In the constantly evolving world of casual dining, innovation often arrives in platefuls of new menu items or revamps of restaurant décor. But on June 20, 2025, Dine Brands—the parent company of Applebee’s and IHOP—made headlines for a different kind of menu enhancement: artificial intelligence (AI). According to The Wall Street Journal, Dine Brands intends to roll out an AI-powered personalization engine across its Applebee’s and IHOP chains, aiming to tailor recommendations and deals based on individual diner habits or the preferences of similar customers. This move is emblematic of a broader shift in the restaurant industry toward leveraging data and AI to foster loyalty, boost revenue, and streamline operations.

At the heart of Dine Brands’ initiative is a personalization engine that taps into customer data—past orders, reward-program activity, and behavioral patterns—to suggest menu items or promotions that resonate with each diner. IHOP already collects ordering habits through its rewards program, offering a robust dataset to kickstart the AI’s learning process. Justin Skelton, Chief Information Officer at Dine Brands, frames the technology as a dual-purpose tool: enhancing customer loyalty and serving as an upselling mechanism by surfacing items a diner might not have otherwise considered.

This personalization mirrors trends in other sectors—think streaming services or e-commerce platforms—that have conditioned consumers to expect tailored suggestions. By bringing similar recommendation logic to the dining table, Dine Brands hopes to deepen engagement: a diner who frequently orders omelettes at IHOP might be nudged toward a seasonal pancake special; someone who often picks a burger at Applebee’s could see a targeted discount on a side dish or a beverage pairing. The critical factor lies in balancing relevance with surprise: recommendations should feel serendipitous yet meaningful, avoiding the trap of monotony.

While Dine Brands has not publicly disclosed every technical detail, reports indicate that the AI engine leverages generative and recommendation systems—potentially including Amazon’s Q generative AI framework—to interpret natural-language queries from franchisees’ staff and to process transactional data for customer-facing suggestions. Behind the scenes, data scientists and engineers likely feed past transaction logs into machine learning models, clustering diners by preferences, and continually refining predictions as new orders are placed. It’s a feedback loop: each redemption of a personalized deal or acceptance of a recommendation sharpens the system’s accuracy.

The reliance on established cloud-based AI services—such as Google Cloud’s Recommendations AI, which IHOP previously piloted for online ordering in 2023—suggests a hybrid approach: combining out-of-the-box solutions with in-house customizations to fit the nuances of Applebee’s and IHOP menus. HospitalityTech coverage from late 2024 noted that Dine Brands built upon such third-party tools at a MURTEC summit, achieving an impressive cost-to-revenue ratio where every dollar spent on the recommendation engine drove roughly sixty dollars in revenue.

Dine Brands is not stopping at customer recommendations. Skelton confirmed ongoing experiments with AI-powered cameras to detect when tables require cleaning, as well as an AI-driven managerial app designed to streamline daily operations—from inventory checks to staffing suggestions. In practice, a camera-based system could alert staff when plates linger too long, reducing wait times for incoming diners; meanwhile, a manager’s AI assistant might analyze sales patterns, predict peak hours, or flag equipment maintenance needs before they escalate.

These internal tools align with broader industry efforts to marry AI with front-line service. For instance, major chains like McDonald’s and Yum Brands are exploring AI-driven voice ordering or computer-vision solutions for order accuracy at drive-thrus. By offloading routine monitoring tasks to algorithms, restaurants hope to free staff to focus on hospitality—engaging guests, personalizing in-person interactions, and maintaining a comfortable atmosphere. Yet, the adoption of such technology raises questions about labor: will these AI tools complement human roles, or gradually supplant certain positions? Dine Brands seems wary, emphasizing augmentation over replacement, but balancing efficiency gains with workforce considerations remains a delicate act.

Dine Brands’ AI ambitions arrive amidst a restaurant landscape increasingly defined by data-driven decision-making. A Food & Wine analysis from March 2025 highlights how AI is revolutionizing smart menus, dynamic pricing, reservation management, waste reduction, and even menu ideation through flavor-pairing suggestions. Casual-dining players face mounting pressure to enhance digital engagement as diners grow accustomed to frictionless, personalized experiences elsewhere. Loyalty programs, once limited to stamp cards or basic point accrual, now feed sophisticated recommendation engines that can re-engage occasional patrons or entice lapsed customers with precisely timed offers.

Competitors are following suit: fast-food giants test AI chatbots for order-taking, predictive maintenance for kitchen equipment, and sentiment analysis on social-media feedback. The goal is twofold: increase operational resilience and drive incremental sales by presenting the right deal at the right moment. In an era of slim margins and unpredictable foot traffic, AI-driven personalization can tip the scales by boosting check averages and frequency of visits.

As with all AI deployments, the success of personalization hinges on data quality, privacy safeguards, and transparency. Customers may welcome custom deals, but skepticism can arise if recommendations feel invasive or data collection seems opaque. Dine Brands must navigate regulations around data protection, ensuring opt-in clarity for rewards-program analytics and secure handling of personal information. Moreover, AI systems risk reinforcing biases—if the algorithm over-targets certain demographics or misinterprets patterns, it could inadvertently alienate segments of the customer base. Continuous human oversight, robust model evaluation, and clear channels for customer feedback will be essential to maintain trust.

Accuracy is another consideration: faulty recommendations or tech glitches (e.g., misidentifying table status via camera) could frustrate guests or staff. Dine Brands appears to be piloting these tools in controlled environments, gathering performance metrics before broad rollout. Iterative testing, combined with staff training on how to interact with AI suggestions, is crucial to smooth integration.

From a diner’s perspective, personalized suggestions can simplify decision-making in a menu sea that sometimes feels overwhelming. A loyal IHOP fan might appreciate a heads-up on a new breakfast variant aligning with their past preferences; an Applebee’s aficionado might be enticed by a bundle offer tailored to their taste profile. On the flip side, some patrons may balk at perceived “surveillance” of their dining habits or feel wary of algorithmic nudges. Clear communication—“We use anonymized data from our rewards program to bring you deals you’re likely to love”—can help. Equally important is ensuring that human touchpoints remain central: AI should serve as a backstage assistant, not a barrier to genuine staff–guest rapport.

Dine Brands’ embrace of AI personalization and operational tools underscores a pivotal moment: the future of dining may hinge on the seamless interplay of data, algorithms, and authentic hospitality. As consumers grow accustomed to AI-curated experiences in streaming, shopping, and travel, expectations for dining convenience and customization will only heighten. In this landscape, Applebee’s and IHOP risk falling behind without innovation—but overzealous automation could undermine the warmth that defines casual dining.

Ultimately, success will depend on striking the right balance: leveraging AI to anticipate needs and streamline operations, while preserving the spontaneity and human connection intrinsic to a satisfying meal out. As Dine Brands pilots its personalization engine, AI cameras, and manager app, it joins a chorus of industry players testing similar waters. How diners respond, and how well the technology performs in day-to-day restaurant life, will determine whether AI becomes a kitchen-side sous-chef or remains a niche experiment. For now, June 2025 marks the start of this next chapter for Applebee’s, IHOP, and casual dining at large—one where bytes and bites mingle in pursuit of the perfect dining experience.