Uploaded March 2025 | Updated September 2026, 1 week ago
The AI explosion has been massive, but so far, adoption of these tools has been rather limited in the world of work. That's partially because it’s been difficult to compare how efficient different AI systems are for reliably solving business problems, because standardized tests to measure their abilities haven't really existed. That inspired IBM Research's Director of AI for IT Automation Daby Sow and his team to create ITBench. It’s a series of benchmarks to test how good AI agents really are at solving actual tasks that businesses carry out every day. Sow runs us through the three benchmarks available today, focused on site reliability engineering, cost management, and compliance assessments. You can also check out these benchmarks on GitHub now: github.com/IBM/itbench-sample-scenarios
#AI #aiagents #itbench
The AI explosion has been massive, but so far, adoption of these tools has been rather limited in the world of work. That's partially because it’s been difficult to compare how efficient different AI systems are for reliably solving business problems, because standardized tests to measure their abilities haven't really existed. That inspired IBM Research's Director of AI for IT Automation Daby Sow and his team to create ITBench. It’s a series of benchmarks to test how good AI agents really are at solving actual tasks that businesses carry out every day. Sow runs us through the three benchmarks available today, focused on site reliability engineering, cost management, and compliance assessments. You can also check out these benchmarks on GitHub now: github.com/IBM/itbench-sample-scenarios
#AI #aiagents #itbench
