By Casey Smallwood of SRS Real Estate Partners
In today’s fiercely competitive quick-service restaurant (QSR) market, digital transformation and artificial intelligence (AI) are reshaping how brands operate, engage with customers and create value. An industry once defined by speed and consistency is now being reshaped by data, automation and intelligent personalization. Across the country, QSRs are embracing cutting-edge technologies to improve operations, enhance the customer experience and maximize profitability.
From mobile ordering apps to AI-powered drive-thru automation and predictive inventory management, these innovations are redefining the QSR business model. To stay competitive and relevant in today’s fast-changing market, franchise operators, developers and commercial real estate investors must understand and adapt to these technology-driven shifts.
At the heart of this evolution is digital transformation — the integration of digital technology across all aspects of the business. In the QSR landscape, this includes everything from mobile ordering apps, digital menu boards to contactless payment systems, smart kitchen equipment and sophisticated customer relationship management (CRM) tools.
Unlike full-service restaurants that emphasize ambiance and table service, QSRs succeed by offering speed, convenience and consistency. Digital transformation amplifies these core strengths, allowing operators to serve more customers faster and more accurately while also collecting and leveraging data to improve operations and improve experiences.
Mobile Ordering Apps
One of the most visible developments in the QSR sector has been the adoption of mobile ordering apps. What began as convenience has quickly become an important part of the customer experience. Leading brands like Chick-fil-A, McDonald’s and Starbucks Coffee now allow customers the ability to browse menus, customize orders, pay in advance and pick up at the counter, curbside or drive-thru — all with minimal friction.
This added convenience leads to higher customer satisfaction and stronger brand loyalty. A recent Deloitte report found that nearly 60 percent of QSR customers favor mobile apps over traditional ordering channels — a preference that’s even more pronounced among younger demographics.
The benefits for operators are equally significant. By minimizing miscommunication, these platforms improve order accuracy, while enabling kitchens to begin preparation before the customer arrives, ultimately reducing wait times. Mobile apps also serve as powerful marketing tools, upselling through personalized offers and suggested add-ons. Perhaps most importantly, they generate rich data on customer preferences and purchasing patterns, allowing restaurants to fine-tune promotions and adjust menu selections in response to real-time demand.
Enhancing Drive-Thru Operations
Drive-thru lanes have long been a lifeline for QSRs, especially during the COVID-19 pandemic when dining rooms were closed. But even as restrictions have eased, the drive-thru remains a preferred channel for many customers. Recognizing this, QSRs are investing heavily in AI-driven technologies to improve speed and accuracy while reducing labor costs.
AI-powered voice assistants — essentially digital order takers — are now being deployed to handle drive-thru interactions. These systems use natural language processing (NLP) to understand customer orders, confirm details and send tickets directly to the kitchen. Brands like Checkers/Rally’s, Hardee’s and Panera Bread are piloting or rolling out these solutions across their locations.
By eliminating the need for a human employee to take orders, AI voice assistants reduce staffing pressures and enable employees to focus on food preparation and customer service. They also reduce errors that commonly occur due to misheard orders, language barriers or multitasking.
Meanwhile, computer vision technology is transforming the way QSRs monitor and manage drive-thru performance. Cameras integrated with AI software can detect car count, identify license plates (where permitted), measure service times and even track facial expressions to assess customer satisfaction. This real-time visibility enables managers to address bottlenecks, adjust staffing and ensure service-level targets are met.
Predicting Demand and Optimizing Operations
Behind the scenes, AI and machine learning are helping QSRs predict customer demand and manage inventory with improved accuracy over traditional forecasting methods. Predictive analytics tools analyze historical sales data, local weather, upcoming event schedules and even social media trends to predict what customers will want and timing.
This data helps restaurants improve staffing schedules, prepare for peak times and order products more efficiently. The result is a leaner, smarter supply chain that reduces food waste, minimizes stockouts and improves profit margins.
For instance, a QSR chain in Florida might use predictive analytics to forecast increased demand for cold or frozen beverages during a heatwave or to anticipate increases in foot traffic during spring break. Having the right inventory in place improves customer experience and the QSR’s profits.
