In recent years, AI technology has rapidly transformed enterprise workflows, necessitating reliable, scalable systems. However, verifying model performance remains a challenge. IBM Research introduced ITBench and AssetOpsBench to introduce rigorous benchmarks for evaluating AI agents in IT and asset management. By partnering with Kaggle, IBM aims to create leaderboards that enable thousands of AI developers and engineers to assess models on realistic, multi-step tasks reflective of real-world conditions. These benchmarks will help identify effective models for diagnosing issues in IT infrastructures and predicting asset failures using diverse data types. While Kaggle facilitates collaboration and innovation among AI practitioners, the current benchmarks don’t fully encapsulate complex production environments. IBM’s initiative marks a significant step toward refining enterprise automation, with plans to expand benchmark capabilities and incorporate agentic evaluations to tackle real-world problems effectively. This collaboration strives to bring together academia, startups, and evaluators to enhance enterprise-grade benchmarks and drive impactful solutions.
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