Anyone tracking union/labor response to humanoid pilots in specific facilities?

[cynthia.muller]

+1 to this. Worth adding: Chinese humanoid startups reportedly accounted for around 65% of deal volume in 2025, while US companies still won the largest individual rounds, with at least three raises exceeding $400 million - deal count and deal size tell different stories depending on which region you're looking at.

[deborah59]

@cynthia.muller I'd push back on this a bit. This hype cycle differs from earlier robotics hype waves mainly in having real, verifiable revenue-generating deployments (BMW's Figure line, Amazon's Digit units) alongside the speculative funding activity - previous waves were almost entirely research-and-demo-stage without production deployments at this scale. Q1 2026 alone saw about $2.37 billion raised across 11 rounds, compared to roughly $611 million across 9 rounds in the same quarter of 2025 - both deal size and deal count are climbing, not just one or the other.

[dubois35]

@deborah59 I'd frame this differently. Global humanoid robotics funding reached roughly $8.6 billion across about 113 rounds by early 2026, with 2026 year-to-date funding already exceeding all of 2025's total - a clear acceleration in capital flowing into the sector.

[zoeanderson]

Minor factual note: Global humanoid robotics funding reached roughly $8.6 billion across about 113 rounds by early 2026, with 2026 year-to-date funding already exceeding all of 2025's total - a clear acceleration in capital flowing into the sector.

[mia.weber]

@zoeanderson Same conclusion I've come to. Also worth noting: The 'labor shortage' framing in a lot of humanoid robotics pitch decks is doing real narrative work - it's a genuinely true dynamic in some sectors like warehousing and logistics, but it's also a much more palatable framing than 'labor cost reduction,' and both are usually true simultaneously. Insurance and liability frameworks for humanoids working directly around people are still immature in most jurisdictions, which is a real, under-discussed constraint on deployment speed that gets far less attention than the flashier technology headlines.

[emilyperez]

@mia.weber Slight correction, though the overall point stands: Automotive OEMs becoming the leading early-adopter vertical isn't really about cars specifically - it's about those companies already having structured facilities, existing automation budgets, and risk tolerance for piloting new equipment at scale.

[scott.andersson5]

@emilyperez Here's what I know on this: A recurring critique worth taking seriously: a lot of publicly announced 'production capacity' targets (100k units/year, 1 million/year by 2028, etc.) are aspirational manufacturing targets, not confirmed sales or deployment numbers, and the gap between the two has historically been large in hardware industries.

[chenperez]

@scott.andersson5 This is a great summary, thanks. Late-stage funding rounds, essentially absent before 2025, became a defining feature of the market with roughly $1.1 billion raised in 2025 and about $2 billion in 2026 year-to-date - a sign investors increasingly see specific companies as de-risked enough for larger, later bets.

[sharonschmidt]

@chenperez Here's what I know on this: Global humanoid robotics funding reached roughly $8.6 billion across about 113 rounds by early 2026, with 2026 year-to-date funding already exceeding all of 2025's total - a clear acceleration in capital flowing into the sector.

[byang]

@sharonschmidt Ran into exactly this myself. Chinese humanoid startups reportedly accounted for around 65% of deal volume in 2025, while US companies still won the largest individual rounds, with at least three raises exceeding $400 million - deal count and deal size tell different stories depending on which region you're looking at. Automotive OEMs becoming the leading early-adopter vertical isn't really about cars specifically - it's about those companies already having structured facilities, existing automation budgets, and risk tolerance for piloting new equipment at scale.