Top 9 Restaurant Technology Trends & Innovations to Implement in 2025

New technologies help restaurants combat challenges caused by outdated tech, such as the lack of insights into customer behavior, high no-show rates, wastage, understocking, and inefficient resource allocation. They also help enhance customer experience, optimize operations, and amplify marketing efforts. According to the Restaurant Technology Landscape Report 2024 by the National Restaurant Association, 76% of operators that have already implemented restaurant technologies state that innovative solutions bring them advantages over competitors.

Yet, proper restaurant technology integrations require a clear understanding of the domain specifics. In this article, we share insights on the most promising applications of restaurant tech and some practical advice on implementing it. Our findings are supported by 15 years of experience in software development and more than a decade of creating POS software for the U.S. hospitality sector and we have collected the most promising cases to pay attention to.

Let’s get started!

Restaurant technology industry landscape in 2025

The restaurant technology market experienced rapid growth in 2024 – and the trend will continue in 2025.

The growth is due to the increasing need for automation, digitization, and the race for data-based solutions. Technologies like Point of Sale (POS) structures, self-service kiosks, and chatbots are already reshaping the way the restaurant industry works, with point of sale structures being the biggest segment of the restaurant technology market.

At the same time, customers expect enhancements in online ordering, app-based delivery and payment, or even more advanced tech perks: robotic kitchens and delivery by drones. Companies like DoorDash and Uber Eats, which were the first to promise innovative service solutions, prove that the implementation of restaurant technologies pays off – DoorDash finished the quarter with a 20% increase in order volumes.

The restaurant sector joins the race to benefit from analytic and generative AI in parallel with other industries. Solutions that allow data-based insights into customer behavior, predictive analytics, and AI-enhanced order and supply management systems are the most popular.

Gen-AI-based service bots take firm positions in the sphere of customer service. The demand for transparency in meal sourcing requires restaurants to be ready with an array of nutrition facts for customers on demand. AI service bots are an excellent solution for taking over educational activity from restaurant staff.

Yet, quite often, the implementation of a new restaurant technology comes with limitations. The dependence on outdated legacy systems is one of them. These systems are slow to scale and unable to integrate with more modern technology, like AI features. At the same time, they are disconnected, leading to manual errors, inefficient resource allocation, not to mention a lot of routine manual labor.

Updating restaurant tech requires large-scale upfront investment and the right talent to translate the business owner’s vision into the best practices of restaurant technology implementation. Quite often, this requires additional consultation from professional services.

To combat the challenges described and reap the benefits of innovations, the hospitality niche has taken a firm position in tech investment. The restaurant technology market shows steady growth at a GAGR of 16.39%, according to Business Research Insights. The restaurant tech investment market closed the year in a mini-boom, while top providers of restaurant technology grew, despite the slowdown in restaurant revenues, according to a recent review from Restaurant Business.

At the same time, restaurateurs show readiness to invest in different areas of restaurant tech: from 48% planning to implement point-of-sale solutions (kiosks or tablets) to 63% planning to enhance digital marketing efforts.

While the future of restaurant technology is promising, we’ll have a look at the TOP 8 most interesting restaurant tech use cases to implement.

Trend #1. Self-order Kiosks and Other Ordering Systems

The desire to streamline customers’ ordering and payment journeys is one of the most prevalent restaurant technology trends in 2025.

Moreover, self-service solutions belong to the most comfortable tech options for customers. According to a recent report from the National Restaurant Association, 60% of adults say they’d prefer making an order using a tablet at the table, and 65% say they prefer paying the check the same way.

Self-ordering solutions include a range of instances, like self-order kiosks, mobile ordering apps, tableside ordering systems, and automated digital menus.

Self-service kiosks allow customers to browse the entire menu without hustle, receive complete information on the ingredients, or even customize the dishes by choosing the ingredients they love. The development of artificial intelligence makes self-order systems even smarter. For example, such a station can be equipped with a service bot ready to provide a customer with the necessary information.

Tableside ordering systems have the same function, with the difference that customers make their decisions at the table, most often by using specialized tableside tablets.

