Autonomous digital assistants perform computational duties that extend well beyond returning text responses. According to Nvidia, modern systems do more than simply generate output, as they actively "search for information, query databases, write and test code and take action." Rather than running entirely on specialized accelerators, "each of those steps relies on a CPU" to handle operational demands.
The underlying architecture of an agent involves alternating compute phases rather than a single unified pipeline. Throughout their runtime, systems function with "agents moving between GPU reasoning and CPU execution throughout a task." Because of this continuous transition, hardware needs are shifting. As commercial deployment scales up, modern "AI factories need CPUs" designed to support these hybrid operational cycles.