Humanoid robots like Agility Robotics' Digit are finally performing measurable paid work in commercial warehouses, but this breakthrough doesn't mean money is about to become useless. While artificial intelligence is creating genuine abundance in digital services, physical robots remain far too limited and expensive to eliminate scarcity across the economy. Money will likely persist wherever land, energy, human attention, ownership, and access remain scarce.

What's Actually Happening With Warehouse Robots Right Now?

The robotics industry has crossed a significant threshold. Agility Robotics reports that Digit has moved more than 100,000 totes in a commercial warehouse deployment, while Figure AI's humanoid completed more than 90,000 parts during 1,250 hours at BMW and contributed to 30,000 vehicles. These aren't stage demonstrations anymore; they're narrow but genuine paid work inside real operations. However, the scale gap remains enormous. Hundreds of units and planned factories don't yet prove that billions of reliable general-purpose robots can be produced economically.

The timing of questions about money becoming obsolete makes sense now because two changes are happening simultaneously. Generative AI has made useful digital intelligence extremely cheap, while robots have started doing measurable paid work in factories and warehouses. Yet treating these early achievements as proof that every form of scarcity is about to vanish would be a huge leap.

Why Does Cheap AI Still Require Expensive Infrastructure?

Digital abundance is real but narrow. A cheap AI answer still depends on expensive chips, data centers, electricity, cooling, fiber networks, and financing. The visible service can approach zero cost while the underlying system remains highly capital-intensive. Five large technology companies spent more than $400 billion on capital expenditure in 2025, with another large jump expected, according to the International Energy Agency.

AI productivity also looks far stronger at the task level than at the company or economy level. Controlled studies show large gains in coding, support, and marketing, while most executives still report little measurable effect on total employment or firm-wide productivity. This suggests that even as robots and AI become more capable, their economic impact will remain uneven across different sectors and skill levels.

How to Understand the Four Possible Futures for Money

• AI Becomes Nearly Free: Everyone gets cheap digital help, but money doesn't disappear because scarcity persists in physical goods and services.
• Work Becomes Optional: People receive income without needing a job, but money still matters less for survival rather than becoming truly useless.
• Basic Living Is Guaranteed: Housing, healthcare, food, or transport are provided publicly, making money matter less for survival but not eliminating it entirely.
• Scarcity Largely Disappears: Almost every desired good is available to everyone, which is the only scenario where money may lose most of its role.

The most plausible outcome is a two-layer economy. A high-quality baseline of intelligence, education, healthcare, transport, and manufactured goods becomes cheap or publicly guaranteed, while money continues to allocate scarce property, premium services, rare experiences, and control over productive assets.

What Remains Expensive Even as Robots Advance?

Automation will push prices down most sharply for digital and standardized products. Housing, food, healthcare, and infrastructure will remain expensive because labor is only one part of their cost. Prime locations, grid capacity, trusted human attention, rare experiences, and social status remain limited even when ordinary goods become plentiful. Ownership may be the decisive issue; machine output initially belongs to the companies, investors, and governments that own the models, data centers, and robot fleets, so technical abundance does not automatically become shared abundance.

The transition could be rougher than the destination. Wages and job security can weaken faster than tax systems, public services, and income guarantees can adapt, making money more urgent for some households before automation makes life cheaper. This timing mismatch means that even as robots like Digit prove their value in warehouses, the economic disruption they cause may arrive before the benefits are widely distributed.

The evidence from Agility Robotics and other humanoid robot makers shows that physical AI is advancing rapidly, but the leap from hundreds of deployed units to billions of economically viable robots remains enormous. Until that gap closes, and until ownership of robot-generated wealth becomes more distributed, money will remain essential for navigating a world where scarcity persists in the things that matter most to human life.