Interestingly, while previously self-service kiosks were implemented mainly by limited-service restaurants, now they have become a norm industry-wide.

Mobile ordering apps are another example of self-ordering solutions, which offer some extra benefits, as building a mobile app opens new opportunities for data collection and building up loyalty programs.

Automated digital menus are another example of popular restaurant tech. Although they are simple to implement, they provide extended information and frequent updates and simplify the customer journey. 70% of customers say they’d like to have the option to place an order in advance and get their food shortly after they get seated.

As for the indicators of consumer readiness to adopt these technologies, they are quite high. Here’s the percentage of customers preferring different self-service options:

HOW TO IMPLEMENT THIS TREND

Building an automated checkout system depends on the complexity of requirements and the state of the existing POS system and requires several steps:

Step 1. Integrate the new ordering system with the existing POS solution.

It is essential to ensure that orders received from mobile apps, self-service kiosks, or tableside tablets go directly to the kitchen without manual intervention.

Step 2. Implement real-time order tracking

This feature will boost customer engagement and loyalty. Moreover, it will help staff view each order dynamically, manage orders more efficiently, and track the order’s progress.

Step 3. Prepare kitchen workflow for mobile orders

The implementation of special restaurant technology tools, like kitchen screens and alert systems, is necessary for flawless integration with self-ordering systems. Software that can adjust and optimize workflow according to real-time demand is also required.

Step 4. Train the staff

New ways of operation will require special workflows. The staff must manage communications with the customers directly and through the system, promptly respond to cancellations and modifications, and deal with atypical situations effectively.

Trend #2. AI-powered Chatbots

Restaurant chatbots are a case of technology replicating human-to-human interactions. Chatbots allow customers to ask questions, make orders, or make table reservations by typing or speaking without interacting with restaurant staff.

We are familiar with chatbots from Pizza Hut, Taco Bell, and KFC as examples. However, it is worth noting that those early chatbots were rule-based, matching keywords with predefined answers.

Modern-era AI chatbots are more complex. They are able to understand the context of the conversation, draw information from a customer’s previous orders, drive conclusions on tastes, and make personalized suggestions.

For restaurant owners, this translates into numerous benefits. For example, chatbots provide better customer service, as customers receive chat consultations about food ingredients without time limitations. They may be programmed to upsell and promote special deals, collect information on customer satisfaction, and other analytics for personalized marketing.

It is also worth noting that this technology has high customer acceptance: 49% of millennials (33% of all adults) say they are ready to order food by speaking to a virtual assistant; 45% would like to order food by using a voice-enabled platform, like Google Home or Alexa. Customers love this option because it allows them to make food or table reservations while carrying out their daily tasks, and we may presume that this option will continue to be prevalent in the future of restaurant technology.

HOW TO IMPLEMENT THIS TECHNOLOGY

AI-powered chatbots can be voice or text-based, or both. They are based on generative AI and retrieval augmented generation (RAG), voice recognition or speech-to-text and text-to-speech, as well as analytic AI.

The preferred level of bot sophistication defines the technology you need for cases where generative AI and contextual analysis are unnecessary. There are numerous bot-building tools and platforms.

More complex options of chatbot development, like chatbots able to sustain meaningful conversations, will require a platform offering robust solutions for conversational AI. In general, the future journey will take the following steps:

1. Existing system checkup

To check whether an existing system (CRM, ERP) can be integrated with new tools and upgrade the proprietary software if necessary.

2. Product feature choice

A clear understanding of the product’s functionality will influence the choice of the technology and further project development lifecycle, as well as the price. The understanding of actions a chatbot will perform will help to prepare a clear idea of software to develop. Therefore, it is important to think hard about features like making reservations, recommending dishes, answering questions on ingredients, and processing payment on demand.

3. Platform and technology choice

Based on the features selected, AI app developers will decide on the technology choice. Developing the voice interface will require technologies like text-to-speech and speech-to-text. The ability of a bot to reason and sustain a conversion is built on the basis of large language models (LLMs). For a bot to be connected with the restaurant’s database of things like menus, free tables, and purchase history (usually stored in a CRM), retrieval augmented generation (RAG) is used, through which a bot learns business-specific data.

