Внедрение ИИ в сфере услуг: тренды
Global companies and Russian firms continue to actively introduce AI into the service industries. According to McKinsey, 88% of companies used AI in at least one business function in 2025, although scaling remains a challenge.. In Russia, by 2025-2026, approximately 35-40% of companies use chatbots and voice assistants in business.. According to a study by Yakov and Partners, 71% of Russian companies already use generative AI in at least one function (an increase of 17 percentage points since 2024). In general, there is an "AI boom" in both the world and Russia: automation systems and intelligent services are expanding the reach of industries, and large corporations are rebuilding processes around AI.
AI is most often used where routine tasks are well formalized. In the banking and insurance sectors, AI is already automating customer scoring, risk calculation, anti-fraud, and processing of applications and appeals.. In logistics, AI is used for intelligent route planning, demand forecasting, and inventory management.. In tourism and HoReCa, AI is being implemented to personalize travel, provide round-the-clock customer support and dynamic pricing (more than half of Western tour operators have already integrated AI and are seeing revenue and loyalty growthIn retail and e‑commerce, recommender systems (RecSys) and behavior analytics can significantly increase sales. For example, in Russian retail, the use of ML referrers raises the average receipt by 15-20%. Adaptive platforms and virtual assistants are developing in education, and medical decision support systems. In all these areas, there is a trend towards personalization of services and the transfer of routine operations under the control of AI.
Finance and insurance.AI application leaders: more than half of banks have already implemented AI solutions. AI is used for risk management, transaction processing, chatbots, data analysis, and even automation of 80% of standardized operations (loan applications, accounting, claims).
Logistics.Active digitalization: AI routing based on traffic and weather reduces costs by 15-20%. Robots and drones in warehouses and delivery are already being implemented by Yandex, Russian Post and other companies..
Tourism and HoReCa.AI creates personalized routes and experiences, and chatbots serve up to 50% of customer requests around the clock. By September 2025, 52% of Western tour operators were actively using AI, recording an increase in average receipts and loyalty. Smart hotel rooms (controlled by voice/app) are already normal in the USA and Europe.
Education.Universities include AI in the educational process: for example, in 2024, the Higher School of Economics conducted an experiment on using GPT models to prepare graduation papers, freeing up students' time for creative tasks.. Adaptive learning and automation of administrative tasks are expected to expand in the future.
Medicine.Patient confidence is growing: 58% of Russians positively assess the prospects of AI in medicine. Orders are growing: the AI market in healthcare – from digital assistants to expert control systems – amounted to 12 billion rubles in 2024 and will grow 6 times by 2030.. AI helps to speed up image analysis, predict illnesses, and collect patient feedback.
The financial sector:AI solutions automate scoring, analytics, and routine operations – for example, banks save hundreds of thousands of hours by implementing internal chatbots.. The secret of successful organizations is process restructuring: companies are moving to "AI-native" architectures and multi-cloud systems (cloud+local data centers+edge).
Areas with high scaling potential for AI solutions
In the coming years, the largest growth rate will be in those service industries where AI can significantly improve efficiency and quality. Let's list the main ones:
Financial services and insurance.High potential: a significant reduction in application processing time and errors has already been proven. Big banks are investing in generative assistants and intelligent systems (for example, Sovcombank's Owl).
Retail and e‑commerce.
Telecommunications and mass media.Telephony and digital services use AI agents to support users, while media uses automatic content generation and demand analytics. According to experts, these industries are the leaders in terms of AI maturity today..
Logistics and transportation.Remote work, a shortage of drivers, and serious investments in infrastructure make logistics a natural field for AI. Intelligent routing, demand forecasts, and robotic warehouses allow for dramatically faster delivery..
Educational services.
Medicine and pharmacy.Diagnosis using AI (image analysis, "digital pathologist") speeds up diagnosis (5 times faster when gastritis is detected). Telemedicine and chatbot patient support services will continue to grow, especially as the regulatory framework improves.
HoReCa (hotels, restaurants).Personalized recommendations for guests, smart rooms, dynamic pricing – all this is still not everywhere, but it is being implemented at an accelerated pace. Thus, the introduction of dynamic pricing in the Courtyard network led to an 18% increase in revenue.%. Service automation (applications, chatbots) relieves the burden on staff and increases customer loyalty.
