Where 2025's agentic AI hype fell short (bytesauna.com)

By 2025, the tech community anticipated the rise of "AI agents"—autonomous systems capable of complex task execution with minimal human oversight. However, this forecast proved overly optimistic, as a recent MIT report revealed that 95% of generative AI pilots in companies have failed. Even more concerning, a METR study indicated that developers using AI tools took 19% longer to complete tasks. This disconnect suggests a fundamental misunderstanding of AI's capabilities and limitations, challenging existing beliefs about its potential. The original definition of artificial intelligence, rooted in a human-like behavior model, illustrates the current gap between expectation and reality. While large language models (LLMs) like ChatGPT can convincingly simulate human-like conversation, they do not exhibit genuine understanding or reasoning akin to human cognition. The implications of this mismatch highlight a critical need for the AI/ML community to reassess its assumptions and approach these technologies with an open mind, emphasizing the importance of realistic expectations in harnessing AI's true capabilities.