Humanoid Robot Future Delusion
The humanoid robot future is built on demonstrations that aren’t real. While Goldman Sachs projects a $38 billion market
The humanoid robot future is built on demonstrations that aren’t real. While Goldman Sachs projects a $38 billion market by 2035 and Morgan Stanley forecasts $5 trillion by 2050, the technology underlying these predictions has a fundamental problem: it doesn’t actually work yet.
Tesla’s Optimus robots served drinks and chatted with guests at the company’s October 2024 “We, Robot” event. Morgan Stanley analyst Adam Jonas later confirmed the robots “relied on tele-ops (human intervention).” Bloomberg reported the bots used AI to walk but needed human assistance to converse. One robot even acknowledged during the event it was getting human help. Tesla’s November 2024 demonstration of an upgraded robot hand, praised for its realistic tendons and 22 degrees of freedom, was also teleoperated according to a Tesla senior staff software engineer.
This pattern repeats across the industry. The impressive demos driving billions in investment show what humanoid robots might do eventually, not what they can do autonomously now. The gap between controlled demonstrations and reliable operation in real environments remains massive.
The Economics Don’t Work
Even optimistic projections reveal broken math. Current humanoid robot manufacturing costs range from $30,000 to $150,000 per unit, down from $50,000 to $250,000 last year. Tesla claims a future price point of $20,000 to $30,000. But cost extends far beyond the initial purchase.
Annual maintenance and upgrades run $1,000 to $10,000 depending on complexity. Staff training for operation and safety adds costs. Integration with existing workflows requires specialized technicians. Downtime for repairs removes the robot from production entirely. A $30,000 humanoid robot represents years of human wages, but a human worker doesn’t require a specialized technician when something breaks.
The comparison gets worse. At current U.S. minimum wage, $30,000 covers roughly two years of labor. In manufacturing, where wages run higher, that timeline shrinks. The robot needs to work flawlessly for years to break even, assuming zero unexpected costs. No company has demonstrated this at scale.
Meanwhile, collaborative robotic arms from Universal Robots cost $35,000 to $50,000, perform specific tasks with proven reliability, and have established maintenance protocols. They work now, not in a projected future. The humanoid robot future asks businesses to pay similar or higher costs for unproven technology with unclear ROI.
The AI Isn’t There
Humanoid robots require AI capabilities that don’t exist. Walking autonomously in structured environments represents the current achievement. Grasping objects reliably remains difficult. Adapting to unstructured environments, handling unexpected situations, and performing diverse tasks without human supervision all require advances in artificial intelligence that haven’t materialized.
Goldman Sachs Research acknowledges significant bottlenecks remain in AI development for manipulation and interaction. Their base case assumes these barriers will eventually be overcome, but viability hasn’t been proven. The humanoid robot future depends on AI breakthroughs arriving on predictable schedules. History suggests otherwise.
Tesla’s Optimus uses “transfer learning,” watching videos of humans performing tasks and replicating movements. Currently limited to first-person perspective videos, this represents progress but not autonomy. The robot learns specific motions for controlled situations, not general problem-solving in dynamic environments.
The AI required for truly autonomous humanoid robots operating in diverse settings looks closer to artificial general intelligence than narrow task-specific models. AGI timelines remain speculative. Building humanoid robots now means constructing hardware before the necessary software exists.
Geopolitical Theater
China leads humanoid robot development with stronger component supply chains, lower production costs, and government funding. The Chinese government created a robot fund for research and development. Publicly listed component makers recruit staff and dedicate resources to humanoid robotics. Western venture capital responds by pouring money into domestic humanoid startups, treating this as a technology race that must be won.
But framing humanoid robotics as geopolitical competition creates perverse incentives. Investment flows toward the most visible, science-fiction-adjacent projects rather than practical automation solutions. National pride drives funding decisions disconnected from business fundamentals. Companies raise hundreds of millions promising future capabilities while proven robotics technologies struggle for attention.
If Western companies are losing a race to build humanoid robots, perhaps the response shouldn’t be running faster in the same direction. Perhaps it’s recognizing the race itself is misguided.
Solving the Wrong Problem
The United States faces 449,000 unfilled manufacturing jobs as of March 2025, with projections suggesting 2.1 million positions could remain vacant by 2030. The logic follows: if we can’t hire enough people, build artificial people to fill the gaps. This misunderstands both the problem and the solution.
