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Snowflake:2026创业新局:AI智能体开启商业新纪元研究报告(中译版)(20页).pdf

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1、STARTUP 2026 AI AGENTS MEAN BUSINESS What venture capitalists are looking for in the era of agentic AITABLE OF CONTENTSAI Continues to Evolve Across the Enterprise .3Investment Strategies Shift in the AI Era Sort Of .6Capital Concentration:Risk or Opportunity?.8Year of the Agents Part Two:Setting Up

2、 Real Progress .10Defensible Barriers Protect Competitive Advantage .12Early Adopters Are in Production,Finding Value .14What to Watch in 2026 .16Secrets of an Irresistible Pitch .17Riding the Next Wave of AI Innovation .19Next Steps .20Table of Contents|2 Startup 2026:AI Agents Mean Business AI Con

3、tinues to Evolve Across the EnterpriseAI hype is alive and well.2025 was named by many in tech as the“the year of the agents”as companies across industries and around the globe raced to infuse AI throughout their business functions.Business leaders felt the pressure from their peers to implement AI

4、at every point in their workflows for fear of being left behind.Its still too early to broadly measure the ROI of agentic AI.It has yet to achieve the level of autonomy and complexity at the core of its promise,but weve seen some key and proven workloads start to move into production,such as agentic

5、 coding.Agentic AI remains an area of tremendous excitement for businesses,venture capitalists and AI-focused startups with the potential to significantly impact innovation,business strategy,revenue and more.Last year,we sat down with investors at eight leading venture capital firms to gain their pe

6、rspectives on the state of AI in the startup space.This year,we did it again,with new and familiar faces.For this version of the report,we focused on how investors approach to AI startups is evolving and where they think AI in general,and agents in particular,are headed in 2026.We started off the co

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1. **AI企业应用深化**:2025年AI从实验转向生产,物流、保险等传统行业落地,如理赔处理、风险建模,提升利润;AI工具使员工效率提升10-100倍。 2. **投资策略分化**:VC关注基础模型与应用层,垂直行业AI(医疗、建筑)受青睐;资本向头部模型公司集中,但中小市场仍存机会。 3. **智能体(Agents)进展**:2025年未达预期,主要处理结构化任务,长周期任务因错误累积受限;2026年将聚焦实际成果。 4. **竞争壁垒**:护城河来自专有数据、深度工作流整合及领域 expertise,避免依赖第三方接口。 5. **2026年展望**:物理AI(机器人)、个性化体验及小模型效率优化将成重点;企业预算向AI与安全融合倾斜。
AI投资风向? 代理AI突破点? 创业者如何胜出?
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