AI Is a Capital Extraction Scheme Targeting Ordina
Let’s be honest about what’s actually happening.
AI companies are hemorrhaging money. OpenAI, Anthropic, Google DeepMind — none of them have a viable business model. They’re burning through billions in investor cash with no clear path to profitability. And what’s their solution? Quietly downgrading their models to cut costs, while charging us the same subscription fees. You’re not imagining it — the quality is getting worse.
Meanwhile, enterprise adoption is a fantasy. Real businesses aren’t deploying AI at scale because current agents are unreliable. One mistake in a critical workflow and who’s liable? Nobody wants that risk. The “AI revolution” in actual workplaces is largely smoke and mirrors.
So where does that leave us, the ordinary people?
Stuck with the bill.
Corporations are using the AI narrative as cover to justify mass layoffs, freeze hiring, and demand more productivity from fewer workers — all while the technology isn’t even mature enough to replace us. Oxford Economics confirmed it: most “AI layoffs” are just regular cost-cutting dressed up in a better story for investors.
Your boss expects 2x output because “you have AI now.” Your job security is being threatened by a technology that still can’t reliably answer basic questions. Entry-level positions are disappearing — not because AI replaced them, but because the hype gave executives an excuse.
Silicon Valley is winning. The rest of us are absorbing the anxiety, the instability, and the toxic work environments that come with it.
The technology might matter someday. But right now? It’s a wealth transfer mechanism. From our labor, our job security, and our peace of mind — straight to venture capital funds and tech billionaires.
At least be honest about what game is being played.
Having closely followed AI and its integration into workplaces, I can attest that the promises of AI revolutionizing businesses are greatly overstated. From my experience and conversations with professionals in various industries, many remain skeptical about AI’s reliability in crucial workflows. The fear of errors causing financial or operational damage naturally limits large-scale adoption. Furthermore, the financial dynamics within AI companies reinforce this caution. The billions of venture capital dollars invested are sustaining companies without a crystal-clear route to profits, often leading to cost-cutting measures like downgrading AI models without reducing subscription fees. This subtle degradation in quality isn’t always obvious immediately but gradually erodes user trust. On the worker side, the narrative around AI leading to job displacement too often masks traditional corporate strategies of cost-cutting. In reality, layoffs and hiring freezes are frequently rebranded as AI-driven workforce reductions. However, the current AI tools are not yet capable of replacing human workers in complex or nuanced roles, especially entry-level jobs that require adaptability and interpersonal skills. This situation creates a paradox where employees are expected to double their productivity thanks to AI yet receive little support and face heightened job insecurity. It’s evident that the wealth generated from these AI advances disproportionately benefits venture capitalists and tech elites, while many employees grapple with increased pressure and anxiety. Personally, I believe transparency is crucial. Recognizing the ongoing challenges and separating hype from reality can help workers and businesses prepare more effectively without falling prey to inflated expectations. Until AI technologies become truly reliable and integrated responsibly, it remains a tool leveraged more for capital extraction than for widespread productivity or job creation. This understanding empowers us to navigate the evolving AI landscape with a more critical and informed perspective.