Manufacturing labor shortage isn’t about needing more bodies that look human. It’s about specific tasks that need automation. Most factory work doesn’t require human-shaped robots. Assembly lines weren’t designed for humanoid optimization. They were designed for human workers and evolved over decades through incremental improvements.
The humanoid robot future promises complete human replacement when businesses need task augmentation. Decades of automation experience show robots aren’t standalone solutions. They’re components in interconnected production systems requiring integration with workflows, data infrastructure, human supervision, and continuous maintenance. Scaling from one robot to a fleet across production lines and shifts remains an unsolved challenge.
What Actually Works
While venture capital floods humanoid robotics startups, proven automation generates billions in revenue. The most successful robotics deployments aren’t humanoid. They’re specialized machines designed for specific functions.
Collaborative robots work in shared spaces with human operators without safety fencing. They excel at repetitive precision tasks like screwdriving, gluing, and component assembly. Industrial vision systems inspect components for micro-fractures, surface defects, and incorrect labeling at speeds and accuracy levels humans can’t match. Autonomous mobile robots handle material transport, integrating with existing production systems.
These technologies succeed because they solve problems with efficiency and precision, not because they look impressive in demo videos. They won’t generate headlines about humanity’s future. But they’re deployed at scale, delivering returns, and actually addressing manufacturing challenges.
Task automation represents the real opportunity. Machines performing specific tasks rather than entire jobs complement human workers instead of replacing them. This addresses skills gaps while improving working conditions and career progression for operators and engineers.
The Pattern Repeats
Technology hype cycles follow predictable patterns. Massive capital flows toward photogenic solutions adjacent to science fiction. Practical innovations solving real problems get overlooked. Early demonstrations show impressive capabilities in controlled settings. Timelines for commercial deployment keep slipping. Costs remain higher than projected. Capabilities fall short of promises.
The humanoid robot future mirrors previous cycles. Companies announce ambitious production targets they quietly scale back. Musk spoke of producing 5,000 Optimus units in 2025 and scaling to tens of thousands in 2026. Independent reporting suggests Tesla’s actual 2025 production counts in the hundreds, not thousands. The gap between announcement and execution widens.
Goldman Sachs revised their humanoid robot market projection from $6 billion to $38 billion by 2035, a sixfold increase driven primarily by faster-than-expected AI progress. But AI progress in controlled demonstrations doesn’t equal AI progress in real-world deployment. The sophistication required for autonomous operation in diverse environments remains distant.
Innovation Requires Ingenuity
The etymology of “engineer” traces to Latin ingenium, meaning innate talent, clever invention, and ingenuity. Yet the humanoid robot future represents constrained thinking. Massive resources and brilliant minds work to replicate what we already have in abundance (the human form). Meanwhile, genuine innovation gets underfunded.
Why two arms instead of four for assembly work? Two legs instead of wheels in controlled environments? Why human height instead of optimized dimensions for specific tasks? The answers reveal the limitation: we’re not engineering optimal solutions, we’re satisfying aesthetic preferences and science fiction expectations.
Manufacturing doesn’t need robots that fold laundry or maintain yoga poses. It needs systems that perform repetitive tasks with precision, adapt to different production requirements, work safely alongside human operators, and deliver measurable productivity improvements. None of these requirements demand humanoid form.
The Real Future
The humanoid robot future sells well in pitch decks and promotional videos. Investors respond to impressive demonstrations and ambitious market projections. But the businesses thriving in the next decade of automation will likely be those that ignored the hype.
Purpose-built systems optimized for specific tasks will continue outperforming generalist humanoid robots. Collaborative technologies working alongside human operators will deliver better returns. Innovation embracing mechanical forms suited to tasks rather than constrained by human anatomy will create more effective solutions.
The manufacturing labor shortage is real. The solution isn’t waiting for humanoid robots that don’t work yet, cost too much, and solve problems that don’t exist. The solution is deploying proven automation technologies now, focusing on task-specific improvements, and investing in systems that complement human capabilities rather than attempting to replace them.
Sources:
Goldman Sachs Research – Humanoid robot market projections and cost analysis
CNBC – Morgan Stanley $5 trillion forecast
Morgan Stanley Research – Tesla Optimus teleoperation confirmation
Bloomberg – Tesla robot event human assistance reporting
Manufacturing Skills Institute – U.S. manufacturing labor shortage data
The Manufacturing Institute & Deloitte – 2030 manufacturing job gap projections
Interesting Engineering – Tesla Optimus production targets and capabilities analysis
