Brendan Foody, the chief executive officer and cofounder of Mercor, recently disclosed that his rapidly expanding company is disbursing more than $1.5 million every single day to a vast network of independent contractors whose primary responsibility is to train artificial intelligence systems. These human participants—scattered across a variety of disciplines and geographic regions—serve as an indispensable part of the company’s mission to refine and advance machine learning models through real-world human insight and judgment.
Mercor operates as a recruitment and coordination platform that assembles specialized teams of professionals to guide AI models toward more accurate reasoning and nuanced understanding. Among its notable clients are leading AI powerhouses such as OpenAI and Anthropic, both of which rely heavily on the expertise of human trainers to ensure that their algorithms can interpret language, context, and human intent with increasing sophistication. On Monday, the company announced the successful completion of a major funding deal based on an astonishing $10 billion valuation—a figure that underscores the tremendous investor confidence in the human-AI training sector.
In an interview on the TBPN show, following the public revelation of Mercor’s valuation, Foody enthusiastically characterized the company’s trajectory as nothing short of explosive, saying that its growth has been “like crazy.” This exponential expansion places Mercor among a select group of new-generation startups recruited by major technology firms to provide human support in refining their artificial intelligence products. Such companies act as bridges between human cognition and synthetic intelligence, ensuring that each model learns not only computational accuracy but also cultural, ethical, and contextual nuance.
Mercor revealed in a company LinkedIn post that it currently collaborates with more than 30,000 active contractors around the world—a workforce representing a remarkably diverse cross section of expertise. According to Foody, substantial investment and participation are pouring in from highly skilled sectors such as software engineering, financial analysis, law, and medical research. These professionals are now applying their domain-specific understanding to the sophisticated process of shaping artificial reasoning systems.
Elaborating further on the company’s new funding round in a detailed blog post, Foody introduced a compelling framework for thinking about this phenomenon: he described human-guided machine training as a “new category of work.” Over the next ten years, he predicted, millions of individuals will devote themselves to instructing machines in precisely those areas where humans still uniquely excel—discernment, empathy, aesthetic sense, and contextual judgment. Rather than spending their careers performing rote, repetitive tasks, these individuals will instead teach intelligent agents to replicate such processes autonomously, enabling machines to perform them millions of times over with consistent precision and speed.
In the same TBPN appearance, Foody hinted that an initial public offering for Mercor could be “potentially on the horizon,” though he offered no fixed timeline or specific date. Business Insider reached out to Foody for additional commentary on these developments, but as of the article’s publication, he had not responded.
This boom in human participation within AI training represents a defining trend in the technology industry’s latest economic surge—a modern-day “gold rush” centered on the human facilitation of AI chatbot development. Across the sector, individuals are being remunerated at extraordinary rates—sometimes earning as much as $100 per hour—to help shape conversational AI. These roles range from meme specialists enhancing xAI’s chatbot Grok with cultural fluency and humor comprehension to language tutors and domain experts refining systems’ understanding of fields such as Japanese linguistics or corporate finance.
Startups connecting these contractors to major AI research labs are experiencing skyrocketing valuations and producing an entirely new class of exceptionally young, self-made billionaires. Forbes, for example, reports that Edwin Chen, the 37-year-old CEO of Surge AI, now holds an estimated net worth of $18 billion. Similarly, Scale AI’s cofounders, Alexandr Wang, age 28, and Lucy Guo, age 30, possess fortunes of approximately $3.2 billion and $1.4 billion, respectively—testament to the industry’s extraordinary financial momentum.
In a comprehensive investigation released last month, Business Insider interviewed more than 60 data labelers employed around the world, revealing that many independent contractors are earning thousands of dollars per month through AI training projects. However, the report also surfaced the complex realities behind the work: while potentially lucrative, the experience can be mentally taxing, monotonous, unpredictable, and, in some cases, psychologically troubling depending on the nature of the data being processed.
Business Insider concluded the report with a call for transparency and secure communication, encouraging individuals with insider knowledge of the AI training ecosystem to share credible information safely through encrypted channels or personal devices using non-work internet connections. By shedding light on this rapidly evolving field, these disclosures help the public understand how human expertise continues to serve as the irreplaceable foundation of contemporary artificial intelligence progress.
Sourse: https://www.businessinsider.com/mercor-pays-million-per-day-human-contractors-training-ai-ceo-2025-10
