第二方面，企业要用好智能体需要组织和资源上的匹配。根据Anthropic 2026年的最新调研，46%的受访者表示与现有系统的集成是智能体部署的主要障碍，43%和42%的受访者分别指向实施成本和数据的可及性/质量，40%和39%的受访者表示安全/合规和员工的学习成本/抵制是重要障碍（中小企业尤其担心学习成本，51%的受访者指向这一点）。对于企业的顾虑，成本、安全等问题和技术进步的关系较大，但数据问题、集成问题、学习或人才问题都是需要企业通过组织变革、进一步数字化和全员的学习来提升。
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Finding these optimization opportunities can itself be a significant undertaking. It requires end-to-end understanding of the spec to identify which behaviors are observable and which can safely be elided. Even then, whether a given optimization is actually spec-compliant is often unclear. Implementers must make judgment calls about which semantics they can relax without breaking compatibility. This puts enormous pressure on runtime teams to become spec experts just to achieve acceptable performance.
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Chris BaraniukTechnology Reporter