Venture Capital Industry
How does AI reshape who gets funded, who funds, and what "venture capital" even means?
The venture capital industry is undergoing structural transformation. Two forces converge: AI collapses the cost of building software to near zero, and crypto creates permissionless capital formation outside the GP/LP structure.
The Numbers
| Metric | 2024 | 2025 | 2026 (est) |
|---|---|---|---|
| AI share of global VC | 33% | 53-61% ($211-270B) | approaching $500B |
| Total global VC | — | $427-512B | — |
| AI deal count | — | 7,176 (31% of all deals) | — |
| Bay Area share of AI funding | — | 60% | — |
| North America share | — | ~80% ($214.5B) | — |
| Late-stage share of all VC | — | ~50% | growing |
| Largest single round | — | OpenAI $40B (SoftBank) | — |
58% of AI funding in 2025 went to rounds of $500M+. The top 5 AI companies raised $84B — 20% of all VC. Deal counts falling (9,844 in Q4 2025, lowest since 2020) while total dollars rise. Fewer bets, bigger bets.
Source: OECD, Crunchbase, EY, Qubit Capital
AI Impact
Capital Concentration
Capital flows toward AI infrastructure, vertical AI, agentic systems, robotics, defence tech, and healthcare AI. It flows away from traditional SaaS, climate tech with long development cycles, and horizontal consumer plays.
Sub-$1B VC funds struggle to compete on AI deal flow. The winners run larger funds deploying larger rounds. 85% of VC dealmakers now use AI for deal sourcing (up from 76% in 2024). 82% use it for company research (up from 64%). Firms like SignalFire, EQT, and Correlation Ventures run AI-powered platforms for deal evaluation and predictive scoring.
The 1000x Team
AI-native startups hit $30M ARR in 20 months vs 60+ for traditional SaaS. Top AI startups reach $125M ARR by year 2. Revenue per employee: $3.48M vs ~$610K for leading SaaS companies.
| Metric | AI-native | Traditional SaaS |
|---|---|---|
| Time to $30M ARR | 20 months | 60+ months |
| Revenue per employee | $3.48M | ~$610K |
| ARR per FTE benchmark | $1.13M | — |
| YoY new customer growth | 360% | 24% |
| Gross margins (2026 est) | 52% | stable |
| Sales efficiency | 1.6x better | baseline |
2 engineers with AI tools now do the work of 5-10. This breaks the VC model at the root:
- Less capital needed — seed dollars shift from headcount to distribution and inference costs
- Faster to revenue — some skip Series A entirely
- Higher margins — the team stays small even as revenue scales
- Different evaluation — output quality and distribution matter more than headcount or burn rate
The question for VCs: if the best companies never need your money, what do you offer?
Post-AI Value
- Distribution — access to customers, channels, partnerships
- Pattern recognition — spotting market timing and founder-market fit
- Governance — board discipline, hiring networks, exit strategy
- Brand signal — a tier-1 fund on the cap table still opens doors
The value shifts from capital to connections. The GP who brings customers beats the GP who brings cash.
The deeper shift: AI agents in your wallet verify truth and alignment before you invest. Not trust-me. Verify-then-trust. When verification is automated, the investor's scarce resource is judgment — knowing which future to fund. This is why investing as long-term decision making is the most undervalued capability in education. See Participatory Capital for how this plays out.
Crypto Impact
Permissionless Capital
DAO treasuries exceeded $40B in early 2025, functioning as decentralised venture capital. Token launches, crowd sales, and DAO treasuries create alternative funding paths that bypass the GP/LP structure entirely.
- Arbitrum DAO — manages hundreds of millions via subDAOs for developer incentives
- Optimism Collective — distributes tens of millions via Retroactive Public Goods Funding
- Gitcoin DAO — quadratic funding for open-source, climate, and DeSci grants
- MakerDAO — "Endgame" with MetaDAOs for modular governance and real-world asset lending
- MetaCartel DAO — Web3 incubator funding dApps without traditional pitch processes
Q2 2025 crypto VC: $1.97B across 378 deals. Banks and enterprises now participate in or launch DAOs. Governance evolving toward professionalized, low-frequency decisions with AI agents handling grants management and Sybil detection.
DePIN Convergence
Delphi Digital tracks the AI + DePIN intersection — where decentralised physical infrastructure (sensors, compute, energy) meets machine intelligence. This creates a new asset class that traditional VC is slow to underwrite.
Stablecoin Rails
Stablecoin market cap approaching $500B. This matters for VC because:
- Global deal flow settles instantly without banking friction
- Emerging market founders access capital without local banking constraints
- Returns can compound in yield-bearing stablecoins between deployments
Sector Predictions
From thesis-driven firms (Framework Ventures, Delphi Digital):
| Sector | Direction | Signal |
|---|---|---|
| AI infrastructure | Strong growth | Chips, data centres, foundation models |
| Vertical AI | Gaining share | Industry-specific applications |
| Robotics | Accelerating | Hardware cost + AI capability convergence |
| DeFi | Maturing | Fee switch activation, institutional adoption |
| Solana ecosystem | Shifting | From meme coins to institutional products |
| New L1s (Berachain, Monad) | Emerging | Purpose-built chains for DeFi |
| Traditional SaaS | Declining share | Without AI differentiation |
| Crypto regulation | Clarifying | US market structure bill expected |
Notable Voices
What the sharpest investors are saying about 2026:
- Conor Moore (KPMG): Non-AI startups struggle for funding as investors prioritize AI models, apps, and infrastructure
- Bain Capital Ventures: Incumbents countering AI natives, open-source catching up, agent infrastructure as key opportunity
- Andrew Ferguson (Databricks Ventures): Enterprises ending AI experimentation — rationalizing tools, picking winners, shrinking budgets for undifferentiated startups
- Rob Biederman (Asymmetric Capital Partners): Few vendors capture most enterprise AI budgets. Defensible startups need proprietary data
- a16z: Open-source AI reaching parity. Hybrid model stacks ending "one model to rule them all." Agentic frameworks as the next wave
Forces
| Force | Effect on VC |
|---|---|
| AI cost collapse | Less capital needed per startup |
| AI concentration | More capital flowing to fewer AI plays |
| Token-based funding | Alternative to equity rounds |
| DAO governance | Alternative to board governance |
| Stablecoin settlement | Removes banking friction from deal flow |
| Regulation clarity | Opens institutional allocation |
Context
- VC Playbook — How to play the game
- Finance Services — Parent industry
- DePIN — Decentralised physical infrastructure
- DAOs — Decentralised governance
- Market Forces — What drives change
Links
- OECD — AI firms capture 61% of global VC in 2025
- Crunchbase — VCs expect more AI funding in 2026
- EY — Venture Capital Investment Trends
- Qubit Capital — AI Startup Fundraising Trends
- BCG — Closing the AI Impact Gap
- Framework Ventures
- Delphi Digital
Questions
What happens to the venture capital industry when the best startups don't need venture capital?
- If AI collapses the cost of building, does VC become a distribution business rather than a capital business?
- Which LP categories (pensions, sovereigns, endowments) adapt fastest to token-based fund structures?
- When does a DAO treasury outperform a traditional VC fund on risk-adjusted returns?