AI for Restaurants: 5 Practical Ways to Increase Profit and Reduce Costs

How artificial intelligence helps restaurants and cafés speed up operations, save resources, and improve customer service. 5 areas, real cases, and tools.

People who don’t talk about AI today are few and far between. It seems there is no field that artificial intelligence hasn’t reached with its “neural tentacles.” But the trouble is, what theorists say doesn’t always match real-life practice. Let’s take food service and HoReCa.

If we believe everything that’s being said, voice assistants should already be taking orders, robots should be cooking the food, and drones should be delivering it. In reality, much of what’s being described is available only to a narrow group of QSRs with huge budgets for experimentation.

In practice, there is a noticeable gap in perception between experts and venue owners. Both see the potential of AI, but the latter often don’t understand how to integrate it into real processes.

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• Limited knowledge and understanding: many don’t realize what exactly AI can bring and how to implement it.
• Resources: a shortage of people, money, and technical infrastructure.
• Resistance to change: fear of losing control, concern about the role of humans.
• Desire to “preserve the human factor”: many refuse to blur the role of staff.

Today we — Natalia Sokolova, Head of Business Development, and Polina Korotkaya, an expert in AI usage, from the dev.family team, came to explain how professionals in foodservice and HoReCa can already start using AI in their work. Below are five key areas where AI helps restaurants increase profits and reduce costs:

• Marketing and promotion
• Menu and kitchen
• Analytics and forecasting
• Process automation and customer loyalty
• Hiring and training staff

SMM manager, marketer, Reels maker — there is a whole roster of specialists focusing on social media content. But for many venues, that’s a luxury. And not running your Instagram nowadays means burying yourself, loyal customers, and hopes for crowds and sold-out displays.

• Generate post topics, interesting facts, ideas for contests or promotions.
• Write texts for the website and social media: dish descriptions, special offers, reviews, events.
• Create content plans — from a publication calendar to a promo schedule.
• Take into account your venue’s tone of voice so texts are lively and recognizable.
• Translate content into different languages.

The result directly depends on your request (prompt). Two ways to work:

• Assign AI a “role” — for example, marketer, SMM specialist, or copywriter. Then the answers will be more strategic and detailed.
• Or simply formulate the task directly — if you need a quick result without context.

Example prompt for a content plan:

• ChatGPT — a basic universal tool for generating ideas and content. (Complexity: ⭐️ 1/5)
• HIX.AI — like a copywriter: articles, captions, hashtags, descriptions for social media. (Complexity: ⭐️ 1/5)
• Copy.ai — selects persuasive wording considering tone of voice and SEO. (Complexity: ⭐️⭐️⭐️ 3/5)
• PepperContent.io — generation and analysis of content aligned to marketing strategy. (Complexity: ⭐️⭐️⭐️⭐️ 4/5)
• Jasper — oriented toward branding and visual content. (Complexity: ⭐️⭐️⭐️ 3/5)
• Rytr — a good option for small businesses. (Complexity: ⭐️⭐️ 2/5)
• Neuroflash — works in different languages. (Complexity: ⭐️⭐️⭐️ 3/5)
• Anyword — analyzes text and predicts how it will perform with the audience. (Complexity: ⭐️⭐️ 2/5)
• Writesonic — SEO optimization of texts for search. (Complexity: ⭐️⭐️ 2/5)
• Article Forge — quick creation of articles by keywords. (Complexity: ⭐️ 1/5)
• Writer.com — advanced corporate scenarios and data security. (Complexity: ⭐️⭐️⭐️⭐️ 4/5)

If you don’t have time to study new platforms, you can simply connect a Telegram bot based on ChatGPT. Such bots can not only write texts, but also:

• generate images,
• follow links,
• provide quick answers based on prompts.

The difficulty level is minimal: ⭐️ 1/5. Suitable for those who want to start “here and now”.

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A family-format restaurant faced a classic problem: — the Instagram account was updated once a month, — reach was falling, — guest engagement had almost disappeared.

Solution: in one evening, with the help of ChatGPT the team:

• compiled a 2-month content plan,
• received ready-to-use texts and rubrics,
• added the venue’s tone of voice,
• exported the plan to Google Sheets.

Time: 40 minutes Result: a threefold increase in reach and more bookings via social media.

• It’s better to write prompts in English — the model understands them faster and more accurately.
• Use roles (“You are a marketer”, “You are a copywriter”) for higher-quality answers.
• Save finished prompts — this speeds up the process in the future.
• Add the brand’s tone of voice (family venue, trendy art space, grunge bar) — the texts will be livelier and closer to the audience.

Content is not just posts for likes. It has long been a way of communicating with the audience, obtaining feedback, creating and motivating user-generated content, forming a loyal audience that will always come back and forgive any glitches or unplanned blackouts.

Updating the menu is always a pain:

• seasonal products quickly become more expensive or disappear,
• ideas repeat from year to year and from restaurant to restaurant: pumpkin, chanterelles, zucchini, smelt — each region has its own “quirks”,
• experiments with new dishes require purchases, time, and people,
• the final result is not always liked by guests; for example, pizzas with sprats, “shuba” (herring under a fur coat), or “Olivier” did not catch on in the “Pizza Fox” chain.