4. Analytics and reporting

An AI bot is a precious source of insights for other restaurant technology solutions, like advanced analytics. To add AI-enhanced analytics and reporting functionality, preparing a clean and structured database on historical orders and transactions is necessary. Based on that, AI software developers will build and train a custom model, able to provide valuable insights into business functioning.

5. Integrations

Ensuring seamless bot integration with the existing systems responsible for reservation, ordering, and payment is necessary. This process will require a lot of validation and testing rounds.

Trend #3. Automated Inventory Management

Automated inventory management presupposes using AI to track and calculate spending on supplies and equipment, predict demand fluctuations, and get better prepared for seasonal peaks and lows, it belongs to the category of must-have restaurant technology integrations.

The features described allow for cost and time saving, reduced food waste, reduced supply-chain issues, or even long wait times. They also give better visibility into the operational chain, allowing for adjustments and approvals, which were not previously apparent.

Automated inventory management modules are based on machine learning models that process historical data on the use and waste of inventory and make exact predictions for the future. Such a system, for example, may predict a seasonal peak in a particular product while calculating its optimal number to satisfy the demand on the one hand but avoid overstocking on the other.

At the same time, automated inventory solutions provide better visibility and real-time tracking of supply levels. For example, one of MobiDev’s clients, BarTrack, uses an IoT-based solution to track and optimize beverage pouring. Smart sensors and scanners allow us to track the keg levels automatically and signal the need for restocking in time. At the same time, they allow for maintaining the optimal temperature for kegged beverages and signals when storage equipment needs maintenance, thus reducing product wastage and extra maintenance time.

HOW TO IMPLEMENT THIS TREND

The implementation of automated inventory management follows a similar path to another AI-based instance of restaurant technology, where data preparations and seamless integrations play a crucial role:

Step 1. Data preparation

It is necessary to prepare clean data on inventory purchases, including dates, prices, and supplier information. It is also essential to organize historical data on sales volumes.

Step 2. Technical equipment

The integration of a new system will require scanners and sensors for the real-time monitoring of supply and inventory levels.

Step 3. Integrations

It is crucial to ensure a frictionless transition from the legacy inventory tracking system to the new one. It is possible that the process will require migration to the cloud, to ensure scalability and uninterrupted operations.

Step 4. Continuous improvement

As the system operates, it will require updates in correspondence with emerging trends and challenges

Trend #4. Restaurant AI Ordering Systems

Busy restaurants sometimes take over 100 calls in an hour during busy hours, making it complicated for staff to take orders quickly and write them down correctly. Missed calls and long wait times may cause lost orders and unsatisfied clients.

AI ordering systems automate the process of ordering by answering simple queries and making orders. Complex questions get automatically directed to qualified person. This way, a restaurant can take as many of the orders as possible.

While AI ordering belongs to emerging restaurant technologies, the benefits are already tangible:

• Increased customer loyalty as people are happy when their orders are taken fast
• Improved order accuracy as the system eliminates mistakes like wrong food orders or mixed up delivery details
• Optimized operations – AI frees personnel from routine calls; they spend more time dealing with issues where human intervention is necessary.

Comprehensive conversations with customers are possible through a range of technologies:

Natural language processing

Technologies like speech-to-text and text-to-speech convert spoken language into text and computer code and vice versa. This way, the system can translate voice queries into a format understandable for a machine so that the computer can process them further.

Conversation AI development

In restaurant technology, conversational AI has to provide a meaningful conversation with a client or, in other words, to sustain a question-answer flow. It also should provide customers with restaurant-specific data, like information on table availability, recommended dishes, and prices. Another task before the AI ordering system is ordering itself: the system has to perform actions on customer requests: make or cancel reservations, process a payment, redeem a discount, etc.

