As competition intensifies in the quick-service restaurant space, operators are increasingly looking for ways to improve speed, reduce labor pressure, and maintain order accuracy at scale. Lee’s Famous Recipe Chicken is responding to that challenge by expanding access to Hi Auto’s AI Order Taker across its franchise network after testing the system in 30 live locations.
The expansion reflects growing confidence in AI-driven drive-thru ordering as a practical operational tool rather than an experimental technology.
System-Wide Readiness Built Through Internal Alignment
Before introducing AI ordering broadly, Lee’s focused on aligning its internal systems. The company unified its POS system and menu database across restaurants, a foundational step that ensured consistency in how orders are processed and interpreted across the network.
This operational alignment is often overlooked in AI deployments, but it is essential for scalability. Without consistent menu structures and backend systems, AI performance can vary significantly from store to store.
With this foundation in place, Lee’s moved forward with a 30-location rollout of Hi Auto, including both company-owned and franchise restaurants operating under real-world conditions.
Optional Adoption Reinforces Franchise Independence
A key element of the rollout is that it is not mandatory. Franchisees are being given access to Hi Auto’s AI Order Taker but retain full discretion over whether to implement it in their restaurants.
This structure reflects a franchise-first philosophy, where operators are treated as decision-makers rather than recipients of centrally imposed technology mandates.
Ryan Weaver, CEO of Lee’s Famous Recipe Chicken, explained the approach: “Our operators are the backbone of Lee’s, and it’s our job to give them every advantage we can.”
He highlighted early results from participating stores, including improved labor efficiency, reduced drive-thru congestion, higher employee morale, and improved order accuracy.
Measurable Operational Gains Drive Momentum
Across the 30 locations where Hi Auto has been deployed, the system has delivered more than 95% order completion and 97% accuracy in live drive-thru environments.
These results are significant in high-volume restaurant settings, where even small inefficiencies can lead to longer wait times and reduced throughput.
Additional benefits reported by operators include labor savings of three to eight hours per day, a 17% reduction in employee turnover, and a 1.5% increase in average ticket size.
These outcomes suggest the system is not only improving efficiency but also contributing to revenue enhancement and workforce stability.
Redefining How Drive-Thru Labor Is Used
The introduction of AI ordering changes the structure of frontline restaurant labor. Instead of employees managing both order-taking and service tasks, AI handles the ordering process while staff focus on food preparation and guest experience.
This redistribution reduces pressure during peak hours, when multitasking often creates operational bottlenecks.
Over time, this shift can lead to more stable operations and improved employee satisfaction, particularly in environments facing ongoing staffing challenges.
Hi Auto’s Scale Provides Operational Confidence
Hi Auto brings significant experience to the partnership. The company powers nearly 1,000 drive-thru locations globally and processes more than 100 million orders annually. It is also used by approximately 200 franchisees across multiple regions and operational environments.
This scale provides reassurance that the system has been tested under a wide range of conditions, strengthening its suitability for broader deployment within Lee’s franchise network.
Hi Auto CEO Roy Baharav has emphasized that the company’s approach is centered on supporting operators and enhancing existing workflows rather than replacing human roles.
A Gradual, Infrastructure-Led Transformation
Rather than pursuing rapid, disruptive change, Lee’s is taking an incremental approach to AI integration. The combination of backend standardization and optional technology deployment allows innovation to scale without forcing uniform adoption across franchisees.
This ensures that each operator can evaluate and adopt the system based on their own operational needs while still benefiting from centralized investment in technology readiness.
As more franchisees consider implementation, Lee’s approach may serve as an example of how QSR brands can integrate AI into core operations in a way that balances innovation with flexibility and franchise autonomy.
