By Dustin Stone, RTN staff writer - 8.12.2026
McDonald’s is nearing completion of a sweeping technology consolidation that will bring data from its major global markets into a common repository, creating a foundation for a much broader use of artificial intelligence across marketing, loyalty and restaurant operations. Chairman and CEO Chris Kempczinski disclosed the effort during the company’s August 4 earnings call, saying McDonald’s is close to putting its major markets on one app, one loyalty program, one pricing engine, one human resources system and one finance system. With those systems increasingly connected, the company expects its data to be pooled in a global data lake that can support new AI applications.
The scale of the customer data involved is enormous. McDonald’s reported nearly 220 million 90-day active loyalty users across 70 markets at the end of the second quarter, up 13 percent from a year earlier, while systemwide sales to loyalty members exceeded $40 billion during the trailing 12 months. The loyalty business alone now gives McDonald’s an identified customer population larger than the total population of many countries and a continuously expanding record of purchasing behavior across one of the world’s largest restaurant systems.
The disclosure drew wider attention after TechTimes reported that McDonald’s was pooling loyalty data into a global AI system. McDonald’s has not said that 220 million individual customer records are being loaded into a single AI training model, and Kempczinski’s comments referred more broadly to company data being consolidated in a global data lake. The company’s current privacy statement does, however, explicitly say that McDonald’s uses information it collects to train algorithms and AI models, personalize products and services, conduct business analytics and support targeted marketing.
McDonald’s has been building toward this architecture for several years. In 2023, the company set a goal of growing its loyalty program from 150 million to 250 million 90-day active users by 2027 while increasing annual loyalty-related systemwide sales from more than $20 billion to $45 billion. With nearly 220 million active users and $40 billion in trailing 12-month loyalty sales today, McDonald’s has already traveled most of the distance toward both targets.
Loyalty has consequently become much more than a mechanism for awarding points and free food. Every identified transaction can help McDonald’s understand which products a customer buys, how frequently that customer visits, which promotions generate a response and how purchasing behavior changes over time. When transaction histories are combined with digital interactions, restaurant location, time of visit and other permitted data, the company can build increasingly detailed models of customer behavior.
McDonald’s own U.S. privacy statement, updated July 1, provides a window into the scope of that information. For MyMcDonald’s Rewards participants, the company says it may collect records of purchases, interactions with the app and restaurant technologies, geolocation when enabled and inferences drawn from those categories to create consumer profiles. The broader privacy statement says collected information may be used to train algorithms and AI models, improve products and services, personalize experiences and conduct consumer and operations research.
The commercial value of those capabilities became particularly visible during McDonald’s second quarter. The company reported only 0.8 percent comparable sales growth in the United States, below its expectations, after pulling back on digital offers while introducing changes to its broader value platform. Management estimated that value execution issues, including the reduction in digital offers and elimination of the Buy One, Add One for $1 program, accounted for roughly two-thirds of the customer traffic shortfall relative to expectations.
Those results demonstrated how tightly digital engagement has become connected to restaurant traffic. McDonald’s said some of its most loyal customers reduced their visits after digital offers were scaled back, leading the company to respond with national digital flash offers and more personalized offers aimed at high-frequency and loyal customers. Loyalty data is therefore no longer a peripheral marketing asset for McDonald’s but an increasingly important component of pricing, promotion and traffic management.
The global data lake should give McDonald’s a much larger foundation for determining which promotions work for different types of customers. A restaurant chain traditionally might send the same coupon to millions of people and evaluate the campaign afterward, while a more sophisticated platform can select different offers based on prior behavior, frequency, product preference and expected response. At McDonald’s scale, even a small improvement in the percentage of customers who respond to an offer can translate into substantial incremental sales.
The same data can also help the company reduce unnecessary discounting. A frequent customer who is likely to purchase without an incentive does not necessarily need the same promotion as a customer whose visits are becoming less frequent. Better models can help restaurants direct discounts toward customers or occasions where an incentive is more likely to alter behavior rather than simply subsidizing a transaction that would have occurred anyway.