Currently, such a system is most often built with the help of a large language model (LLM), which gives a basis for a bot to ask and answer questions. With the help of a method called retrieval augmented generation (RAG), developers connect an LLM-based bot with a restaurant’s database. This way, the bot gets connected to the restaurant’s CRM to drive information on available tables, prices, etc. Further, AI application developers build software that allows for a bot to make changes in the restaurant’s CRM, like paying for orders.

Machine learning

An AI ordering system can be a precious source of analytics and insights that lay the basis for another AI-based restaurant technology: sales and demand forecasting. Most often, AI analytics tools are based on custom AI models. These are built by AI app developers specifically for a restaurant’s business and trained on the restaurateur’s proprietary data, such as sales history, inventory prices, seasonal discounts, etc.

In another scenario, developers may use foundational models, like GPT, and fine-tune their solutions, as well as train them on the restaurant’s data. An analytic tool integrated into the AI ordering system goes further than providing an owner with real-time insights on sales, it can also autogenerate recommendations to adjust inventory, staffing, etc.

HOW TO IMPLEMENT THIS TREND

To develop a restaurant AI ordering system, it is required to pay attention to the following aspects:

1. Deciding on the product design

Whether online ordering systems will be implemented as a text-based chatbot, automated menu, or a voice-based chatbot. A clear description of features at the beginning of a project will help with the proper technology choice. For example, some LLMs have lower pricing compared to others and if the desired features fit within their capability, the overall project cost can be reduced.

2. Running a check-up of a current CRM, used by a restaurant

The outdated systems may not be able to integrate well with new tools. It can be a huge obstacle, as the bot’s ability to drive information on things like table availability or take actions like payment processing, depends on a seamless integration with the existing database.

3. Preparing data

An analytics and forecasting tool requires clear and structured data on historical sales, inventory levels, promotions and seasonal discounts.

4. Product development and testing

At this stage of product development, it is necessary to pay special attention to allowing customers different privacy options and take extra steps to embed compliance with privacy and security regulations in the product design.

Trend #5 Employee Fraud Detection

Staff in restaurants and bars regularly perform some form of theft, from snacking on French fries to taking home some extra complicated meals at the end of the night. Usually, such minor theft instances are hard to detect, and their influence on business operations seems minor. Yet, the cumulative effect of such behavior is quite tangible, and eliminating it leads to considerable savings.

AI helps spot anomalous behavior or strange stock usage patterns and alerts a business owner to possible employee fraud. One of the examples is detecting the so-called “wagon wheel scheme.” In this scheme, a server takes an item already paid from the order right before closing it. In this way, a customer pays for the order, but because a server changes the receipt after payment, they can pocket the extra money for the item they delete. With AI analytics and inventory tracking, situations like this can be eliminated.

HOW TO IMPLEMENT THIS TREND

Since the technology described will perform analytic and tracking tasks, analytical AI will be used in this scenario. The solution development will take the following stages:

1. Data preparation

To build an analytic mechanism, developers will have to develop and train a custom model based on the restaurateur’s proprietary data. Therefore, a clean and structured database with information on orders and inventory will be needed.

2. Model development and training

At this stage, the model will be developed, validated, and tested. It is worth mentioning that it will be necessary to retrain the model regularly to maintain its precision and quality.

3. Integration with the existing CRM

It is necessary to ensure the flawless integration of the analytics model with the existing CRM. For this, it is required to make sure that the legacy system is updated and flexible enough to take on new integrations.

Trend #6 Predictive Analytics and Demand Forecasting

Demand forecasting is a must-have technology to ensure you are not caught off-guard during rush or peak hours. Restaurants have always been sensitive to seasonal trends, employing traditional logic-based forecasting, like buying more products for pumpkin pies for Thanksgiving. Leveraging technology can significantly simplify this process and enhance its quality by identifying subtle patterns that are traditionally overlooked.

Also, by analyzing historical data and past trends, AI-based demand forecasting allows for better quantitative calculations of supplies needed for specific periods, so that restaurants don’t experience shortages during peaks and eliminate waste during lows.

Another factor to mention is that modern AI tools process information on ongoing things, like weather change, competitor activity, or fashion dynamics. This allows adjusting long-term and short-term forecasts in real time.

