually (Report 1). This is real, measurable demand driven by quantifiable productivity gains.

4. Infrastructure Constraints Are Real, Not Manufactured

NVIDIA's earnings explicitly show supply limitation, not demand weakness (Report 6):
- A minor 0.9% sequential compute sales dip was attributed to networking budget reallocations, not slack demand
- Networking revenue surged 97.7% to $7.25B as clusters prioritize scale-out
- The constraint has shifted from chip availability to power/energy infrastructure

The pivot from GPU scarcity to power constraints (driving NVIDIA's "Green AI" Rubin architecture with 40% efficiency gains) indicates the bottleneck is moving, not disappearing.

5. The Risk Is Concentration, Not Oversupply

The research reveals extreme concentration: top-3 coding players hold 70%+ market share (Report 1); 9 Anthropic customers spend $100M+ each (Report 4); 58% of AI funding went to $500M+ megarounds (Report 8). The bubble risk isn't overcapacity—it's that a handful of companies failing to monetize could cascade into infrastructure writedowns. But their current utilization rates and revenue trajectories don't support that scenario through 2027.

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Strategic Implications

For infrastructure investors: The demand-supply mismatch is real. GPU utilization at capacity plus 3.2x annual revenue growth suggests we're still in the "undersupply" phase of the cycle. The shift from chip constraints to power constraints (Report 6) extends the runway for infrastructure investment.

For token resellers: The 50-85% gross margin window (Report 7) is sustainable while foundation model prices continue falling (Anthropic cut Opus pricing 67%—Report 7). The winning strategy is domain-specific value capture (Harvey's 80x multiple vs. generic resellers' margin compression).

For bubble skeptics: The research consistently shows demand exceeding supply across every metric—utilization, pricing power, revenue growth, forward commitments. Sam Altman and Anthropic saying they "can't keep up with token demand" appears to be accurate, not marketing spin.