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AI news for: Autonomous Agent

Explore AI news and udpates focusing on Autonomous Agent for the last 7 days.

With Amazon And Salesforce As Customers, Agentic AI Startup AppZen Lands $180M To ‘Transform’ Finance Teams
With Amazon And Salesforce As Customers, Agentic AI Startup AppZen Lands $180M To ‘Transform’ Finance Teams
source news.crunchbase.com Sep 22, 2025

AppZen, which has built an agentic AI platform for finance teams, has raised $180 million in a Series D round, the company told Crunchbase News. River...

TL;DR
AppZen, an agentic AI startup, raises $180M in a Series D round from Riverwood Capital, citing its mission to 'transform' finance teams with AI agents.

Key Takeaways:
  • AppZen has raised a total of $290 million over its lifetime and counts over 500 global enterprise companies, including Amazon and Salesforce, as customers.
  • The company claims its proprietary AI models, combined with its Mastermind AI Studio, provide a more effective solution than traditional LLMs and automation tools.
  • AppZen's agentic AI platform automates manual work for finance teams, allowing companies to manage growing complexity without adding headcount.
50 AI agents get their first annual performance review - 6 lessons learned - ZDNET
50 AI agents get their first annual performance review - 6 lessons learned - ZDNET
source www.zdnet.com Yesterday

50 AI agents get their first annual performance review - 6 lessons learned ZDNETThe agentic organization: Contours of the next paradigm for the AI era...

TL;DR
A year-long experiment with 50 AI agents by McKinsey revealed six key lessons, emphasizing the need for careful planning, human oversight, and collaboration.

Key Takeaways:
  • Agentic AI efforts should focus on injecting agents to boost workflows and address key user pain points.
  • AI agents aren't the best answer to every business need, and simpler options like rules-based automation or large language model prompting may be more suitable.
  • Companies should invest in agent development, onboard agents, and provide continual feedback to improve their performance and address issues like 'AI slop' or low-quality outputs.
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