Healthcare:
Artificial intelligence helps doctors make diagnoses faster (a digital pathologist speeds up image analysis by 5 times), personalize treatment and lead a "smart" assistant, freeing up time for the doctor. High public confidence (58% of Russians have a positive view of AI in medicine) and the clinics' commitment to digitalization create significant growth potential.
Areas with limited AI adoption and causes
AI is not being implemented quickly in all areas. Among those that are traditionally conservative or difficult to access for digitalization are:
Small business and local services.
Healthcare and social services.Despite the potential, the introduction of AI in clinics is constrained by strict regulations and the need for a medical license. For example, the new rules on telemedicine (from 2025) partially limited the remote practice of a doctor.. High standards of patient data security and confidentiality are also required.
The education sector.
Creative services and art.Here, the person remains the key: many people note that creating ideas is still better for a person, not a model.. For example, translators, lawyers, and artists look at AI more as a tool, but are not yet ready to fully entrust it with creative solutions or controversial legal cases.
Hotels and hospitality.
The main limitations are related to data quality, regulatory barriers, and the "labor intensity" of the transition: in many areas, large investments and process reorganization are required, and the profitability of projects is poorly proven for small and medium-sized businesses.
The impact of macro factors on the implementation of AI
The development of AI services is influenced by a combination of regulatory, economic, and social factors.:
Regulation.A national AI strategy is being formed in Russia, but detailed standards are still lagging behind the pace of technology. In 2025, new telemedicine regulations came into force, limiting some aspects of online consultations.. In general, the business expects a legal "AI boom" with unified certification of models and requirements for explainability. The EU is preparing its "AI Act" with strict standards, which creates requirements for export-oriented services. The legislation on personal data and cybersecurity (GDPR and its Russian counterparts) also imposes restrictions on the processing of large amounts of user data for AI training.
Infrastructure.AI scaling depends on the availability of computing power and data. According to Deloitte, companies have to switch to hybrid architectures (cloud services + proprietary data centers + edge). This approach makes it possible to scale "computational dreams" — large language models and agent—based systems - at reasonable cost. Russia is striving to create its own AI platforms (Yandex.GPT, Gigachat, etc.) and expand data centers, but so far lagging behind the world leaders. The growth of the Internet of Things (IoT) and 5G is also expanding opportunities: smart devices will generate a lot of data to train recognition and prediction systems in real time.
The labor market.Simultaneously with automating tasks, AI is changing the demand for skills. On the one hand, the service sector risks losing a number of typical professions (call center operators, routine administrators, tour operators on standard routesOn the other hand, new professions are being formed: "AI analyst", "prompt systems engineer", "AI travel designer" (as noted in the travel industry). The new economy values specialists who can work with data and machine learning systems. Companies are starting to invest in internal AI labs and educational programs (for example, universities are conducting advanced training programs for AI teachers).
Consumer behavior.The emergence of mass AI services (chatbots, content generators) is changing customer expectations. More and more people are ready to entrust the planning of routine tasks to artificial intelligence: in Russia, 35% of tourists are already considering a trip fully planned by AI. Satisfied users of common "smart" interfaces (for example, navigators and voice assistants on smartphones) perceive AI in other services faster. In addition, the pandemic has reinforced the trend towards online services: users demand instant answers and personalized recommendations 24/7. However, negative experiences (AI errors, data privacy) can undermine trust. Sociologists are already noting an increase in the technological sophistication of Russians: 90% of patients who have undergone a telemedicine consultation have been satisfied with this format.. At the same time, the services take into account different generational preferences: young people and millennials are more willing to use AI applications, while the older generation is more conservative.
Cases of AI implementation in services in 2025-2026
SPIEF 2025 (St. Petersburg International Economic Forum).Especially for the forum, the organizers have implemented a voice AI assistant. During the event, it automatically processed about 50% of incoming calls to the information center, reducing the workload of operators by half.. This made it possible to answer questions from participants around the clock without expanding the staff.