McDonald’s has been experimenting with this type of personalization for years. The company acquired Dynamic Yield in 2019 to bring machine-learning-based personalization to drive-thru menu boards and other digital ordering channels, using factors such as time of day, restaurant traffic and trending products to influence recommendations. McDonald’s later sold Dynamic Yield to Mastercard in 2021 while continuing to use and expand the technology across its digital customer experiences.
The current effort goes considerably further because McDonald’s is consolidating systems that historically operated across different markets and functions. Instead of treating mobile ordering, loyalty, pricing and restaurant technology as isolated digital projects, the company is building common platforms intended to operate across the enterprise. The resulting architecture should make it easier to deploy a successful application in multiple markets without repeatedly rebuilding the underlying technology.
A global partnership with Google Cloud announced in 2023 provides another part of the infrastructure. McDonald’s said it would use Google Cloud hardware, data and AI technologies across thousands of restaurants and deploy Google Distributed Cloud capabilities at the restaurant level. The companies also established a dedicated team to work on generative AI applications for restaurant employees and customers.
McDonald’s was already talking at the time about connecting millions of data points across its digital ecosystem so that models could improve as additional information became available. The company also began moving toward a common operating system supporting customer and restaurant platforms, including mobile ordering, loyalty and kiosks. The global data lake described by Kempczinski represents the next stage of that consolidation.
Customer personalization is only one possible use. McDonald’s has deployed AI and digital technologies in restaurant operations, including AI-powered accuracy scales that compare the expected and actual weight of outgoing orders and alert employees when an item may be missing. The company said last year that the technology had been deployed in thousands of restaurants across approximately a dozen markets.
The same technology initiative includes Ready on Arrival, which uses geofencing to tell a restaurant when a mobile-order customer is approaching so employees can begin preparing the order before the customer reaches the restaurant. McDonald’s has said the system can reduce customer wait times by more than 50 percent in participating locations. Combining identified customer demand with restaurant operating data creates opportunities to coordinate marketing, order preparation and service rather than optimizing each independently.
A customer receiving a personalized afternoon offer, for example, can generate information that affects more than the marketing department. If enough customers respond, the resulting demand can influence kitchen preparation, staffing, inventory requirements and drive-thru volume. A system capable of recognizing those relationships can potentially help a restaurant anticipate the operational consequences of a successful promotion instead of reacting after orders begin arriving.
McDonald’s has not yet detailed exactly which new applications will be built on the global data lake. Kempczinski said the company plans to provide more information at its Investor Day in Chicago on September 23. Until then, the company’s comments point toward a platform that brings customer personalization and restaurant operations into a more unified technology environment.
McDonald’s is not alone in pursuing that model. Starbucks has spent years building one of the restaurant industry’s most valuable loyalty ecosystems and said at its January 2026 Investor Day that Starbucks Rewards generated nearly 60 percent of U.S. company-operated revenue in fiscal 2025. The company revamped Rewards this year with Green, Gold and Reserve tiers intended to increase personalization and engagement while also expanding its use of AI in areas such as scheduling and supply-chain management.
Starbucks offers a useful comparison because loyalty has become deeply embedded in the economics of the business rather than functioning simply as a discount program. When close to 60 percent of U.S. company-operated revenue is tied to Rewards members, relatively small changes in member frequency, retention or spending can materially affect overall sales. The company said at Investor Day that even modest increases in member engagement could produce significant incremental revenue.
Yum! Brands is building its own version of an integrated restaurant technology platform through Byte by Yum!. The proprietary platform combines mobile and web ordering, point of sale, kitchen technology, delivery optimization, menus, inventory, labor management and employee tools across brands including Taco Bell and KFC. Yum said when it introduced Byte that its U.S. brands were processing more than 300 million digital transactions annually through elements of the platform and that at least one Byte product was already operating in 25,000 restaurants globally.
