Enterprise AI, AI infrastructure, and vertical AI dominate funding rounds. Consumer AI struggles for traction.
Global AI startup funding reached $48 billion in Q1 2026, according to PitchBook data—a 35% increase over Q1 2025 and the highest quarterly total since the generative AI boom began. But the composition of deals has shifted dramatically from the 'spray and pray' approach of 2023–2024.
Enterprise AI captured the lion's share at $22 billion, with investors favouring companies that can demonstrate clear ROI and paying customers over those selling potential. Glean (enterprise search, $4.2B valuation), Harvey (legal AI, $3.1B), and Cohere (enterprise LLM platform, $6.5B) led the largest rounds.
AI infrastructure—the 'picks and shovels' of the boom—attracted $15 billion. GPU cloud providers (Lambda, CoreWeave, Together AI), vector database companies (Pinecone, Weaviate), and observability platforms (Arize, Weights & Biases) are all seeing surging demand as enterprises move from experimentation to production deployment.
Vertical AI—companies building domain-specific AI solutions for healthcare, finance, legal, and manufacturing—raised $8 billion. These companies typically combine proprietary datasets with fine-tuned models to deliver performance that general-purpose models can't match. Vincony's Fine-Tuning pipeline is a key enabler for many of these vertical AI startups.
Consumer AI, by contrast, has struggled. Outside of ChatGPT and a handful of creative tools, consumer AI apps have failed to achieve durable retention. VCs report that most consumer AI apps see 80% user churn within 30 days, making them difficult to fund at scale.
For startup founders and investors tracking the AI funding landscape, Vincony's Deep Research tool can synthesise deal data, competitive landscapes, and market sizing analyses across any AI vertical in minutes.