ITBench-AA: Frontier Models Score Below 50% on the First Benchmark for Agentic Enterprise IT Tasks — by Artificial Analysis and IBM
Benchmark measuring AI agent performance on enterprise IT tasks.
Overview
ITBench-AA is a benchmark dataset created by Artificial Analysis and IBM Research to evaluate how well frontier AI models handle agentic enterprise IT workflows. It reveals that current models score below 50% on realistic IT operations tasks like system administration and troubleshooting. Designed for researchers and enterprises assessing AI agent readiness for production IT environments.
Pros
- Evaluates real-world enterprise IT tasks, not abstract benchmarks
- Open-source dataset enables community research and reproducibility
- Reveals performance gaps in frontier models below 50%
- Covers diverse IT operations scenarios and complexity levels
✕ Cons
- Limited to IT domain; doesn't assess other enterprise workflows
- Below-50% scores may discourage practical AI agent deployment
- Benchmark results may become outdated as models improve
Key Features
Use Cases
Best For
Frequently Asked Questions
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Ratings & Reviews
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