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Why It's Time to Stop Calling Trillion-Dollar AI Corporations 'Labs'

September 5, 2026

Based on reporting from The Atlantic → — simplified & explained by VAIIYA.

Why It's Time to Stop Calling Trillion-Dollar AI Corporations 'Labs'

Over the past few years, a specific piece of vocabulary has quietly reshaped how the public views the artificial intelligence sector: the word "lab." Industry executives, commentators, and major news outlets routinely describe companies like OpenAI and Anthropic not as commercial entities, but as scientific research laboratories.

This terminology misrepresents the current reality of the AI industry. While early iterations of OpenAI and Anthropic functioned primarily as research organizations, both have swiftly transformed into commercial powerhouses. Valued near $1 trillion each and generating billions in quarterly revenue, these firms operate like any major corporate tech player.

The Public Relations Halo Effect

Adopting academic nomenclature provides AI firms with a distinct public relations advantage. The term "lab" evokes images of objective researchers working purely in the interest of science and human knowledge.

This branding stands in stark contrast to public attitudes toward corporate tech leadership. A 2026 Pew Research Center survey revealed that over 75 percent of Americans trust scientists to act in the public interest, whereas a majority distrust business executives. By leaning into their scientific heritage, AI corporations can signal altruism and downplay commercial motives during a period of mounting public concern over job displacement, privacy risks, and massive spending.

A Departure from Scientific Rigor

Despite framing their work around safety and scientific discovery, AI companies rarely adhere to standard academic protocols.

An analysis of 100 recent research posts featured on the official sites of OpenAI and Anthropic found that the vast majority were not peer-reviewed papers accepted by independent scholarly journals or academic conferences. Instead, much of this output functions as self-published material that adopts the visual aesthetics of scientific literature—such as graphs and citations—without undergoing third-party validation.

This approach resembles historical policy advocacy groups that produced internal reports designed to shape public perception without submitting their claims to peer review. While AI firms occasionally publish self-critical studies—such as Anthropic's research on model sycophancy and disempowerment—they ultimately retain total control over how findings are framed and released.

Redefining Accountability

If major AI developers want to maintain the mantle of scientific institutions, they should adhere to established scientific standards. That would mean open-sourcing code, preregistering studies, and subjecting their research to independent peer review.

Without those commitments, continuing to call these multi-billion-dollar entities "labs" serves only to obscure their true nature as profit-driven corporations reshaping global workplaces and infrastructure.