Scale AI and CAIS’s Remote Labor Index exposes a stark gap between agentic AI marketing and real-world performance: top systems completed under 3% of Upwork tasks by value ($1,810 of $143,991). Agents excel in narrow reasoning tasks but fail at toolchain use, multi-step workflows, and error propagation, leading to brittle automation and repeated mistakes. For enterprises this means agentic systems currently function as assistive tools rather than autonomous labor—requiring human oversight, validation, and safety overhead that can negate cost benefits. Legal and accountability frameworks lag, shifting liability onto users and owners and creating regulatory risk. Organizations should treat current agents cautiously, adopt rigorous benchmarks like the Remote Labor Index, and invest in governance, testing, and phased deployment before large-scale automation.