Dairy Queen Extends AI Drive-Thru Testing Across Franchise Locations

Why It Matters

The rollout shows that AI‑driven ordering is maturing enough for large franchised chains, potentially reshaping labor costs and increasing average ticket size across the fast‑food sector.

Key Takeaways

• AI drive‑thru pilot now in several dozen Dairy Queen franchisees
• Voice AI targets order accuracy, speed, and consistent upselling
• Presto competes with SoundHound and other vendors in a crowded market
• Gradual rollout lets operators weigh performance against implementation costs

Pulse Analysis

The quick‑service restaurant (QSR) landscape has long wrestled with the paradox of high‑volume drive‑thru demand and chronic labor shortages. Dairy Queen, with more than 7,700 locations worldwide, has historically relied on a human‑centric ordering model, but the brand’s recent AI expansion reflects a broader industry shift toward automation. Drive‑thrus account for the majority of sales for many QSRs, making them a prime target for technology that can standardize the ordering experience, reduce turnover‑related training costs, and capture incremental revenue through consistent upselling.

Presto’s voice‑AI platform tackles the unique acoustic challenges of drive‑thru lanes—background engine noise, regional accents, and rapid‑fire ordering—by leveraging advanced speech‑recognition models and real‑time menu integration. The company’s growing client roster, which includes Carl’s Jr., Hardee’s and Taco John’s, positions it as a leading specialist in a market still fragmented among vendors like SoundHound and larger tech conglomerates. By focusing on the “last mile” of deployment—menu complexity, handoff to human staff, and error mitigation—Presto aims to demonstrate a clear economic case: higher order accuracy, faster throughput, and a modest lift in average check size that scales across high‑volume locations.

For franchisees, the decision hinges on tangible performance metrics versus the upfront cost of hardware, software licensing, and integration. A phased pilot allows operators to benchmark AI‑driven throughput against traditional staffing models, assess customer sentiment, and refine hybrid workflows where remote human agents intervene during edge cases. If the technology delivers consistent speed gains and revenue uplift, it could reshape labor allocation, shifting employees from order‑taking to food preparation and guest interaction—areas where human touch remains critical. As more QSRs adopt similar pilots, the industry will gain clearer data on whether voice AI becomes a standard drive‑thru component or remains a niche experiment.