The Humanoid Hypothesis: A New Frontier in Productivity

00:22, Chris Thonis

Hi everybody. Welcome back to William Blair Thinking Presents. Today is June 9th, 2026. I'm joined by Ross Sparenblek. He’s the research analyst in William Blair's industrials group where he covers diversified industrials with a focus on robotics and automation. Ross, thanks for joining us.

00:40, Ross Sparenblek

Hey, Chris. Thanks for having me. Happy to be here.

00:42, Chris T

So today we're discussing your team's latest industry report. It's called Race to Infinite Labor: The Humanoid Hypothesis. To start, can you give us a high-level overview of what the report is focused on, and then why the topic is relevant right now?

00:59, Ross S

Yeah. Yeah, certainly. You know, our report focuses on one of the next major inflection points in the robotics market, which is the shift from static automation, which handles, you know, narrow, repetitive tasks, to robots that can handle broad, physical work that defines, you know, most of the global economy. And, if you go back the last several decades, we've seen incremental improvements with each new wave of robots.

By and large, you know, physical labor has remained untouched. AI is transforming this on the digital side, everything from coding to customer service, and even creative roles. But, we haven't really bridged that gap to real world physical execution.

But this is what humanoids are, you know, set to provide, and, specifically, close that gap between planning and doing.

And we see that the reason this matters right now is that when you think across the core economic drivers, productivity seems to have the highest torque to sustain that economic growth.

01:57, Chris T

You know, you walk through a number of structural forces in the report. When you step back, what are the biggest shifts you're seeing that make this moment feel different or, you know, more urgent than prior waves of automation?

02:09, Ross S

Yeah, certainly. There are several structural headwinds that are working not only against the West, but many developed economies today. Aging populations are top of mind and the most obvious. The U.S. is expected to see, something around 2030, children outnumbered by adults for the first time. And also, given the limited traction with China's two child policy, the country is on course to undergo the largest absolute population decline over the next several decades.

But at the same time, governments and corporations are also looking to reshore and dual source the global supply chain, following the aftershocks of Covid and the supply chain bottlenecks, which just further compounds the need for more localized labor. And then you consider the burden of rising national debts, growing energy scarcity from the ramping data center build that power AI, it all points back to productivity, where we see humanoids as the tool to drive the greatest output at scale.

03:05, Chris T

All right. So, at a basic level, automation isn’t new. So, what is it about humanoid robotics that changes the equation in a more meaningful way?

03:16, Ross S

Yeah. Well, traditional automation has been incredibly successful doing what it's designed for. But, it's fundamentally limited. You know, it's specific task and rigid.

You have to redesign entire workflows and facilities around these machines. This is expensive. It's time consuming. And you frequently run into issues with the introduction of edge cases.

Humanoids are more aspirational by nature. You know, they're built from the ground up to operate in human-centric environments with the same factories, warehouses, and job sites that we already use.

This task agnostic approach, which seeks to allow an operator to move a piece of equipment across industries and job functions without a complete overhaul of the environment. From a high level, you know, this flexibility is what makes them so compelling and a revamp of traditional robotic thinking, as it looks to address one of the top concerns that we hear when speaking with customers that are seeking automated solutions.

04:05, Chris T

All right. Cool. So, how much has the timeline to real world development shifted in recent years?

04:12, Ross S

Yeah, that's one of the primary reasons we wanted to write this report. We've been following this market for many years. And if you go back to even early 2024, many in the industry, and I would go as far as to say even the consensus, view humanoids as more of a novelty, decades away from mass commercialization was the message we repeatedly heard.

Although, if you fast forward to just a year later, our discussions have made a complete 180. Advancements in AI were noted as having rapidly condensed the timeline, and I would put the consensus today at somewhere around, you know, five years. That being said, there's still a lot of uncertainties surrounding some of the technical challenges, structural issues that come with scaling, but the direction of momentum have clearly shifted.

And China does look to have taken the early pole position.

04:58, Chris T

You also frame this as a, you know, something bigger than a traditional technology cycle. So how would you say listeners should think about the broader strategic or geopolitical context shaping this?

