Altman Warns World Unprepared for AI Surge Amid AI Washing and $600B Compute Push

OpenAI CEO Sam Altman has sounded an urgent alarm on the pace of artificial intelligence advancement, declaring that "the world is not prepared" for the societal, economic, and ethical disruptions on the horizon. Speaking at the Express Adda event in India, Altman stated that artificial general intelligence (AGI) is "pretty close" and superintelligence is "not that far off," underscoring that OpenAI is now leveraging its own AI models to accelerate internal research — a self-reinforcing loop that could exponentially outpace human oversight.

According to The Decoder, Altman emphasized that the company’s proprietary AI systems are already contributing to model training, architecture design, and even identifying research bottlenecks — a form of AI-driven autogenesis that raises profound questions about control, transparency, and safety. "We’re not just building tools; we’re building entities that build themselves," Altman reportedly said, highlighting the accelerating feedback cycle between human engineers and AI systems.

Meanwhile, Altman has also turned his attention to the corporate landscape, where he accused numerous firms of engaging in "AI washing" — the practice of attributing unrelated layoffs or operational failures to artificial intelligence to justify cost-cutting. In remarks reported by Tom’s Hardware and Fortune, Altman called out this trend as misleading and dangerous. "Companies are using AI as a scapegoat," he said. "But the real disruption is coming, and we need to be honest about it. We can’t pretend the job displacement isn’t real just because some firms are misrepresenting the cause."

Altman’s warnings come amid unprecedented financial commitments from OpenAI. As CNBC revealed, the company has reset its long-term spending expectations, targeting approximately $600 billion in compute infrastructure investment by 2030. This figure dwarfs the annual budgets of entire nations and reflects the astronomical scale of energy, hardware, and data center resources required to sustain the current trajectory of AI development. The investment is not merely for training larger models, but for building the physical and computational ecosystems necessary to support continuous, real-time AI self-improvement.

The convergence of these three developments — self-accelerating AI research, corporate misrepresentation of AI’s role in job losses, and an unprecedented capital surge — paints a picture of a technological inflection point. Experts warn that regulatory frameworks, labor policies, and public understanding have not kept pace. The European Union’s AI Act and U.S. executive orders on AI safety are seen as necessary but insufficient. "We’re racing toward a future where AI systems make decisions that affect millions, yet we haven’t even agreed on how to define autonomy," said Dr. Elena Rodriguez, a technology ethicist at Stanford University.

OpenAI’s internal use of AI to improve its own models represents a paradigm shift: instead of humans guiding AI development step-by-step, AI is now co-piloting its evolution. This raises ethical red flags about alignment, accountability, and the potential for emergent behaviors beyond human comprehension. Altman acknowledged these concerns but argued that slowing progress is not the answer. "We need to build guardrails while we build the engine," he said.

As governments and industries scramble to respond, the challenge is no longer theoretical. The $600 billion compute target means OpenAI will require more energy than some countries, prompting renewed scrutiny from climate scientists. Meanwhile, workers displaced by automation — whether due to AI or corporate pretext — face an uncertain future without adequate retraining or social safety nets.

Altman’s message is clear: the age of AI is not coming. It’s here. And the world, he insists, is still asleep at the wheel.