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Frontier AI era’s ‘paradox of automation’ persists as progress remains slow

As AI models advance, companies are showing growing interest in autonomous AI agents that can carry out tasks without people. Yet complaints persist that AI-driven automation is still slow, even in Silicon Valley, highlighting a gap between expectations and on-the-ground experience. Some argue today’s large language models are built to assist humans rather than automate work, and that pursuing both goals can produce uneven performance. Surveys cited in reports show time saved by AI is often spent fixing or checking AI outputs.