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.

翻译：前沿AI系统正从对话助手转向端到端执行任务的自主代理，弥合了智能性与实用性之间的差距。我们利用Perplexity搜索与计算机产品的生产数据，通过研究AI代理如何加速并重塑知识工作，来考察这一转变。三大主要实证发现浮现。首先，将具有近乎相同初始查询对的会话作为同一基础任务在两种产品上的自然实验，计算机每个用户会话执行26分钟的自主工作，而搜索仅33秒。计算机自动进行搜索用户可能需手动编排与执行的任务分解和操作，从而将后续查询分布转向验证与扩展等高阶工作。自主性还提升了执行质量：计算机每次查询的不满意度比搜索低55%。其次，由于自主性优势，计算机将匹配任务的完成时间从269分钟缩短至36分钟，相比仅配备搜索的人类用户，预估时间和成本分别降低87%和94%。第三，计算机改变了用户尝试的工作范围：其查询更常跨越职业边界，需要高阶认知，依赖更广泛专业知识，采取将相互依赖的子任务捆绑至单一查询的复合任务形式，并解锁了同一用户在搜索使用中基本不涉及的工作活动。综上所述，证据表明AI代理能加速工作流、提升输出质量、降低成本，并扩大自动化工作的广度与深度。