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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
- Salesforce study warns against rushing LLMs into CRM . . . - CIO
Salesforce’s CRMArena-Pro test reveals state-of-the-art models—including GPT-4o—fail to meet critical enterprise needs in CRM, especially around secure, multi-turn processes
- Study shows AI agents struggle with CRM and confidentiality
Large Language Model (LLM) agents aren’t very good at key parts of CRM, according to a study led by Salesforce AI scientist Kung-Hsiang Huang The report showed AI agents had a roughly 58% success rate on single-step tasks that didn’t require follow-up actions or information That dropped to 35% when a task required multiple steps
- Salesforce Study Warns: Don’t Rush LLMs into CRM Without . . .
<p>Key Takeaways: A new study from Salesforce AI Research is cautioning enterprise leaders not to deploy generative AI agents into CRM workflows without clearly defined safety and performance guardrails According to results from Salesforce’s CRMArena-Pro benchmark, top-performing large language models such as GPT‑4o and Gemini 2 5 Pro demonstrated only 35% accuracy on multi-step tasks
- Salesforce Study Finds LLM Agents Flunk CRM and . . .
A new Salesforce-led study found that LLM-based AI agents struggle with real-world CRM tasks, achieving only 58% success on simple tasks and dropping to 35% on multi-step ones They also demonstrated poor confidentiality awareness "Agents demonstrate low confidentiality awareness, which, while impr
- CRM AI: Confidentiality Concerns Persist - SUCCESS QUARTERLY . . .
The study paints a picture of stark contrasts in AI performance On the one hand, LLM agents demonstrated a modest 58% success rate on straightforward, single-step tasks that required no follow-up This indicates a baseline capability, a certain aptitude for simple, isolated actions
- Salesforce Study: LLMs Underperform in Enterprise CRM
Perhaps even more troubling than operational inefficiency is the glaring failure of these agents to uphold data confidentiality – a non-negotiable cornerstone of any robust CRM system The arXiv paper chillingly notes that many models struggled to identify and protect sensitive customer information, inadvertently disclosing data in simulated
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