AI allows you to test ideas before you buy anything or launch production. It helps not just to “invent”, but to make informed decisions. You can always first survey your audience on social media to see whether they would like a new dish. Whether it makes sense to bring back an old one. Or find out what ideas “neighbors” had.

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• Generate dish ideas under your conditions (for example: seasonal, vegetarian, with a specific ingredient).
• Calculate calories and macronutrients (even approximately — already useful at the start).
• Create photorealistic images of dishes for menus or social media. Some aggregators are already using generated content (labeled “made by AI”).
• Analyze the popularity of items and suggest improvements.

Suppose you have a vegetarian restaurant, and you want to launch a seasonal menu with pumpkin as the main ingredient.

Prompt for ChatGPT:

In a few seconds you will receive a list of 10 dishes, for example:

• pumpkin soup with coconut milk,
• salad with roasted pumpkin and feta,
• casserole with pumpkin and quinoa.

Next request:

📍Result: approximate calories and macronutrients for each dish. This helps with cost planning, adapting to guests’ dietary requests, and presenting information clearly on the menu.

Today AI can create images that are hard to distinguish from real photos. For example, Midjourney allows you to:

• quickly get visuals for new dishes,
• maintain a consistent menu style,
• save on photoshoots.

Example prompt for Midjourney:

📍 As a result — a high-quality image ready to be placed in the menu or on the website.

Which AI cases are well known today?

• Tanuki used Midjourney for an ad campaign, placing AI-generated visuals on billboards in several Russian cities.
• Heinz ran a campaign showing that even without mentioning the brand, a neural network draws a ketchup bottle similar to Heinz — the brand became synonymous with the product.
• Musso & Frank Restaurant, a historic, traditional restaurant, began introducing AI-generated visuals into the menu (stylized dish visualizations and digital menus created through platforms like ReelMind.ai).
• Nutella launched the Nutella Unica project: 7 million jars with unique designs created by AI — and all were sold.

• Write prompts in English — this improves generation accuracy.
• Specify the shooting angle, style, and mood (top view, warm light, minimalism, etc.).
• Align all images to a single style — this creates a recognizable visual language.

You can combine generations with real photos — this reduces costs and increases quality.

We would like to believe that in the restaurant business, as in any other, decisions are made based on numbers. But the reality is that people usually rely on their (or others’) experience, intuition, or at best competitor analysis. Nevertheless, even with minimal AI skills, you can connect simple analytics or build some charts/reports on which decisions about new items, staff, etc. will be made.

We have already explained how AI helps collect and analyze data in different business scenarios. Now let’s talk about foodservice.

• Analyze order data and identify popular and unpopular dishes.
• Track demand dynamics by season and day of the week.
• Forecast revenue by categories and menu items.
• Suggest which dishes to remove and which to promote.
• Evaluate the effectiveness of promotions and marketing campaigns.
• Recommend optimal adjustments based on data.

In one franchise network, sales reports were compiled over several days. The same item had different names and IDs. For example: “country-style fries large” in one system and “country-style fries XL” in another. As a result, a person spent three days manually consolidating everything into one file.

We built a drag-and-drop interface for mapping, automatic data collection every 5 minutes, connected a data visualization system, and simple AI for analytics.

Now statistics are in real time, and any report is built in a couple of clicks.

Another example: expense accounting

Previously, employees spent hours retyping data from receipts and invoices into Excel. We built a service: you upload a photo or PDF, the system itself, using simple AI, recognizes all items and enters them into a table. As a result, the P&L is visible immediately: where profit is, where expenses are, which items “eat” the money.

AI processes historical data — orders, average checks, staff load, seasonal fluctuations, weather factors — and builds a demand model using machine learning. Based on it, the restaurant receives clear scenarios:

• how many visitors to expect,
• which dishes will sell better,
• which promotions will have real effect.

Instead of intuitive decisions, you get a planning tool.

• Purchases become more accurate, costs go down.
• Margins grow due to assortment optimization.
• Waste and product losses decrease.
• Promotions run at the right time and bring profit.

Management becomes predictable rather than reactive.

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At dev.family we implement such analytical solutions for foodtech projects, helping restaurants make decisions based on data, not intuition. Want the same?

There probably aren’t many businesses with turnover like in hospitality. First, depending on the region, there is seasonality. Second, many see work as a waiter, bartender, or kitchen assistant as a side job — few plan a career here. But few think about how many resources are spent on training each new team member.

Under such conditions, traditional HR processes become a bottleneck. AI helps remove part of this load and make HR systematic.

• Automates initial candidate screening.
• Analyzes resumes and highlights suitable employees by set criteria.
• Conducts initial interviews via chatbots.
• Personalizes training and onboarding.
• Helps create schedules and manage team workload.

This doesn’t replace HR and managers — it frees them from routine tasks and lets them focus on key decisions.

