Possible Niches for AI Services in Ukraine: Process Automation in SMB and B2C

Introduction

Small and medium-sized businesses in Ukraine are becoming increasingly interested in artificial intelligence (AI) as a means of automating routine tasks and increasing efficiency. However, there are still few ready-made quality AI solutions on the market, meaning there is significant room for new useful services. Below is a study of potential niches for launching AI services among the Ukrainian audience. The main focus is on automating business processes in the small and medium-sized business (SMB) segment, with an emphasis on industries with low competition (including unconventional areas). Several promising B2C niches are also considered. For each niche, the following are provided: industry/area, specific automated tasks, examples of AI solutions (services), level of competition in Ukraine, and global analogs.

B2B Niches: AI Automation of Business Processes for SMB

1. Agriculture and Agribusiness

Industry Potential: The agro-industrial complex remains one of the least digitized industries, despite its great potential for precision agriculture. Globally, the market for AI solutions in agriculture is rapidly growing – from $1.7 billion in 2023, it is expected to reach $4.7 billion in 2028, according to hub.kyivstar.ua. In Ukraine, large agricultural holdings are implementing AI for crop rotation planning, crop monitoring, yield forecasting, logistics, etc., but small farms still lack affordable products. Competition is currently low: only a few startups like DroneUA (a global integrator of drone solutions) have started applying AI technologies in agriculture and gained global recognition agro-business.com.ua.

Typical Problems: Manual monitoring of fields and crop conditions requires a lot of time and labor. Farmers find it difficult to timely detect plant diseases, optimally plan irrigation and fertilization, and forecast yields. There is a need to automate the analysis of large agricultural datasets (weather conditions, soil status, field images, etc.) for decision-making. Also relevant is the problem of staff shortages due to war and mobilization: there are not enough agronomists and specialists capable of constantly monitoring all processes – AI can partially fill this gap.

Possible AI Solutions: A SaaS platform or chatbot for "smart farming" that integrates with IoT sensors, drones, and satellite data. Such a service can automatically collect data on temperature, soil moisture, precipitation, equipment status, etc., and analyze it using ML algorithms. Based on this, AI will provide the farmer with recommendations: when to water and fertilize plants, how to control pests, and forecast crop ripening. For example, AI can recognize plant diseases from images (from drones or smartphones) and immediately offer solutions – change growing conditions or apply necessary preparations. Another scenario is the analysis of aerial photographs of crops and soil indicators to optimize irrigation and fertilizers. AI can also predict yields and detect anomalies (nitrogen deficiency, signs of drought, etc.) long before they become obvious to humans. A separate niche is animal husbandry: computer vision for counting livestock, detecting sick animals, optimizing diets. For beekeepers – a "smart apiary" with sensors in hives and AI analytics (as implemented in the experimental AmoHive project in Kyiv region) can monitor the condition of bee colonies and suggest to the beekeeper when intervention is needed (according to hub.kyivstar.ua).

Level of Competition in Ukraine: Very low. Most agro-AI solutions are currently implemented by large players for their own needs or offered by foreign companies. There are almost no local SaaS products for small farmers. There are individual startups – for example, the Ukrainian company Feodal created the Feodal FMS system for comprehensive agribusiness management, which automatically collects data on fields, equipment, weather, and identifies inefficiencies in farm operations. Overall, the market shows a noticeable lack of supply, while the demand for increased yields and reduced costs is very high. This is also confirmed by a quote from Mordor Intelligence: "the industry is turning to AI technologies to meet its needs for precision agriculture, improve crop quality, combat pests, and monitor soils." Thus, the space for new AI services in agriculture is enormous.

Global Analogs: Sway AI (USA) – a no-code AI platform for precision agriculture that analyzes aerial crop and soil images and provides advice on optimal irrigation and fertilizers (agrotimes.ua). OneSoil (Switzerland) – a satellite-based field monitoring service with AI analytics for farmers. Plantix – a mobile app based on AI that identifies plant diseases from photos and recommends treatment methods. These solutions demonstrate how AI can automate agricultural processes that previously relied on human experience.

2. Retail and E-commerce

Industry Potential: Retail is one of the most promising areas for AI implementation, as business processes here are data-rich. Large networks are actively experimenting with AI tools in almost all areas: from demand forecasting and inventory management to marketing and customer communications. Small and medium-sized retailers are only beginning this journey, so competition among local AI services is low. There is a niche for solutions adapted to the Ukrainian e-commerce infrastructure (local marketplaces, payments, language, etc.). According to analysts, AI solutions in retail can significantly increase efficiency: optimizing inventory, personalizing offers, and automating marketing can increase sales and reduce operating costs. Ukrainian startups are just starting to explore this niche – a striking example is Lookerz, which was the first in Ukraine to apply AI in fashion retail (according to hub.kyivstar.ua). Therefore, there is room for new players in the market.

