Unemployed Hollywood writers are secretly training AI systems while tech companies announce thousands of layoffs, contradicting government claims that artificial intelligence isn’t displacing workers. According to a Wired investigation, entertainment industry professionals are working for AI training platforms like Mercor, Outlier, and Turing to survive after the 2023 strikes devastated employment.
The disconnect comes as National Economic Council Director Kevin Hassett told CNBC there’s “no sign in the data” that AI is costing jobs, while Block slashed its workforce by nearly half in February, citing a pivot to smaller AI-powered teams.
Writers Become AI Trainers After Industry Collapse
Hollywood writers who once created prime-time television are now annotating videos, generating content, and red-teaming AI systems for companies with anonymous platform names. One showrunner, identified only as “ri611” on training platforms, describes assessing chatbot tone, identifying furniture patterns, and time-stamping video content.
According to the writer, the shift began after a producer defaulted on a six-figure payment for creating a TV show in early 2025. “AI training wasn’t on my radar until a comment in an unofficial Writers Guild of America Facebook group caught my attention,” the writer explained.
The work includes generating anime content, testing safety precautions, and probing AI weaknesses. Writers report earning income through multiple platforms simultaneously, often using different identification codes depending on the client.
Tech Layoffs Accelerate Despite Official Denials
Major tech companies continue announcing AI-related workforce reductions while government officials deny job displacement. Amazon, Meta, and Oracle have announced cuts specifically tied to AI automation initiatives, CNBC reported.
Block’s February workforce reduction of nearly 50% represents the most dramatic example, with executives citing AI’s ability to enable smaller teams to accomplish more work. The company’s pivot reflects broader industry trends toward AI-augmented operations.
Hassett’s comments to CNBC emphasized data showing no measurable AI job displacement, but the timing coincides with accelerating automation announcements across multiple sectors.
Enterprise AI Governance Creates New Workforce Dynamics
Enterprise software companies are implementing what Forbes describes as “agentic enterprise” models that move beyond simple bot deployment. Sanjoy Sarkar, SVP at First Citizens Bank, argues that automation maturity requires intelligent orchestration rather than scale alone.
“Scale alone does not equal maturity,” Sarkar wrote in Forbes. “What started as innovation gradually turned into automation sprawl.” Organizations are consolidating multiple platforms performing similar functions while implementing unified governance models.
SAP’s recent API policy changes reflect this trend toward enterprise-grade AI governance. The company clarified that its unified controls represent existing restrictions rather than new limitations, emphasizing stewardship over restriction.
Skills Gap Emerges as Traditional Roles Evolve
The entertainment industry’s transformation illustrates broader workforce adaptation patterns. Writers who previously created television content now perform AI training tasks requiring different skill sets, from data annotation to safety testing.
Dark Reading’s analysis of cybersecurity evolution over two decades shows similar workforce transitions. The publication notes that “cyber has evolved into a board-level business risk” with implications extending beyond technical roles.
Traditional creative professionals are developing technical capabilities while maintaining their core expertise. The Hollywood writer describes generating content for AI systems while continuing to create television shows, though noting decreased opportunities in traditional entertainment.
Automation Sprawl Drives Workforce Restructuring
Many organizations face “automation sprawl” as different departments adopt AI tools independently, creating governance challenges. Forbes reports that credential management and monitoring often lack centralization as automation scales.
First Citizens Bank’s Sarkar identifies patterns where “scripts and workflows proliferated” while “visibility became fragmented.” This complexity drives workforce restructuring as companies consolidate overlapping functions.
Block’s dramatic workforce reduction exemplifies this consolidation trend, with AI enabling smaller teams to handle previously distributed responsibilities. Similar patterns appear across enterprise software, where unified platforms replace specialized roles.
What This Means
The gap between official job displacement denials and actual workforce changes suggests AI’s employment impact is more nuanced than aggregate data reveals. While headline unemployment numbers may not show dramatic AI displacement, specific sectors like entertainment and enterprise software are experiencing significant restructuring.
Hollywood writers transitioning to AI training roles represent a broader pattern of skill adaptation rather than simple job loss. These workers maintain employment by developing new capabilities while leveraging existing expertise in content creation and evaluation.
Enterprise automation evolution indicates that AI’s workforce impact involves role transformation more than elimination. Organizations are consolidating functions and requiring workers to manage more sophisticated systems, but human oversight remains essential for governance and quality control.
FAQ
Are AI systems actually replacing human workers right now?
Government data shows no aggregate job displacement, but specific industries like entertainment and enterprise software are experiencing significant workforce restructuring. Companies like Block have reduced headcount by nearly 50% while citing AI’s ability to enable smaller teams to accomplish more work.
What types of jobs are Hollywood writers doing in AI training?
Writers are performing content annotation, video time-stamping, chatbot tone assessment, safety testing, and red-team exercises for platforms like Mercor, Outlier, and Turing. They work under anonymous identifiers and often juggle multiple platforms simultaneously.
How are companies managing automation sprawl in their workforce planning?
Organizations are moving toward “agentic enterprise” models that emphasize intelligent orchestration over simple bot deployment. This involves consolidating overlapping automation functions, implementing unified governance, and requiring workers to manage more sophisticated integrated systems rather than specialized tools.
