PitchBook: VC investment in AI and machine learning companies totaled nearly $80B in 2023, accounting for 23% of deals, the largest of any sector
Context & Ripple Effects
This marks an early benchmark for AI’s shift from a prominent venture category to the market’s leading destination for deal activity. Subsequent coverage reinforced the breadth of that buildout, including $330B invested across roughly 26,000 AI and ML startups over three years.
The concentration intensified rather than receded: later PitchBook data showed AI taking 36% of US VC deal value in the first three quarters of 2024, putting the 2023 result in the opening phase of a sustained allocation shift.
First-order effects
- AI and ML startups entered fundraising with the strongest sector-level signal of investor appetite, improving their relative access to venture attention and capital.
- PitchBook’s data gave VCs and limited partners a clear benchmark: AI/ML had become the largest sector by deal share, not merely a handful of headline financings.
Second-order effects
- Startups in other venture categories faced a tougher relative competition for partner time and fund reserves as investors prioritized AI-related pipelines.
- The volume of AI financings creates pressure for investors to differentiate between companies with durable technical or commercial advantages and a broad field using the same label.
Third-order effects
- If the allocation pattern persists, venture returns and portfolio construction will become more dependent on a single technology cycle, raising the importance of eventual exits and realized outcomes.
- The pattern points toward a more concentrated AI funding market over time, where capital may increasingly cluster around the companies able to support large-scale development and infrastructure needs.
The trend: AI is becoming venture capital’s dominant allocation theme, with funding concentration likely to shape which startups can scale and which sectors receive less risk capital.