Typical Problems: Small retail often faces manual inventory and pricing management, approximate demand forecasting ("by eye"), inefficient marketing (same promotions for all customer segments), and a heavy workload for staff (customer consultations, order processing, etc.). Online stores find it difficult to retain customers without a personalized approach – 70% of users may switch to a competitor if they don't receive relevant product recommendations. SMBs also lack analytics: which products are stagnant, who is the buyer, when is the best time to run discounts, etc. All these are tasks for AI.

Possible AI Solutions: For small retailers, an AI assistant for inventory and pricing management would be useful. For example, a cloud service that integrates with the store's accounting system and forecasts demand based on sales, seasonality, and trends. AI can automatically recommend when and how much product to order to avoid shortages or surpluses, and also suggest optimal prices (dynamic pricing depending on demand and competitor promotions). Another direction is personalization for e-commerce: a product recommendation module "like on Amazon" but adapted for Ukrainian stores. Based on user behavior on the site, AI creates selections of similar or complementary products. For example, the Lookerz service generates ready-made "looks" for online clothing stores – selecting a set of items for a favorite product and showing alternative positions in real time using AI. This increases average check and conversion. Also relevant are AI marketers: a chatbot or SaaS that analyzes sales data and customer segments and automatically launches targeted promotions (mailings, banners) for each segment. AI can generate texts and images for promotional materials for a specific audience (e.g., a promotion for young mothers vs. students) – large retailers are testing this functionality. An AI module for customer service in retail is also possible – a virtual sales consultant on the website or in a messenger, answering questions about product availability, order status, delivery conditions, etc., 24/7. Finally, computer vision can find application in physical stores: cameras with AI can monitor shelf replenishment and signal when an item is out of stock, or analyze checkout queues and optimize staff numbers on the floor.

Level of Competition in Ukraine: Low–moderate. Among large players, many develop AI solutions internally (e.g., Epicenter or Metro implement their own developments for data analysis, content generation, voice assistants, etc.). For small businesses, there are still few specific products. There are BI systems (for example, Ukrainian Datawiz) for sales analytics, but they are mainly used by networks. Personalized recommendations are only gaining popularity – the Lookerz service currently works with large online stores and is practically a pioneer in fashion retail in the local market. This indicates that most SMBs still lack such tools. On the other hand, global platforms like Shopify, Magento, etc., offer basic AI functions (recommender, chatbot) that Ukrainian entrepreneurs can also use. However, these solutions do not always take into account local needs (language, assortment specifics). Therefore, there is room for Ukrainian SaaS with more flexible and localized functionality. Overall, according to the Independent Association of Banks of Ukraine, small and medium-sized businesses are still minimally involved in AI and are rather observing the successes of large companies, but the situation is rapidly changing. Now is the moment when the launch of a new service can secure a leadership position.

Global Analogs: Amazon AI – Amazon's internal tools for demand forecasting, warehouse management, and product recommendations (they have largely become the standard for e-commerce worldwide). Alibaba Cloud ET Retail – a set of AI services for retail (in-store customer analysis via video, intelligent price tags, etc.). Specialized services: Dynamic Yield (now owned by Mastercard) – a personalization platform for e-commerce; Trax – computer vision for shelf analysis in retail. In the fashion segment, Stylitics are globally known, offering AI-stylistics and outfit recommendations similar to the functionality of Ukrainian Lookerz. These examples confirm that even in the saturated retail market, there are niches where AI services are becoming a must-have tool.

3. Logistics and Transport

Industry Potential: The logistics sector (delivery, warehouses, transportation) generates complex supply chains where optimization directly saves money. Large companies actively invest in AI to optimize routes, automate warehouses, analyze customer inquiries, etc. In Ukraine, for example, Nova Poshta reports a number of AI implementation projects – from forecasting optimal courier routes to image recognition and voice bots in the contact center. However, for smaller logistics firms and delivery services, ready-made services are practically nonexistent – many processes still depend on dispatchers and human factors. Competition in the local market for AI solutions is low, as giants ("Nova Poshta", "Ukrposhta", international DHL/Bolt/Uklon) develop AI features in-house, and there are few "off-the-shelf" SaaS products. Meanwhile, demand for efficient logistics is only growing with the development of e-commerce. According to Y Combinator, startups in this area should pay attention to digital logistics solutions and automated deliveries, as the growth of online trade increases demands for delivery speed and accuracy (according to speka.ua).

