White House economic advisor Kevin Hassett said Monday there’s “no sign in the data” that artificial intelligence is displacing workers, even as major tech companies continue announcing AI-related layoffs and Hollywood writers pivot to training AI systems for income.
Hassett’s comments to CNBC came amid a wave of workforce reductions at Amazon, Meta, and Oracle tied to AI initiatives. Block slashed nearly half its workforce in February, citing a shift to smaller teams using AI tools to increase productivity.
Hollywood Writers Turn to AI Training Work
The entertainment industry’s post-strike recovery has pushed many writers into unexpected AI training roles. According to a Wired investigation, unemployed Hollywood writers are now working for companies like Mercor, Outlier, and Turing to assess chatbot responses, annotate video content, and conduct AI safety testing.
One anonymous showrunner described training AI systems to identify furniture patterns, eliminate people from photos, and generate content for safety testing. The writer began AI training work in early 2025 after a producer defaulted on a six-figure payment for a TV show.
“In 2023, Hollywood went on strike, partly to keep the studios from replacing writers and actors with AI,” the writer noted. “When the strike ended after nearly five months, the entertainment-industry carousel never gained back its momentum.”
The shift represents a significant irony: writers who struck to prevent AI replacement are now training the systems they once opposed. Posts in unofficial Writers Guild Facebook groups show unemployed writers sharing AI training opportunities as traditional entertainment work remains scarce.
Enterprise Software Adapts AI Governance
Major enterprise software vendors are implementing new controls around AI connectivity and usage. SAP released a unified API policy clarifying usage controls across its products, emphasizing what the company calls “enterprise-grade stewardship” rather than new restrictions.
According to VentureBeat reporting, SAP’s approach mirrors existing practices across the industry. CRM platforms maintain daily API call limits, productivity suites throttle graph APIs, and hyperscalers publish per-service quotas with infrastructure-layer enforcement.
“These are not controversial measures. They are baseline hygiene for enterprise-grade software platforms operating shared infrastructure at scale,” SAP stated in its policy documentation.
The governance approach reflects broader enterprise concerns about AI integration risks, including liability issues, disclosure requirements, and sector-specific compliance obligations that now affect chief information security officers and corporate boards.
New Job Categories Emerging Despite Displacement
Venture capitalist David George from Andreessen Horowitz argues that AI will create new roles currently “out of our line of sight,” drawing parallels to how computers generated unexpected job categories rather than simply eliminating work.
Forbes analysis points to historical precedent from a 1966 Time magazine essay that predicted computers would replace manual workers, secretaries, and middle managers, leaving only 10% of the population working. Instead, computers created new types of work and made existing workers busier across extended hours.
“Work didn’t disappear because of computers – if anything, it created new kinds of work, or opportunities, and lots of them,” according to the Forbes report. The analysis suggests AI may follow a similar pattern of job transformation rather than wholesale replacement.
Current labor market data supports this view, showing job creation in AI-adjacent fields including prompt engineering, AI safety testing, and machine learning operations. However, the transition period creates uncertainty for workers in affected industries.
Cybersecurity Landscape Reshapes Around AI
The cybersecurity industry has identified AI as a transformative force comparable to major historical events like Stuxnet, WannaCry, and the SolarWinds compromise. Dark Reading’s 20-year retrospective places ChatGPT’s emergence among the top 20 cyber events that “rewrote the playbook for security teams.”
Security leaders now face “attacker automation” challenges as AI tools become available to both defenders and threat actors. The shift has elevated cybersecurity from a technical concern to a “board-level business risk” affecting operational and strategic decisions.
Liability concerns now include disclosure rules, critical infrastructure directives, and sector-specific obligations that raise stakes for security officers. The hyperconnected enterprise environment means security incidents have expanded “blast radius” beyond digital systems to operational and strategic impacts.
What This Means
The AI job market presents a complex picture of simultaneous displacement and creation. While tech companies eliminate traditional roles through AI automation, new categories of AI-related work emerge for those willing to adapt.
The Hollywood writer example illustrates how workers can transition from opposing AI to participating in its development, though often at reduced compensation compared to previous roles. This pattern may repeat across other industries as AI adoption accelerates.
Enterprise software governance around AI suggests companies are prioritizing controlled implementation over unrestricted adoption. This measured approach may slow displacement while allowing organizations to develop internal AI capabilities and retrain existing workers.
The disconnect between Hassett’s optimistic assessment and ongoing tech layoffs highlights the challenge of measuring AI’s workforce impact in real-time. Traditional employment data may lag behind rapid technological changes, making current displacement difficult to quantify accurately.
FAQ
Are AI systems currently causing widespread job losses?
White House data shows no clear evidence of AI-driven displacement, but tech companies continue announcing layoffs tied to AI initiatives. The impact appears concentrated in specific sectors rather than economy-wide.
What types of new AI jobs are emerging?
New roles include AI trainers, prompt engineers, safety testers, and machine learning operations specialists. Many require adapting existing skills rather than completely new training.
How are companies managing AI workforce transitions?
Major enterprises are implementing governance policies and usage controls to manage AI adoption gradually. This approach allows time for worker retraining and controlled integration of AI tools.
