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CORPGEN advances AI agents for real work

Today's AI agents fail at real work. Microsoft Research just showed why—and how to fix it.

Reporting by Microsoft Research 1 min brief
Illustration of independent geometric mechanisms passing paper tasks along branching amber tracks.
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The KeyNews take

Why it matters

Microsoft Research identifies a fundamental gap in how AI agents are evaluated vs. how knowledge workers actually operate—opening a new frontier for enterprise AI deployment beyond single-task benchmarks.

The key facts

10 to know

  1. CORPGEN framework addresses multi-task, interdependent workflows

  2. Current model evaluation misses real-world knowledge work complexity

  3. Published on Microsoft Research blog (Feb 26, 2026)

  4. Focus on practical agent deployment in enterprise settings

  5. Content appears truncated—full research depth unavailable in excerpt

  6. Research from Microsoft Research (published Feb 26, 2026)

  7. Focus on multi-tasking AI agents for knowledge workers

  8. Critique: current models evaluated on single tasks, not interdependent workflows

  9. CORPGEN framework targets simultaneous task management

  10. Relevance to enterprise AI deployment and agent evaluation standards

Go to the source

Microsoft Researchmicrosoft.com

Publisher excerpt: By mid-morning, a typical knowledge worker is already juggling a client report, a budget spreadsheet, a slide deck, and an email backlog, all interdependent and all demanding attention at once. For AI agents to be genuinely useful in that environment, they will need to operate the same way, but…
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