Typical Problems: For small logistics operators, the main tasks are manually compiling courier routes (not always optimal in terms of distance and time), uneven vehicle load (vehicles drive half-empty or stand idle), and difficulty forecasting peak periods. In warehouses – manual inventory management and order picking, leading to errors and delays. In customer service – managers are overloaded with calls regarding delivery status, parcel tracking, and typical questions (how to fill out a waybill, etc.). Also, safety: driver control (from fatigue to compliance with traffic rules) in small companies is almost not automated. These "bottlenecks" in logistics can be solved with AI.

Possible AI Solutions: A promising service is a platform for optimizing routes and vehicle loading. Input includes a list of delivery (or pickup) addresses for the day, vehicle characteristics, traffic, and other parameters. AI builds optimal routes for each vehicle in seconds, considering traffic jams, distance, and customer time windows. This can reduce mileage and travel time by 20–30%. Similar solutions exist globally, but a Ukrainian product could consider our realities (road conditions, checkpoints during wartime, etc.). Another idea is an AI dispatcher for cargo transportation: automatic selection of a vehicle for an order (by tonnage, location) and calculation of transportation cost based on market data. For warehouses – a "smart warehouse" with increasing e-commerce complexity: a system with computer vision that tracks product placement, and robotic platforms controlled by AI algorithms. In a more accessible form for SMB, this could be a chatbot for a warehouse manager: you can ask it by voice or text "how much of product X is in stock?" – the bot will analyze the database and answer, or "what to order for next week?" – and it will generate a list based on sales and seasonality. An AI driver assistant is also relevant: a mobile application that uses a smartphone camera to analyze the driver's condition (detects if they are drowsy), warns of speeding, and builds a safe route considering road conditions. Similar functions are available in expensive truck onboard computers, but a budget solution can be made for mass transport. And, of course, customer service: a chatbot that integrates into Viber/Telegram, where a client can track a parcel, get tariff information, or place a shipment order without calling an operator. For example, Nova Poshta is testing a chatbot in its mobile application that answers customer questions without involving contact center operators. Such a GPT-based bot can also be adapted for smaller courier services.

Level of Competition in Ukraine: Low. Some international players offer local services (Google Maps has an API for routes, some foreign platforms offer SaaS for fleet management), but mass implementation is not yet widespread. Larger companies such as Meest, Ukrposhta develop their own solutions – for example, Meest China uses AI to generate marketing creatives, and Uklon uses AI algorithms to determine optimal pickup points and forecast taxi supply/demand balance. However, for medium and small operators, ready-made solutions are scarce. Startups in this niche are few – known Ukrainian SaaS specifically for logistics are hard to name, except perhaps B2B services for dropshippers (but they do not use AI). So, competition is currently lower than in fintech or marketing. The popularity of such solutions is also only emerging: companies realize that AI can significantly reduce logistics costs, but not everyone understands how. This is confirmed by the words of a Bolt director: "600 AI models help solve tasks from quick customer responses to optimizing scooter parking," which allowed the company to scale services in 50 countries. Thus, there is every chance to establish oneself as the first universal AI provider for Ukrainian logistics SMB.

Global Analogs: Flexport (USA) – a digital platform for international logistics management that optimizes freight transportation using data and ML. Route4Me, OptimoRoute – cloud services for automated delivery route planning. Ocado Smart Platform (Great Britain) – a complex of AI solutions for automated warehouses (used in online supermarkets). Uber Freight – a platform that connects shippers and carriers with dynamic pricing based on AI. These analogs demonstrate how even small companies can benefit from logistics AI – from fuel savings to better customer service.

4. Manufacturing and Industry

Industry Potential: The industrial sector (small factories, workshops) in Ukraine is currently implementing AI approaches slower than marketing or finance. Reasons include more complex processes and higher solution costs. But that is precisely why competition here is currently low, and "early birds" can occupy their niche. Ukrainian IT teams have a strong engineering background and create solutions for industrial AI: an example is the company IT-Enterprise, which has been developing AI equipment diagnostic systems for over 10 years and successfully implementing them in production facilities in Ukraine. This indicates significant potential: our industrial sector is looking for ways to automate, especially against the backdrop of post-war reconstruction. The popularity of the direction is growing, although many are still only looking at the technology. According to experts, in the coming years, even medium-sized businesses will be able to afford basic AI solutions due to the decreasing cost of sensors and cloud computing.

Typical Problems: Small manufacturing businesses often face equipment downtime due to unexpected breakdowns (lack of wear forecasting), losses from product defects (human quality control is limited, checked selectively), inefficient use of resources (e.g., equipment operating at sub-optimal modes, consuming excessive energy). Production planning is also often done manually in Excel – it is difficult to quickly reconfigure schedules for new orders or understand where the "bottleneck" is. There are also tasks in the field of safety: monitoring whether employees comply with rules (wearing helmets, not entering dangerous areas). All of these are opportunities for AI.

