AT&T Cuts Assistant Costs With Small Models

AT&T boosted the efficiency of its internal Ask AT&T personal assistant by reworking the orchestration layer and shifting more work from large language models to small language models, VentureBeat reported Thursday (Feb. 26). The change lowered latency and response times, cut costs by about 90% and enabled the system to process three times as many tokens. The move indicates enterprises can use SLMs to reduce operational costs while reserving LLMs for high-stakes steps.