Editorial
Agentic AI Benchmarks Now Measure Real-World Task Completion — Not Just Q&A Accuracy
New agentic leaderboards score AI models on whether they actually finish real tasks, recover from errors, and avoid inventing tools — not on multiple-choice accuracy. For institutions weighing AI agents for literature review, data cleaning, or grant administration, that shift changes what reliable enough to deploy means, and exposes governance gaps in policies built around chatbot use rather than autonomous systems.
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