这篇论文用真实数据证明了 AI Agent 在知识工作中的巨大价值——效率提升 7 倍、成本降低 94%，做 AI 产品设计或知识管理的人值得仔细看，尤其是 Perplexity 的案例很有参考意义。
这篇论文基于 Perplexity 的 Search 和 Computer 产品的实际使用数据，研究了 AI Agent 如何改变知识工作。研究发现，Computer 产品（具有自主执行能力）每个用户会话可自动完成 26 分钟的工作，而 Search 仅为 33 秒。在相同任务上，Computer 将完成时间从 269 分钟降至 36 分钟，成本降低 94%，且用户不满率降低 55%。此外，Computer 用户更倾向于尝试跨职业边界、需要高阶认知的复合任务，解锁了 Search 中几乎不存在的活动。这表明 AI Agent 不仅加速了工作流，还提升了质量、降低了成本，并扩展了自动化工作的广度和深度。
How AI Agents Reshape Knowledge Work: Autonomy, Efficiency, and Scope
Frontier AI systems are bridging the gap between intelligence and utility by shifting from conversational assistants to autonomous agents that execute tasks end to end. Using production data from Perplexity's Search and Computer products, we study this transition by examining how AI agents accelerate and reshape knowledge work. Three key empirical findings emerge. First, using sessions with near-identical initial query pairs as natural experiments for the same underlying task attempted with both products, Computer performs 26 minutes of autonomous work per user session, versus 33 seconds for Search. Computer automates task decomposition and execution that Search users might otherwise manually orchestrate and implement. As a result, Computer shifts follow-up query distribution toward higher-order work such as verification and extension. Autonomy also increases execution quality, with per-query dissatisfaction rates 55% lower on Computer than on Search. Second, due to its autonomy advantage, Computer reduces completion time from 269 to 36 minutes on matched tasks, lowering estimated time and cost by 87% and 94%, respectively, compared to humans equipped with Search alone. Third, Computer changes the scope of work that users attempt: Computer queries more often cross occupational boundaries, require higher-order cognition, draw on broader expertise, take the form of composite tasks that bundle interdependent subtasks into a single query, and unlock work activities that are essentially absent from Search usage among the same users. Together, the evidence indicates that AI agents accelerate workflows, enhance output quality, reduce costs, and expand the breadth and depth of automated work.