AI and Fast Food: A Match Made in Drive-Thru Heaven

Operating a restaurant is one of the most complicated tasks—a challenging endeavor that needs a perfect dance from the backend (purchasing the right vegetables, meats, etc.) to kitchen operations (having the right cooks to cook the right meal with the right taste, every time) to frontend experience (serving the right customers the right food, with the right service standards). While you’d imagine needing a high level of technology investment to streamline this multitude of simultaneous tasks, technology investments in the restaurant industry have traditionally lagged behind other industries.

Restaurant operators have historically witnessed a tight margin structure, leaving very little wiggle room to maneuver. What’s more, with semiskilled workers earning minimum wage, restaurants have typically found it more cost-effective to employ more people than invest in technology. Plus, franchisees—who bear the burden of such investments—often prioritize near-term store profitability over long-term tech spending. Yet now, profitability pressures and the reduced gap between labor costs and tech costs are inducing restaurants to look for long-term solutions to restore profitability. As a result, AI is finally expected to find its place in the restaurant ecosystem.

Fast Food Goes High-Tech

In recent years, the restaurant industry has had to adapt to changing consumer preferences. During the pandemic, more consumers wanted to order food online and new companies emerged to help them order from different restaurants all in one place (think “aggregators” like UberEats, DoorDash, etc). Additionally, some restaurants now make food in special “ghost kitchens” just for delivery. All these changes have forced restaurants to adopt new technologies to keep up with evolving demands, with larger chains leading the charge.

That’s where AI comes in. For instance, AI can significantly ease drive-thru chaos—from lane management, order taking via voice recognition, auto product recommendation based on past order history and orders from similar customers, and effectively communicating the order to the back of the house. Bernstein Research projects that AI could halve order inaccuracies, which represent ~15% of customer orders (Display). How? AI-led vision analytics can do a quick quality check, and image-check versus the item ordered, and trigger human intervention for inaccuracies before the order leaves the counter. Since a store takes ~50 additional seconds on average to fill an inaccurate order, the impact for the industry could be in the order of $9-$10B in the US.<sup>1</sup>

Drive-thru Order Accuracy is One of the Industry’s Biggest Pain Points

Then there’s “suggestive selling.” Currently, many restaurants rely on staff to make recommendations, leading to uneven results (Display). Self-operated kiosk-based ordering and checkout has significantly eased front-of-house operations, enhanced customer experience, and improved systematic suggestive selling. With the rise of kiosk sales, restaurants are now utilizing AI to analyze past customer orders, use order similarities with other customers, optimize current store inventory levels, and incorporate current weather patterns and time of day to recommend items/product combinations to customers as they order. This usage of AI could significantly uplift average checks in a frictionless upsell/cross-sell engagement process.

Plenty of Room for AI Upselling Versus Relying on Employee Suggestions

Some believe the next evolution is AI-led digital menu boards that will recommend products depending on product inventory, kitchen capacity at the time of ordering, weather patterns, and daypart rush—or as the industry depicts it—to conduct “AI-driven suggestive selling.” For instance, McDonald’s rolled out its digital menu boards with AI-led suggestive selling and has witnessed a significant increment in check sizes. AI-generated menus could also accelerate the scaling of virtual brands and reduce the time to market for new menu introductions.

Back of the House Cases for AI

Supply chain management is one of the key pillars of good restaurant operations. Having the right vegetables/meats/condiments/oil in the right quantity at the right time is essential for service.

Restaurants often over-order to cover up for potential lack of products, so much so that 4%–10% of food purchased by restaurants never reaches consumers. With food costs at ~30% of sales, restaurants can save ~1.2%–3% in margins by streamlining supply chain operations and order management.<sup>2</sup>

Recent advancements in AI have helped link the back of the house to the front of the house. Consider Yum (parent company of Taco Bell and KFC), which uses its AI application “Recommended Ordering” to predict and recommend the quantity of products for a restaurant manager to order each week with the goal of reducing product waste and intra-store transfers of inventory.

Besides food costs, labor costs represent the largest cost item for any restaurant. With increased labor challenges, high labor turnover, and the continuous rise in the need for more flexible staffing, restaurants could benefit significantly by leveraging AI tools to optimize labor scheduling, recruiting, and retention. Recruiting is one of the low-hanging fruits—in a labor market with significant issues in filling roles, AI-led virtual assistants can accelerate the employment process by taking over basic application processes such as indexing resumes, matching skills, and scheduling interviews, making it easier to recruit talent. In addition, AI tools are also being used to optimize staff management.

The AI Secret Sauce

The restaurant industry has lagged other industries in tech innovation. Yet multiple use cases are arising with an increased AI focus (Display).

AI Application in Top Five Critical Areas Is Quite Low

Some will scale faster than others—and have a more meaningful impact on the bottom line. Scale is an important factor in ensuring maximum return from tech investments, so the ability to “operate” stores offers more control over the speed of the rollout of innovation. Ultimately, the secret sauce for digital success may rest on creating a digital culture that permeates all levels of the organization and remains consistent over time. As the fast-food industry continues to evolve, AI may prove to be a supersized idea that transforms the landscape.

Investment Strategy Group
Danilo Gargiulo
Senior Analyst—Bernstein Research Services
Bill He
Associate—Bernstein Research Services

1 As of June 2023. Assumes a US$7.6 average ticket on QSRs (per Euromonitor data) and ~200K drive-thru stores in the US. Source: Bernstein Research

2 As of June 2023. Source: Bernstein Research

The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AB portfolio-management teams.

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