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  • LLM agents flunk CRM and confidentiality tasks • The Register
    A new benchmark developed by academics shows that LLM-based AI agents perform below par on standard CRM tests and fail to understand the need for customer confidentiality A team led by Kung-Hsiang Huang, a Salesforce AI researcher, showed that using a new benchmark relying on synthetic data, LLM
  • Salesforce study finds LLM agents flunk CRM and confidentiality tests . . .
    A new benchmark developed by academics shows that LLM-based AI agents perform below par on standard CRM tests and fail to understand the need for customer confidentiality A team led by Kung-Hsiang Huang, a Salesforce AI researcher, showed that using a new benchmark relying on synthetic data, LLM agents achieve around a 58 …
  • Salesforce study finds LLM agents flunk CRM and confidentiality tests
    A team led by Kung-Hsiang Huang, a Salesforce AI researcher, showed that using a new benchmark relying on synthetic data, LLM agents achieve around a 58 percent success rate on tasks that can be completed in a single step without needing follow-up actions or more information
  • AI in CRM: Promise and Pitfalls Revealed by Salesforce Study
    The study, as covered by The Register, highlights that LLM agents consistently underperformed across essential business skills, with success rates below 38 percent for multi-step tasks This suggests a fundamental disconnect between the raw intelligence of these models and their practical application in professional environments where precision and context are paramount
  • Salesforces CRM benchmark finds AI agents struggle in real-world . . .
    Salesforce has launched CRMArena-Pro, a benchmark designed to evaluate AI agents in practical business situations, including multi-step conversations and data protection checks within CRM systems Leading models like Gemini 2 5 Pro succeed in just 58 percent of straightforward tasks, and their accuracy drops to 35 percent in extended dialogues, mainly because they often miss key questions
  • AI Agents Drop the Ball: Struggling with CRM and Confidentiality . . .
    Researchers at Salesforce have revealed that LLM-based AI agents are struggling with CRM tests, achieving only a 58% success rate on single-step tasks and a mere 35% on multi-step tasks The CRMArena-Pro tool highlights their poor performance and low confidentiality awareness There's a significant gap between LLM capabilities and real-world enterprise demands
  • Salesforce study finds LLM Agents Fail 65% of CX Tasks: what this means . . .
    What Salesforce’s AI Study Reveals About Agent Accuracy The Salesforce study evaluated large language model (LLM)-based agents across single-turn and multi-turn customer support scenarios These included: Refund and cancellation requests Account updates Order tracking Payment failures General product inquiries





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