At the hiring stage, AI processes the flow of resumes, filters out unsuitable applications, and forms a shortlist of candidates. Next, a chatbot can conduct a primary interview — ask standard questions, record answers, and pass them to the manager.

After hiring, the system helps structure training:

• identifies topics important for a specific employee,
• provides materials and instructions via chat,
• tracks progress.

For shift management and workload, AI analyzes schedules, the booking calendar, and footfall forecasts, suggesting optimal staff allocation.

• Hiring time is reduced.
• The accuracy of personnel selection increases.
• Newcomers adapt to service standards faster.
• Managers spend less time on routine.

A small café network connected a chatbot for initial interviews and basic staff training. Hiring time decreased from 10 to 4 days, manager workload dropped, and service quality stabilized: newcomers mastered standards faster because they received all the necessary information in a convenient format.

• Leena AI — chatbot for interviews and candidate interaction.
• Manatal, Vervoe — automated resume screening and initial selection.
• Reclaim, Quinyx — schedule planning and workload distribution.
• Visier — people analytics and forecasting workforce needs.

Book a short session with our team to learn how to use existing solutions and save on hiring

Max B. CEO

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There are many repetitive processes in the restaurant business: taking orders, answering typical questions, confirmations, reservations. These tasks don’t require human creativity, but they take time. Moreover, when a human handles them, the risk of errors increases significantly.

For example, when we automated table reservations at the largest restaurant-brewery in the CIS, Druzya, we increased customer loyalty and reduced the risk of errors and queues. But that case is almost 10 years old.

Restaurant and brewery Druzya

We automated the work flows of place reservation and kitchen load control

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Today, AI can take on many roles. It automates these operations, frees the team, and improves service quality without increasing headcount.

• Automates online orders and reservations.
• Handles common guest queries via chatbots.
• Personalizes offers based on order history.
• Manages newsletters and promotions at the right time.
• Reduces response time to customer requests.

On the front-end — chatbots that take orders, suggest dishes, help choose options, and inform about promotions. They can answer standard questions: business hours, address, parking, dish availability.

On the back-end — algorithms that analyze data on orders and customer behavior. Based on this, the system forms personalized offers and reaches out at the right moment.

For example, if a guest often orders pasta on Friday evening, the system can send them an offer in advance with a new seasonal dish or a discount on their favorite item. This increases the likelihood of a repeat visit and raises the average check.

• Reduced workload on staff.
• Shorter response times and queues.
• Higher accuracy and speed of service.
• More repeat orders due to personalization.
• A more predictable operating model.

A small restaurant launched a chatbot for online orders and integrated a system of personalized newsletters. In a month, the number of repeat orders grew by 35%, and the response time to customer requests was almost halved. The staff got the opportunity to focus on in-house service rather than messaging.

• Chatbots based on Telegram and similar platforms for automating orders and responses.
• CRM solutions with built-in AI modules for personalized communications.
• Demand forecasting systems for planning promotions and workload.

Process automation increases business resilience: costs are reduced, dependence on the human factor decreases, service quality improves. At the same time, the customer receives faster, more accurate, and more personalized service, while the team gains time for tasks where human contact matters.

If you want to understand which processes can be automated in your business — feel free to request a consultation

Max B. CEO

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Growth trend According to industry reports, by 2026 80% of venues will use generative AI or their own AI solutions in daily operations.

In 2025, Papa John’s announced an expanded partnership with Google Cloud to integrate AI into the ordering system. They plan personalized push notifications, chatbots, behavior-based offers, and optimization of inventory and delivery routes. 

Two directions:

• FreshAI — a drive-thru voice ordering system (with Google Cloud)
• Supply chain project with Palantir — procurement optimization, demand forecasting, logistics.

A platform used by Applebee’s, Chili’s, Outback, Denny’s, and others, which includes:

• voice AI assistant for taking orders,
• ordering and payment via tablets at tables.

In a ZS study, five large QSR cases are described where Max.AI:

• delivers targeted menu recommendations increasing average check,
• improves customer experience,
• supports omnichannel interactions,
• manages marketing and campaigns in real time.

A new restaurant concept from the founder of Chipotle, built on robots and AI:

• no printed menu — ordering is online, food is picked up from lockers,
• part of the processes are automated, there are fewer people, but they are paid more,
• the concept is already launching in Manhattan with plans to license the technology.

Despite technical limitations in Cuba, the Doña Alicia restaurant implemented digital menus, voice assistants, and a “robot waiter” that delivers food to tables.

It’s clear these are different budgets and scales. But in this article I tried to describe how even the smallest restaurant, for the price of a paid AI subscription, can solve a huge number of tasks today.

The dev.family team helps restaurants and foodtech projects implement AI solutions without complex setups and costly experiments:

• process audit and identifying automation zones,
• selecting and implementing tools,
• configuring scenarios for marketing, analytics, and operational work.

If you want to understand how AI can improve efficiency in your particular restaurant, you can start with a consultation or a pilot project. This will deliver clear results — without extra risks and without abstract talk about “the future.”