Core Insights - The core message emphasizes that generative AI has transitioned from a storytelling phase to a practical application phase, where embedding AI into business processes is crucial for success in the future [1][2] Organizational Barriers - Three main organizational barriers hinder the implementation of generative AI in enterprises: - Resistance from personnel due to differing levels of understanding of AI, leading to communication issues [2] - Organizational resistance characterized by departmental silos that prevent data sharing and process integration [2] - Capability resistance where a lack of skills results in the inability to effectively utilize purchased technology [2] Technical Barriers - Three primary technical barriers complicate the deployment of generative AI: - Difficulty in identifying suitable application scenarios within enterprises, as IT personnel may lack business knowledge [2] - High technical thresholds for application, making it challenging for in-house IT teams to implement AI effectively [2] - Customization challenges due to insufficient data, which hampers the development of models that truly understand business needs [2] Strategic Approach - The company adopts a "top-down" strategy, termed "One-Person Project," to address organizational barriers by aligning the understanding of AI among top management and creating tailored solutions [5][8] - The "Forward Deployed Engineer (FDE) model" is implemented to ensure engineers work closely with client business teams, facilitating the integration of business needs with technical solutions [5][8] Government and Enterprise Engagement - The company targets new productivity industrial parks with a phased approach to create a closed-loop industry ecosystem, including various model training and application development bases [6] - For enterprises, the company promotes a customized consulting model to drive process reengineering and technology implementation, ensuring a closed-loop iteration [6] Case Study and Implementation - A case study of a large global industrial enterprise illustrates the company's "1+3+9" integrated service model, which includes strategic design, platform implementation, and high-value scenario realization [8] - The company has established deep collaborations with leading firms across various sectors, including telecommunications and finance, to deploy its generative AI solutions [8] Ecosystem Development - The company aims to become an ecosystem connector in the AI 2.0 era, fostering collaboration among industry clients, partners, and itself to co-create innovative solutions [8][12] - A multi-tiered partner ecosystem is being built, offering various levels of collaboration and support to enhance joint market development and product co-creation [10][11] Future Vision - The company envisions generative AI as an open, shareable, and extendable "ecological origin," emphasizing the importance of deep integration with vertical industries and third-party developers [12]

海内外科技企业Agent产品持续涌现，行业对于AI Agent在技术架构和产品形态层面正在逐步成型， 2025年正在成为"AI Agent元年"。 "超级智能的AI和Agent将无处不在，我们相信它将带来有史以来最大规模的经济飞跃。到2035年，全球 GDP的增长率将远超以往，迎来一个新增长的黄金十年。"近日，在零一万物举办的"'元启上海'华东数 智大会"上，零一万物CEO李开复在演讲中表示。 AI正从依赖数据规模的知识积累，跃迁至具备强大推理能力的新阶段。对于企业来说，这将重塑企业 价值链与业务流程，消除内部沟通壁垒，带来"基于结果"的商业模式再造。 Gartner曾在报告中预测，到2028年，33%的企业级软件应用将整合AI Agent，届时，15%的日常工作任 务决策可实现完全自主化。 李开复表示，AI Agent浪潮是中国产业升级、实现数智化转型必须抓住的机遇，将深刻改变组织的工作 方式和组织形态，成为推动下一轮商业智能变革的核心引擎。 从"降本"到"增效" Agent已经不是一个新的概念，多家大厂和创业公司纷纷布局，但市场对于其实际应用效果一直有疑 虑。 当前，各行各业生产力的构成当中有部分逐步通过 ...

（原标题：李开复： AI落地企业，智能体是CEO最需关注的核心技术） Gartner曾在报告中预测，到2028年，33%的企业级软件应用将整合AI Agent，届时，15%的日常工作任 务决策可实现完全自主化。 李开复表示，AI Agent浪潮是中国产业升级、实现数智化转型必须抓住的机遇，将深刻改变组织的工作 方式和组织形态，成为推动下一轮商业智能变革的核心引擎。 （零一万物CEO李开复、联创沈鹏飞接受记者采访 董静怡/摄） 从"降本"到"增效" Agent已经不是一个新的概念，多家大厂和创业公司纷纷布局，但市场对于其实际应用效果一直有疑 虑。 "AI Agent如果只能做到降本，那企业客户的付费意愿其实还是偏低的。"零一万物联合创始人沈鹏飞向 21世纪经济报道记者表示，企业更为关注的是其能否真正带来"增量"价值。 而如今，Agent技术在经历重要演进。 21世纪经济报道记者 董静怡 上海报道 海内外科技企业Agent产品持续涌现，行业对于AI Agent在技术架构和产品形态层面正在逐步成型， 2025年正在成为的"AI Agent元年"。 "超级智能的AI和Agent将无处不在，我们相信它将带来有史以来最大 ...