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ITBench-AA: Frontier Models Score Below 50% on the First Benchmark for Agentic Enterprise IT Tasks — by Artificial Analysis and IBM logo

ITBench-AA: Frontier Models Score Below 50% on the First Benchmark for Agentic Enterprise IT Tasks — by Artificial Analysis and IBM

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Benchmark measuring AI agent performance on enterprise IT tasks.

AI Agents
8.6 (60.458 score)
open-source
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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  • Benchmark results may become outdated as models improve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

Enterprise IT task benchmark
Frontier model evaluation
Agentic workflow assessment
Open-source dataset
Performance scoring
Research collaboration platform

Use Cases

Researchers evaluating AI agent capabilities for IT operationsEnterprises assessing readiness of AI agents for IT tasksAI model developers benchmarking against IT-specific workloadsIT teams understanding current limitations of AI automation

Best For

IT Operations LeadersEnterprise AI EvaluatorsAI ResearchersAgentic Workflow Architects

Frequently Asked Questions

Is ITBench-AA free to use?▾
Yes, ITBench-AA is open-source, making the dataset and benchmark freely available for research and evaluation purposes. There are no licensing costs to access or use the benchmark.
How difficult is it to set up and start using ITBench-AA?▾
Setup is straightforward for technical teams familiar with benchmark evaluation. The open-source nature means you can implement it directly, though interpreting results requires understanding of enterprise IT operations and AI agent capabilities.
Can ITBench-AA integrate with existing AI tools and platforms?▾
ITBench-AA is designed as an evaluation framework for testing AI agents on enterprise IT tasks. It works by benchmarking model performance rather than integrating into operational systems, making it compatible with testing various frontier models and agentic solutions.
What are the main limitations of ITBench-AA?▾
The benchmark shows that frontier models score below 50% on these tasks, indicating significant capability gaps for real-world enterprise IT automation. Results may vary based on how agents are implemented and prompted, and the benchmark covers specific IT scenarios rather than universal enterprise needs.
Who should use ITBench-AA and when?▾
IT leaders, AI researchers, and enterprises evaluating AI agents for IT operations should use ITBench-AA to assess whether frontier models meet their automation needs. It's ideal for understanding current AI agent limitations before deploying agentic workflows in production IT environments.

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Verified Info

Added to directory6/25/2026
CategoryAI Agents
Pricing modelopen-source
Last verifiedJuly 2026

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