Sovcombank (“Owl").One of the largest Russian banks has created an internal chatbot "Owl" for employees. The system based on modern LLMS responds to thousands of internal queries (on salary, products, CRM). According to the Bank's estimates, Sova saves ~310,000 working hours per year (equivalent to 155 employees) by optimizing staff training and support.. This is a real example of how AI allows a large service to handle personnel and operational tasks without massive staff growth.
Vkusville.An internal AI hackathon was held in the Russian retail network, which resulted in the launch of 26 AI-based projects in 1.5 months.. The innovations concerned automation of sales analytics, inventory management and customer services. Such an internal "accelerator" has shown that even in the traditional service business, AI solutions can be quickly generated and efficiency can be measurably increased (for example, by improving loyalty rates and the average check).
Tourism and HoReCa.All over the world, hotel chains and travel services are implementing AI functions. Many Western hotels have smart rooms controlled by voice and apps, and major tour operators are noting an increase in repeat bookings due to AI personalization.. There are fewer local cases in Russia, but there are examples: for example, Azimut has implemented a digital help bot, speeding up the processing of guest requests. In the educational field, children and teenagers have already become hooked on digital sports platforms that combine real and virtual activities, creating a new ecosystem of leisure.
Medicine.The Russian clinic MEDSI, together with researchers, has achieved a sharp growth in the AI medicine market: in 2024, the turnover reached 12 billion rubles, and a sixfold increase is expected by 2030.. One of the developments was the "digital pathologist", an AI system that analyzes biopsies and speeds up the diagnosis of gastritis and other stomach diseases by 5 times.. In telemedicine, AI models help doctors process routine protocols faster (for example, autoanalysis of prescriptions and complaints), and in private clinics, AI chatbots already provide initial recommendations on symptoms, reducing the workload of the registry.
Forecasts and development scenarios for 2026 and beyond
Generative AI and intelligent agents.It is expected that in 2026, text, speech, and image generation technologies will finally disappear from the category of business innovations: AI assistants will become the standard in services, fulfilling complex user requests (for example, personalized consultations). Conventionally, "analytical models" will replace routine BI reports. As Deloitte notes, "organizations are rebuilding around AI," creating "AI-native" structures with constantly updated modules and integrated management.. It is important for companies to focus on the main business task when implementing AI and quickly test solutions ("less perfectionism, more speed").
Infrastructure and architecture.Companies will continue to move away from simple clouds: a hybrid model (cloud + own data centers + edge) will come to the fore. This will reduce costs when "pumping" powerful AI models and provide an instant response to local events. The development of domestic data centers and AI accelerators (GPU/TPU) will be a priority to reduce dependence on foreign suppliers. Distributed computing, containerization of models and services, as well as "AI routers" within companies will ensure AI scaling to thousands of real-time tasks.
Cybersecurity and responsibility.As AI becomes the core of services, vulnerability is also growing: companies are forced to build multi-level defenses (protecting data, models, and applications) and use AI for counter-defense.. There will be standard practices for AI auditing, reducing the "side effects" of generation (hallucinations), and transparent reporting. In 2026, stricter regulations are expected: for example, mandatory ethical AI policies, a blockchain for verifying the originality of data, and "model passports." This will require a new approach to building a service: from design with safety in mind to constant monitoring of the quality of the AI product.
Personalization and hyperpixel service.Services will become much more focused on individual needs: "your personal AI-based concierges" will appear, warning about convenient offers even before the user applies (combining big data and predictive analytics). Augmented reality (AR) and virtual interaction (VR) technologies can be integrated into services (for example: virtual tours and fittings), but first of all, the concierge level of AI bots will dominate. Experts predict that those companies that will be able to "rebuild" the entire service process around the AI + human model will prevail.
Working with data and adapting employees.
In total, by the end of 2026, we will see a profound transformation of services: familiar business processes will give way to "digital twins" and flexible platforms where AI is embedded in everything from sales and marketing to after-sales support. Successful players will build the service as an ecosystem centered on data and continuous improvement of algorithms. Laggers, on the other hand, risk being left without profit, considering AI only a tool for optimizing old processes.