August 13, 2025

AI Drive-Thru Technology: How QSRs Can Boost Performance & Protect Revenue

According to Patron.AI, restaurants using AI in their drive-thrus are cutting service times by 35 seconds and increasing throughput by nearly 23% during peak hours.

For quick-service restaurants (QSRs), those seconds aren’t just convenience… they’re revenue. And as competition heats up, AI-powered video analytics are becoming a game-changer for improving speed, accuracy, and customer experience.

In the QSR industry, the drive-thru is often the biggest revenue driver and the most visible part of the customer experience. But with labor shortages, shifting consumer demands, and rising operational costs, operators are under more pressure than ever to keep lines moving and orders accurate.

To dig deeper into how AI is reshaping drive-thru operations, we spoke with Kyle Vanderlinden, Senior Product Manager – AI & Analytics at Envysion. In this Q&A, Kyle shares the biggest challenges facing operators today, the hidden inefficiencies that cost brands time and money, and how AI-powered drive-thru analytics can deliver faster, smarter, and more profitable service.

 

Top Drive-Thru Challenges for QSR Operators

Q: What challenges are QSR operators facing today when it comes to drive-thru operations?

A: From my conversations with operators every day, the biggest challenges are staffing shortages, longer wait times, and order accuracy. Labor gaps make it tough to cover peak hours, which drives wait times beyond 3 minutes in some locations. Incorrect orders cut into revenue and impact customer satisfaction. Rising costs and supply chain issues add more strain. With drive-thru sales often representing 60–70% of QSR revenue, slowdowns have a direct effect on profitability. At Envysion, we are using AI drive-thru analytics to streamline traffic flow, improve accuracy, and help operators maintain a positive customer experience.

 

Q: What trends in consumer behavior or labor are forcing QSRs to rethink the drive-thru experience?

A: Customers want speed, accuracy, and value. Gen Z diners, in particular, are looking for bold flavors, customization, and the ability to order digitally. Economic pressures have slightly reduced overall QSR traffic, so every transaction matters. On the labor side, staffing shortages are accelerating the adoption of automation, including AI-powered voice ordering. Operators are investing in predictive analytics and AI video intelligence to anticipate problems and keep drive-thru operations efficient.

 

Q: Why is the drive-thru experience so critical to a brand’s reputation and bottom line?

A: The drive-thru is the main brand touchpoint for most customers. More than half of U.S. QSR revenue comes through this channel, and poor experiences, such as long waits or incorrect orders, can quickly lead to lost business and negative reviews. A smooth, efficient drive-thru experience can increase repeat visits and upselling opportunities. Our AI-powered metrics help operators fine-tune performance to protect both brand reputation and profitability.

 

Fixing Blind Spots in Drive-Thru Operations

Q: What are the biggest blind spots brands have in their drive-thru operations today?

A: Many operators lack real-time visibility into vehicle flow and order progress. Without knowing where bottlenecks occur or how long cars idle at the menu board, efficiency and revenue suffer. Customer experience can also decline due to unclear signage or unmonitored service times. AI video analytics closes these gaps by turning camera feeds into actionable insights.

 

Q: Why do you think many QSRs are still using outdated tools to measure drive-thru performance?

A: It is often due to cost concerns or reliance on legacy systems that once worked “well enough.” Some brands still depend on basic timers or manual logs, which cannot scale with today’s fast-moving QSR environment. AI-driven systems now offer smoother adoption, faster ROI, and the ability to adapt quickly to changes in traffic patterns.

 

Q: What makes a camera-based solution easier or more practical than other drive-thru tracking systems?

A: Camera-based systems are simple to install compared to traditional loop sensors or other hardware. There is no need for construction, just mount, connect, and start tracking. They integrate with existing technology and scale easily across multiple locations. With Envysion’s cloud-based updates, QSR operators can keep their systems up to date without complicated or costly upgrades.

 

How AI Drive-Thru Analytics Improve Performance

Q: What did Envysion see in the market that made you say, “we need to build this?”

A: Operators had plenty of data from POS systems and timers, but no unified way to understand how it all connected. There was no holistic view of traffic patterns, customer flow, and order accuracy. AI-powered video intelligence bridges that gap by converting visual data into actionable metrics, helping operators respond faster and smarter.

 

Q: There are plenty of solutions that claim to optimize drive-thrus. What’s broken in that approach, and how does Envysion think differently?

A: Many solutions focus solely on speed of service without addressing the root causes of inefficiency. Envysion’s AI drive-thru analytics provide a complete view of performance, combining vehicle detection, dwell times, and contextual video insights to show not just what happened, but why it happened.

 

Q: How does this solution give operators better insight into their drive-thru performance, and what sets it apart from other tools on the market?

A: Our platform delivers real-time dashboards that break down each stage of the drive-thru journey, from pre-menu queues to handoff times. AI identifies trends before they become service issues, allowing proactive adjustments. Unlike basic timers, our video intelligence explains the “why” behind the numbers.

 

Q: AI can sometimes feel like “just more data” for already overloaded managers. How does Envysion use AI to make their lives easier?

A: We focus on actionable insights, not overwhelming data. AI highlights specific opportunities, such as reallocating staff during peak hours, and automates reporting to save time. This shifts managers’ energy from data processing to operational improvements.

 

Operational Wins with AI Video Intelligence

Q: What kind of data or trends can operators uncover with it that they couldn’t see before?

A: Operators can now identify trends like customer abandonment during long waits, weather-related slowdowns, and inefficiencies in lane usage. AI video analytics captures menu board engagement and other details that are impossible to measure manually.

 

Q: What’s something that operators can fix immediately once they start seeing the data?

A: Order point bottlenecks are often the first improvement. Data may show confusing signage or poor staffing allocation, both of which can be corrected quickly to reduce wait times and increase throughput.

 

The Future of AI in Quick-Service Restaurants

Q: What does the future of drive-thru operations and AI technology look like, and how will video intelligence shape it?

A: The future will be predictive and personalized. AI will forecast peak hours, automate upselling, and use vehicle recognition to speed service. Video intelligence will enable real-time decision-making, moving operators from reactive problem-solving to proactive performance optimization.

 

Q: What excites you most about the future of AI technology in the QSR space?

A: The potential for complete, end-to-end optimization. AI will combine video, voice, and transactional data to deliver faster, more personalized experiences that drive loyalty and revenue. We are heading toward a future where QSR drive-thrus are not only quicker, but smarter and more customer-focused.

 

See How AI-Driven Video Intelligence Can Elevate Your Drive-Thru Performance

Ready to see how Envysion’s Drive-Thru Performance uses AI video analytics to protect your business and improve operations? Chat with Envysion experts, backed by Motorola Solutions Inc., and put smart, reliable insights to work for you.

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