Abstract

The article examines the impact of a voice AI assistant on the efficiency of support‑team interactions in the restaurant and service sectors. The study justifies the urgency of deploying a voice AI assistant against the backdrop of rising costs for manually handling telephone inquiries and increasing labor expenses for restaurant call-center operators. Given that the telephone remains a critically important channel for restaurants and delivery services, automating routine requests can deliver a significant economy of scale and accelerate return on investment. The aim of this work is a quantitative and qualitative assessment of the voice AI assistant’s effect on key support‑service metrics: average handle time (AHT), the rate of calls completed automatically, and the level of abandoned calls. The novelty of the study lies in its comprehensive approach, which combines the analysis of 50,000 Slang AI dialogues, calculations of Hostie AI’s economic impact, evaluation of modern ASR module accuracy under noisy conditions, and a systematic review of pilot projects by Wendy’s FreshAI, PolyAI at Golden Nugget, and DoorDash. Methodologically, the work relies on correlational and statistical analyses, conversational content analysis, and comparative analysis of pre‑ and post‑integration periods. The main findings demonstrate that implementing a voice AI assistant can reduce AHT by 20–40% (from 6 to 4.5 minutes), automate 34% to 86% of calls depending on the scenario, lower peak‑hour abandonment rates from over 10% to industry benchmarks (5–8%), and free up to 150 operator hours per month at 10 000 calls. Integration with POS, CRM, and courier services not only eliminates manual-entry errors but also implements an upsell protocol, resulting in a growth of average check size and outlet margin by up to 80 basis points per year. At the same time, high levels of customer satisfaction (CSAT, NPS) are maintained through instant fallback to a live agent and multilingual support. This article will be helpful to executives of restaurant and service companies, AI‑technology implementation specialists in contact centers, analysts, and voice‑interface developers.

Keywords

  • voice AI assistant interaction efficiency callcenter automation Average Handle Time abandoned calls

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