05:11, Ross S

Yeah, I mean, if you look at China's policy announcements over the last six months, it's calling for nothing short of a full mobilization towards AI, and thereby physical intelligence. With all the added benefits of its top-down coordination, including easier access to capital, which has certainly been robust out of the gate.

But this goes beyond just economic resilience in the means of offsetting demographic headwinds, when you consider the thought of robots, manufacturing robots, the geopolitical ramifications are pretty clear. And this really underpins our thesis, you know, the race to infinite labor, as you're seeing the growing alignment between the private sector investments and public policy out of Washington that looks to de-risk the investment case in our eyes, in the form of this government backstop.

05:53, Chris T

All right. So, when you look under the surface, you know, what are the biggest friction points today? What are the challenges that still need to be solved, would you say, before this can scale in a meaningful way, especially, you know, from a hardware and data perspective?

06:06, Ross S

Yeah, as all things automation, the more you dig, the more you find. But just from a high level, from a hardware perspective, we view as twofold, really durability and availability. You know, on the durability front, the industry is working through challenges within the motion systems. You have wear from thermal waste that's compounding on the components, that are already subjected to repetitive, high duty cycles. And we've seen several announcements around supplier OEM partnerships to help, you know, develop proprietary solutions with the goal at a more economic price point.

And then on availability, you know, these critical components are difficult to scale in the West, as most of the low-cost manufacturing base sits within China. And this is also in addition to the rare earths that are required for the permanent magnets. Hundreds of these go into each humanoid.

So, when you really take a step back and start pulling these numbers together to, kind of, map out the manufacturing path here from, say, tens of thousands of units, which is the near-term targets for most these OEMs, to the millions that some of the major OEMs are speaking to, the uplift in the supply chain, it's almost daunting from today's perspective, and it's just going to take time and more investment.

And then just segway into the data aspect, real world training data is still limited, and it's expensive to collect. This does looks like a classic chicken and egg problem. You need the data so the robots can effectively operate, but then you need to deploy them to collect the data. And solving for that loop is one of the key gating items over the next couple of years.

But we've spoken with several OEMs, and in our discussions, they indicate that there's workarounds being deployed that should help them, kind of, get out of the gate, and then quickly scale that S-curve as more robots are deployed.

07:48, Chris T

So, when people hear about humanoid robotics, you know, the opportunity can sound abstract, not real. How do you anchor that in practical terms? Like, where does this show up first?

08:00, Ross S

Yeah, we say either the automotive market or just the physical labor market is probably the best way to anchor the sheer size and TAM here, because we're talking about hundreds of millions of repetitive, physical intensive roles that can eventually be performed by these humanoids over time. Although early adoption will most likely show up in three key areas around logistics, manufacturing, and maintenance. Places where the tasks at hand are well-defined and are more suitable for the day's capabilities.

But over time, the technology will improve and regulation will catch up, and that adoption should expand into more industries and varied roles, with the thought being that eventually you're going to have a broad and diverse landscape of different types of humanoid models, different shapes and sizes to handle niche applications.

08:45, Chris T

All right. So, you know, as we wrap up, what's the most common misconception you encountered while working on this report? And was there anything you found yourself really wanting to clarify?

08:57, Ross S

Yeah, yeah. Working on this was a good journey. And it really, kind of, changed our perspective. I mean, it's clear that something is happening, and we really want to get across that, you know, humanoids are not just simply the next incremental improvement in automation. In reality, they do represent, kind of, a structural shift in productivity.

These engineers are no longer seeking to address just individual problems and static point solutions, but they're working towards a general purpose platform that really offers this promise of addressing labor shortages at a macro scale.

And, at the same time, though, we want to be more measured in our expectations. As, you know, the advances in AI have begun to accelerate. But there's still numerous technological and real-world constraints that investors should consider.

And, we view this as, you know, more of a long-term transition rather than a sudden, disruptive technology that's going to reshape the world.

09:49, Chris T

Alright. Well, Ross, that's all the time we have today. Really thankful that you joined us. Yeah, this report was very interesting. It's called Race to Infinite Labor: The Humanoid Hypothesis. For those interested in reading the full report, you can request a copy by visiting WilliamBlair.com/contact-us. Thank you everybody for listening.

10:09, Ross S

Thank you, Chris.