HOW TO IMPLEMENT THIS TREND

The creation of a prediction analytics and demand forecasting tool for restaurant businesses will depend on several factors, like data arability, technology choice, and project goal. Although there is no one-size-fits-all procedure in this case, here are some general trends for a better understanding of what to expect:

1. Data preparation

The accuracy of the demand forecasting model will depend significantly on the quality of the data. A restaurant demand forecasting tool will need data on:

• Historical sales: this data helps track which items were sold, when, and by which seller
• Seasonality and holidays: local events, promotional campaigns, and holiday times impact customer flows
• Customer footfall data: checking traffic and reservation data will allow for establishing the demand for reservations on specific dates
• Weather data: historical weather data and forecasts will help to specify whether customers will be more likely to show up or cancel reservations on certain days
• Competitor analysis: include competitor data for sales and promotions that may lure your audience away
• Economic indicators: factors like unemployment and income level in the area will affect visitor flow

2. Technology selection

Often, a single demand forecasting solution may depend on different algorithms. The most common ones are regression models, ensemble models, transformer-based models, gradient boosting, ARIMA/SARIMA, exponential smoothing, and long short-term memory (LSTM). These technologies have proven to be most effective in meeting the demand forecasting needs of the restaurant business.

3. Model training and validation

Model training and validation are done iteratively until the desired result is achieved. To enhance the experience of interaction with predictions, it is recommended that a front-end interface like a dynamic dashboard be developed.

At the same time, it is important to keep in mind that training a model is not a one-time-adventure. A predictive model will require regular retraining rounds to keep it actual and functional.

This is just a superficial overview of how to create a demand forecasting tool for restaurants. For deeper insight, read the success story on how MobiDev implemented an AI-powered demand forecasting analytics feature for SmartTab, a leading POS system that serves 1,000+ venues and chains across the USA.

MobiDev & SmartTab - 10 years of Collaboration for

Developing POS Solution That Revolutionizes Hospitality Management

Trend #7. Advanced POS Systems

Restaurant point-of-sale systems are critical for a successful business, where speed and accuracy become an essential add-on to the consumer experience.

This restaurant technology allows one to track sales, manage tables and orders, run reports, and manage inventory. When united with self-service solutions, POS systems also provide for increased efficiency and speed and order customization.

As AI and machine learning implementations in the hospitality sector are becoming increasingly popular, integrating AI into POS is becoming a popular trend.

MobiDev has stood at the outset of this trend as we entered the niche of advanced POS development back in 2014. Back then, we started cooperating with SmartTab, which needed an innovative POS system for the hospitality industry. With the solutions provided by MobiDev, SmartTabd has grown from a startup to an industry leader with 700+ venues and chains. The SmartTab POS system has grown into a user-friendly ecosystem that includes a POS system, a customer app, and an AI analysis system for demand forecasting.

Besides AI-driven demand forecasting, AI also helps with advanced analytics. Advanced analytics can help single out the most and least selling items, the number of earnings per product, or trends per period. It also provides margins for checking the accuracy of demand forecasts by comparing forecasts and actual sales.

HOW TO IMPLEMENT THIS TREND

A custom POS software development project consists of the following steps:

Step 1. Designing POS architecture

At this step, it is important to decide what type of POS you want to create: desktop, mobile, cloud, self-service kiosk, or several solutions in one.

Step 2. Developing key features

Modern POS systems include inventory, sales, employee, and customer management blocks and analytics, as well as reporting and forecasting tools.

Step 3. Implementing advanced AI features

Suppose you decide to enhance the POS system with AI. In that case, you may want to implement demand and sales forecasting, advanced sales analytics, automated customer verification, intelligent inventory management, and smart recommendations.

Step 4. Updating POS hardware and additional equipment

The central part of the equipment is the display, which can be a desktop, tablet, mobile, or self-service screen. You may also need kitchen displays, physical inventory, scanners, and other equipment.

