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TechCrunch Debuts Rating System to Measure AI Labs’ Commercial Ambitions from Level 1 (Pure Research) to Level 5 (Daily Revenue)
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Human and workplace AI plans are at level 3, but there are no tangible products. World Labs advances to Level 4 with spatial AI model shipments
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Thinking Machines Lab loses half of its founding executives in a matter of weeks, raising questions about Level 4 roadmap
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Safe Superintelligence’s Ilya Sutskever raised $3 billion for pure research, but hinted at a potential commercial pivot if timelines change
The AI industry’s latest identity crisis is only just beginning to take shape. As foundational model startups raise billions of dollars without a clear revenue strategy, TechCrunch introduced a five-point scale to measure commercial ambition, not success. The timing couldn’t be more acute. With Humans& raising $480 million while remaining vague about its product, Thinking Machines Lab bleeding into management, and Safe Superintelligence turning down Meta’s takeover bid, the question isn’t who’s making money. It’s about who is making the effort.
The AI gold rush poses a strange problem. It’s becoming impossible to tell which labs actually want to make money. OpenAI, Google, and Meta veterans are building startups with multibillion-dollar war chests and foundational models with zero revenue pressure. Investors are keen to fund anything related to AI, so business plans have become optional.
TechCrunch just proposed a solution: a five-stage commercialization scale that measures ambition rather than actual profits. Level 5 companies like OpenAI and Anthropic mint millions of dollars every day. Level 1 Lab treats “true wealth” as self-actualization. In the middle tier, where most emerging startups enter, the industry’s existential confusion over whether AI research should prioritize science or shareholders is evident.
This scale comes as several high-profile labs navigate this tension in real time. Humans&, which raised $480 million this week, received a Level 3 rating for having “many promising product ideas,” without going into details. The startup has floated vague plans for an AI workplace tool to replace Slack and Google Docs, but observers remain stumped about the specifics of its implementation.
“It’s my job to know what this means, but I’m still pretty confused,” TechCrunch’s Russell Brandom wrote, capturing the industry-wide bewilderment.
Thinking Machines Lab’s trajectory tells an even more troubling story. The $2 billion seed round, led by former OpenAI CTO Mira Murati, proposed Level 4 operations with a detailed commercialization plan. Then within two weeks, citing concerns about the company’s direction. In just one year, nearly half of the founding team left.
