Which AI companies are going public in 2026? Full IPO pipeline for OpenAI, Anthropic, xAI, Databricks, Cerebras and 80+ AI companies — readiness scores, valuations, S-1 filings. Updated monthly.
The artificial intelligence sector is the defining technology story of 2026. Foundation model valuations continue to compress as inference economics improve, while enterprise AI infrastructure spending hits record highs. This report tracks every significant AI company in the pre-IPO pipeline — from large language model labs to AI chip makers and vertical AI application companies — with proprietary IPO readiness scores and live valuation data.
OpenAI, valued at $852 billion after its most recent financing round, remains the most anticipated IPO candidate in history. Anthropic ($380B), xAI ($50B), and Databricks ($62B) follow as the most likely AI unicorns to access public markets in the 2026–2028 window. Cerebras Systems filed its S-1 in April 2026 and is the first pure-play foundation model infrastructure company to seek a public listing.
AI sector IPOs face a specific challenge: revenue visibility. Public market investors have historically penalized pre-revenue or low-revenue tech companies after 2021's correction. The AI companies most likely to IPO successfully will be those with durable enterprise contracts, high gross margins, and demonstrated path to profitability — not just headline valuation. This pipeline report tracks those signals.
| Company | Status | Valuation | Revenue | IPO Readiness |
|---|---|---|---|---|
| Anthropic | IPO Announced | $380B | $4B | 94 |
| OpenAI | IPO Announced | $852B | $13B | 86 |
| xAI | Pre-IPO | $80B | — | 83 |
| Lightmatter | S-1 Filed | $4.4B | — | 80 |
| Databricks | S-1 Filed | $134B | $4B | 76 |
| Lambda | Pre-IPO | $5.9B | — | 74 |
| Ironclad | Pre-IPO | $3.2B | — | 74 |
| Scale AI | S-1 Filed | $14B | — | 73 |
| Starcloud | Pre-IPO | $1.1B | — | 72 |
| Mistral AI | Pre-IPO | $6B | — | 72 |
| Nscale | S-1 Filed | $14.6B | — | 70 |
| Midjourney | Pre-IPO | $10B | — | 70 |
| Cohere | Pre-IPO | $9.2B | — | 69 |
| Lambda Labs | Private | $1.5B | — | 69 |
| Groq | Pre-IPO | $6.2B | — | 69 |
| Abnormal Security | Pre-IPO | $5.1B | — | 69 |
| Synthesia | Pre-IPO | $4B | — | 69 |
| Legora | S-1 Filed | $5.55B | — | 66 |
| Harvey | Pre-IPO | $11B | — | 66 |
| Tempus AI | Public | $8B | — | 64 |
| Perplexity AI | Pre-IPO | $20B | — | 63 |
| Axiom Math | Pre-IPO | $1.6B | — | 62 |
| Rhoda AI | Pre-IPO | $1.7B | — | 62 |
| Frore Systems | Pre-IPO | $1.64B | — | 61 |
| SentinelOne | Public | $15B | — | 60 |
| Character.ai | Pre-IPO | $5B | — | 60 |
| Palantir Technologies | Public | $200B | — | 59 |
| Glean | Pre-IPO | $4.6B | — | 59 |
| CoreWeave | Public | $35B | — | 58 |
| Inflection AI | Pre-IPO | $4B | — | 58 |
Revenue marked e = 2024 reported. IPO Readiness 0–100 proprietary score. How scores are calculated →
Cerebras Systems filed its S-1 in April 2026 and is the most imminent AI IPO. Databricks ($62B), Mistral, and Cohere are tracking for 2026–2027 windows. OpenAI and Anthropic remain private by choice despite massive valuations — OpenAI at $852B and Anthropic at $380B. xAI, Elon Musk's AI lab, has discussed a potential IPO but no timeline is confirmed.
Databricks is the most likely large AI IPO in 2026, with a $62B valuation, $2.4B+ in ARR, and strong enterprise data + AI platform revenue. OpenAI would be the largest AI IPO in history at $852B, but the company has indicated it prefers to remain private until at least 2027.
IPO readiness scores (0–100) measure five signals: revenue scale and growth rate, profitability trajectory, S-1 or listing activity, institutional ownership quality, and time since last private funding round. Higher scores indicate companies with stronger public market readiness fundamentals.
Both companies have sufficient access to private capital at valuations that would make an IPO dilutive rather than additive. OpenAI raised at $157B then $300B in quick succession. Anthropic raised at $380B from Google and Amazon. Both companies are still investing heavily in R&D, making profitability-focused public market scrutiny premature from their perspective.
AI infrastructure (chips, inference, data pipelines) and vertical AI applications (legal, medical, coding) are most likely. Foundation model labs with unpredictable capex are less IPO-ready than companies with recurring enterprise revenue. Cerebras (chips), Cohere (enterprise LLMs), and Harvey (legal AI) represent different archetypes of AI IPO readiness.