If you want to learn more details about the POS software development process, you can also read our article: Custom POS Software Development Guide: From Idea to Implementation

Trend #8. Kitchen Automation and Robotics

Robotic kitchen solutions belong to the emerging technologies in restaurants. While expected to bring potential cost-savings, operational efficiencies, and improved customer experiences over time, robotic kitchens have already become a magnet for tech-savvy clientele interested in new impressions. According to the National Restaurant Association, 47% of millennials say they would like to try food prepared by robots, and 58% in the same age category would love to have their food delivered by robots or other automated systems.

Apart from the high-tech touch, kitchen automation can also help by taking over specific tasks like chopping vegetables, frying chicken, grilling burgers, and assembling dishes. For example, Flippy by Misorobotics can cook simple standalone dishes like burgers, chicken wings, and onion rings. It can prepare up to 300 burgers in an hour and is a perfect solution for busy rush hours.

Although currently, implementing robotics requires considerable upfront investment, the cost of this technology is going down, making robots more accessible to businesses of all sizes. The developments in AI and ML promise to enhance reprogrammable robots, able to perform various tasks by following human voice or even gesture commands.

HOW TO IMPLEMENT THIS TREND

Before you decide to implement kitchen automation, it is necessary to check whether your menu profile fits automation. Robots can handle simple foods like pizzas and burgers, but sophisticated dishes are not the best fit for automation.

If you are thinking of building a restaurant robotics and automation solution as a SaaS product, feel free to contact us for AI consulting services that will help you crystallize your idea and build a feasible roadmap for its implementation.

Read Success Story of Collaboration between MobiDev and Refraction AI

Developing a Robot Delivery Solution, which Secured $10.7M in Investments

Trend #9. Omnichannel Integrations

A successful restaurant business requires effective management of various tasks, from supply management to establishing trusting relations with customers. A restaurant management system is a piece of software allowing access to multiple functions from one place. It unites some or all the technologies we’ve discussed, like POS, inventory management software, scheduling tools, and customer relationship management.

While collecting all the integrations in one place, a restaurant owner streamlines the processes, such as managing employee schedules in line with expected demand or updating inventory volumes based on sales. Additionally, these systems enhance order processing by eliminating mistakes and increasing the speed of operations. Information collected during such operations works as fuel for statistics, predictive analytics, personalized marketing efforts, and providing better customer service.

When talking about the finance side, restaurant management systems that integrate accounting software can significantly improve general oversight of spending and revenues. An extra security layer is provided with payment processing solutions. They often get implemented with business intelligence tools, which also provide insights into sales trends.

In other words, such omnichannel solutions provide a holistic view of a restaurant’s performance, which enhances decision-making and strategic planning. Altogether, these solutions lead to increased revenue and a better brand reputation.

How to Adopt Restaurant Technologies

When accessing the technology that can be implemented to enhance business operations, it is necessary to start with careful planning. The following steps will be required:

• Evaluate business needs: it is recommended to start with the most pressing pain points and scale forward. For example, if your business suffers a lot of no-show instances or food waste, sales, and demand forecasting tools will be necessary. Self-service kiosks will be an excellent option for companies suffering from labor shortages.
• Deciding on the technology: this is the stage of discussion with the technology consulting team. At this stage, you’ll choose which technical possibilities can be implemented within your needs and budget.
• Preparing for development: the outdated legacy systems may be unable to integrate with the newer technologies. At this point, enhancing or even rebuilding the existing software tools will be necessary.
• Launch and test: At the software launch stage, it is necessary to validate the product to check whether it stands up to expectations and correct mistakes if needed.

Build or Modernize Your Restaurant Tech Product with MobiDev

At any stage of the restaurant tech product development process, from tech consulting to launch, you need close oversight of the processes and understanding that you are following the best possible scenario that balances expenses and outcomes.

At MobiDev, we’ll comprehensively analyze your business case to offer you the optimal ways to move forward. With our consulting and engineering services, we can meet you at any stage of your journey and provide complex solutions, including innovative technologies like AI, AR, and IoT.

Being in software product development since 2009 and in the restaurant technology market since 2014, we have developed expertise and knowledge to provide sustainable value and results and help you scale based on your needs and desires.