Skild AI raised $1.4B in January 20261 — ten times its $135M Series B from just months earlier. The jump signals a broader pattern: AI foundation models have changed the calculus for robotics investment.
Mind Robotics closed a $500M Series A in March2, then added a $400M follow-on in May3. Neura Robotics secured up to $1.4B in a Series C in June4. Shihang Intelligent raised $1B at Series A stage that same month5.
Billion-dollar valuations at Series A and B are the telling detail. Early-stage companies typically raise tens of millions, not hundreds. Investors are pricing in the assumption that AI-driven robots will reach commercial viability by 2027-2028.
Apptronik extended its Series A with $520M in February 20266, building on its $415M raise in 2025. Saronic, developing autonomous maritime vessels, closed a $1.75B Series D in March7.
Foundation models trained on diverse, unstructured data let robots generalize across tasks. Earlier robotics systems required expensive per-task programming. That bottleneck has narrowed as model capabilities have scaled — and capital is following the shift.
M&A is accelerating alongside the funding. Meta acquired Assured Robot Intelligence in May 20268. Skild AI acquired Zebra Technologies' Robotics Division in April9, expanding its enterprise deployment footprint shortly after its own mega-round closed.
For the broader AI sector, robotics is now the clearest near-term path from model capabilities to physical-world revenue. The companies holding this capital face the harder test: consistent performance outside controlled environments, at the scale needed to justify these valuations.