The promise of agentic AI, touted by firms like McKinsey, suggests transformative productivity gains in project execution. However, recent findings from the Center for AI Safety and Scale AI reveal a stark reality: AI agents achieve only a 2.5% automation success rate in fulfilling professional tasks across diverse domains. The Remote Labor Index (RLI), which assesses 240 freelance projects, highlights ongoing failures due to low-quality outputs, including corrupted files and inconsistent deliverables. While limited success is found in specific tasks such as content drafting and data visualization, systemic challenges remain—particularly for complex, multi-hour projects. Instead of replacing roles, AI should enhance productivity, with humans verifying and integrating results. Growth is anticipated as AI capabilities improve, but immediate expectations should focus on task augmentation, not total project automation. By addressing these realities, organizations can effectively leverage AI as a valuable tool while steering clear of overhyped promises.
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