Yum has since expanded AI deeper into restaurant operations. Its Crave AI technology can recommend inventory orders before managers recognize that stock is running low, while Byte Coach uses information such as forecasts and customer reviews to tailor operating routines. Yum reported late last year that its digital mix had reached a record 60 percent in the third quarter and that Byte Coach was operating across nearly 30,000 KFC and Pizza Hut restaurants.
The competitive advantage sought by McDonald’s, Starbucks and Yum is increasingly rooted in first-party data. Traditional restaurant advertising often relies on broad demographic assumptions or third-party audience information, while loyalty platforms identify actual customers and connect marketing activity with purchases. A restaurant company that knows which customer received an offer and whether that person subsequently bought a meal has a much stronger feedback loop for training predictive models.
McDonald’s has an unusual advantage because of the size and geographic breadth of its customer base. Nearly 220 million active loyalty users across 70 markets create opportunities to identify patterns that would be difficult for smaller restaurant companies to observe. The company can also test programs across countries, menu categories and customer segments and potentially transfer successful approaches across the system.
Scale alone does not guarantee useful AI. Customer preferences vary substantially between countries and even between neighborhoods, while promotions that increase transactions in one market may perform differently in another. Models also depend on accurate inputs, consistent identifiers and governance rules that determine how information can be combined and used.
Centralizing data also raises privacy and security questions that will become more prominent as restaurant companies expand AI-driven personalization. McDonald’s says the consolidation of systems is intended partly to improve security and stability, and its privacy policies provide customers with rights and choices that vary according to jurisdiction. A larger, more connected repository nevertheless makes governance, access controls and transparency increasingly consequential as more customer information becomes available for analytics and model development.
Those questions received additional attention this week when WIRED reported on the data returned to one California McDonald’s customer after he exercised his right to request access to his personal information. The resulting file included extensive transaction history along with algorithmic estimates involving future visits, expected spending, product preferences and customer behavior. McDonald’s told WIRED that it takes privacy and security seriously and uses information such as past purchases to provide more relevant deals, offers and messages while giving customers privacy choices.
The episode shows how sophisticated restaurant loyalty programs have become largely outside public view. What appears to customers as an app for earning points can also serve as an identity layer connecting transactions over months or years and generating predictions about future behavior. AI gives restaurant companies the ability to analyze those histories at far greater scale and translate the results into increasingly individualized decisions.
For restaurant operators outside the largest global brands, competing on raw data volume is unrealistic. Few restaurant companies will ever have hundreds of millions of identified customers or the resources to develop a worldwide data infrastructure comparable to McDonald’s. Cloud platforms, customer data platforms, loyalty vendors and restaurant technology providers can nevertheless give smaller chains access to many of the same techniques without requiring them to build the underlying AI infrastructure themselves.
The larger shift is from loyalty programs designed primarily to reward transactions toward customer platforms designed to understand and influence future ones. Points and free products remain useful because they give customers a reason to identify themselves when they order. The resulting data can become considerably more valuable to the restaurant company than the loyalty mechanism that collected it.
McDonald’s second-quarter experience provides an unusually direct example. When the company reduced digital offers, visits from some of its most loyal customers weakened enough for management to identify the change as a major contributor to the quarter’s traffic shortfall. McDonald’s is now responding with more personalized digital offers, supported by a technology infrastructure designed to know more about which customers should receive them.
The global data lake gives McDonald’s the technical foundation to take that process much further. Marketing, pricing, loyalty and restaurant operations can increasingly be informed by common data rather than separate systems, while AI can search for patterns across a customer base approaching a quarter-billion active users. McDonald’s has not yet revealed the full set of applications it plans to deploy, but its September Investor Day should provide a clearer picture of how the company intends to convert that data advantage into restaurant traffic, operating efficiency and sales.
The restaurant industry has spent much of the past decade building digital ordering and loyalty programs. The next phase will be determined by what companies can do with the information those systems have accumulated. McDonald’s is preparing for that phase with a customer and operational data foundation few restaurant companies can match.