Smarter Kitchens, Personalized Marketing
Restaurant chains are also using AI to automate back-of-house operations, including prep guides that adjust in real-time based on order volume, helping with consistent customer experience during peak times.
AI isn’t just improving operations; it’s making customer relationships more personalized. QSRs are leveraging AI-powered CRM systems to deliver personalized offers, loyalty rewards and customized menus based on individual preferences.
For example, a customer who frequently orders spicy chicken sandwiches through a mobile app might receive a push notification when a new spicy item launches. Or a customer who visits on weekday mornings may get a promotion for discounted breakfast combos during morning commute hours.
These brief interactions boost engagement, encourage repeat visits and increase average ticket size. Loyalty programs embedded within mobile apps reward customers for their purchases while also reinforcing habits and building brand loyalty.
Starbucks, for example, was an early adopter in this area, using AI to power its Deep Brew engine, a personalization tool that influences functions such as app recommendations marketing messages and inventory planning.
Labor Optimization and Operational Efficiency
The labor shortage that has gripped the service industry in recent years has only accelerated the adoption of automation and AI. With higher wages and high turnover, QSRs are seeking new ways to do more with less. AI technologies are stepping in to fill these gaps by automating repetitive tasks and providing real-time performance insights.
In addition to AI voice assistants and predictive scheduling, some restaurants are experimenting with robotics for food prep and kitchen automation. While still in the early stages, robotic fryers, drink dispensers and burger-flipping arms are showing promise in reducing workload and ensuring consistent food quality.
Smart kitchen systems that integrate orders from multiple channels — mobile, in-store, delivery — help streamline workflows and reduce chaos during peak hours. Managers can access dashboards that show real-time metrics on throughput, wait times and staff productivity, allowing for better decision-making and immediate course corrections.
These technological shifts are having deepening effects on QSR site selection, store design and real estate strategy. As digital and drive-thru platforms receive attention, traditional dine-in spaces are being downsized or eliminated altogether. New prototype designs from major chains feature double or even triple drive-thru lanes, dedicated mobile order pickup areas and smaller footprints for off-premises consumption.
Taco Bell’s “Go Mobile” and McDonald’s “Order Ahead Lane” concepts are great examples. These high-efficiency models serve to digital-first customers and require less real estate while delivering greater throughput.
For developers and investors, this means evaluating properties based on accessibility, traffic flow, and digital infrastructure readiness. Locations equipped to support mobile pickup area, third-party delivery drivers and drive-thru upgrades are in high demand.
Additionally, being close to tech-savvy demographics, like urban professionals and college students is increasingly important. These consumers are more likely to use mobile ordering and respond to digital promotions, making them ideal targets for AI-enhanced QSR operations.
Although integrating AI and digital tools into QSR operations offers clear benefits, it also has significant challenges, including high upfront investment costs, data privacy concerns, cybersecurity threats and resistance from the existing workforce. Smaller operators, especially, may struggle to justify large technology investments without the advantages of scale.
Moreover, the fast pace of innovation means today’s solutions can quickly become obsolete. QSRs must be agile, continuously testing and adapting to stay ahead of consumer expectations and technological shifts.
There is also a need for balance when adopting automation. While efficiency is key, QSRs must retain the human touch that many customers still appreciate. Hybrid models that combine technology with hospitality, such as AI-driven service with human oversight, may offer the most ideal solution.
The QSR of the future is one where AI and digital tools work together to create a faster, smarter and more personalized experience for every customer. Whether through mobile ordering, automated drive-thru lanes or data-driven inventory management, these innovations are becoming crucial for staying competitive in a crowded and evolving marketplace.
In the Southeast, where population growth, tourism and a strong food culture continue to drive demand, QSRs that adopt digital transformation are positioned for longer term success. The intersection of technology and real estate will shape the next decade of growth, and companies that invest in both will themselves in a position to thrive.
For commercial real estate professionals, the message is clear: the future of QSRs is not just about location, but about integration of data, automation and customer insights. As AI transforms the industry, those who adapt quickly and build with technology in mind who will emerge as leaders.
— Casey Smallwood is the senior vice president and managing principal of SRS Real Estate Partners’ Louisville, Ky., office.