Possible AI Solutions: One of the most obvious is a predictive maintenance system. It collects data from sensors on machines (vibration, temperature, current, etc.) and uses an ML model to predict when and what might fail. Thus, instead of emergency downtime, repairs can be planned in advance. For example, the Ukrainian AI assistant Anna from IT-Enterprise monitors equipment status and warns of possible breakdowns at early stages, forming repair recommendations. A similar SaaS service could be in demand by hundreds of small manufacturers who do not have their own staff of diagnosticians. The next direction is AI quality control: cameras on the conveyor belt, equipped with computer vision, automatically reject defective products. For SMB, this could be a boxed solution: camera + "brain" with an ML model trained to recognize defects (spots, cracks, uneven seams, etc.) on a specific type of product. AI can also optimize processes: for example, a machine learning model configures machine parameters for optimal operation. A real case: MHP developed a model for setting up equipment that processes chicken carcasses to achieve maximum productivity. Similarly, AI could manage temperature in a bakery or line speed, based on output quality data. Another idea is a digital twin of production: a software simulator of a workshop where AI runs different scenarios (supplier change, additional order) and finds the optimal option that minimizes costs and time. For small businesses, this can be implemented as a cloud service: the user inputs initial data (production capacities, orders), and AI provides an optimized schedule or advice on where to expand capacities. Finally, safety and occupational health: an AI camera that monitors whether a person is wearing a helmet, or if they have entered a dangerous area, and immediately signals an alert. Such systems appear at large facilities, but simplified solutions could even be used by small construction companies or workshops.

Level of Competition in Ukraine: Low. There are several strong players, such as the aforementioned IT-Enterprise or departments in companies like SoftServe, EPAM, which deal with industrial AI for large clients, but there are almost no separate products "for mass small-scale production" currently. Most solutions are custom projects for a specific enterprise. Among SMBs, AI implementation is slow: as experts note, "a year earlier, businesses paid almost no attention to AI, but now interest is rapidly growing, and 2025 will be the peak year for implementation." However, even in large businesses, 6% of companies admit they are not yet working with AI – and in small businesses, this percentage is significantly higher. This is confirmed by a quote from IT-Enterprise: "in the industrial sector, AI implementation is slower... processes are more complex, the price of solutions is higher," but the developments of Ukrainian teams have high potential. Thus, competition is currently limited, and the popularity of solutions will grow with their accessibility. The first to offer an affordable and effective AI product for factories/plants can become leaders for years to come.

Global Analogs: Siemens MindSphere and GE Predix – industrial IoT platforms with AI-based analytics (used primarily by large factories for predictive maintenance and optimization). Instrumental (USA) – a service that uses computer vision for quality control on electronics production lines. Most of these solutions are aimed at the enterprise segment, so there are few analogs in the SMB segment – this is a chance for a local player.

5. Finance and Accounting

Industry Potential: Automation of financial routines is one of the "pain points" for almost every small business. In Ukraine, many entrepreneurs still keep records manually or in spreadsheets, which is time-consuming and prone to errors. AI solutions can radically simplify accounting, and this direction is only at the beginning of its development. FinTech solutions for SMB are not yet saturated: experts note that the Ukrainian fintech market is not as developed as the Western one, and there are prospects, particularly in automating accounting for small businesses (according to speka.ua). Competition here is moderate – there are several online accounting services on the market (e.g., "Takser", Fredo), but they are more about automation without AI. Large players (Mastercard, banks) are exploring AI for financial monitoring, antifraud, but offer almost no AI-based products for SMBs. So, the emergence of an "AI accountant" or "AI financial assistant" could well be a niche breakthrough.

Typical Problems: Entrepreneurs and accountants spend a lot of time on routine operations: manual entry of primary documents (invoices, acts, waybills), posting bank statements, payment reconciliations, filling out tax declarations. The human factor leads to errors in reports and tax penalties. It is also difficult for small businesses to analyze their financial situation: where the biggest expenses are, which products are most profitable, how to forecast cash flow – often this is done intuitively. Financial analyst consulting is expensive, so decisions are made blindly. At the same time, small businesses are very sensitive to cash gaps, exchange rate fluctuations, payment delays – here AI could help with forecasts and advice.

Possible AI Solutions: AI Accountant / CFO-as-a-Service. Let's consider an example of a cloud service where a company connects its data: bank statements, invoices (PDF or photo), receipts. Then AI automatically recognizes (OCR) and categorizes it: here are rent expenses, here is income from such and such a client, allocating by categories. Already, individual tools exist that perform such tasks, but AI can go further – generating accounting entries, checking their compliance with standards. For example, thanks to NLP technology, an accountant chatbot can be implemented: the entrepreneur asks it: "What is my stock balance and how much is it in hryvnias?" or "Prepare my quarterly tax declaration" – and the bot, having access to accounting data, provides the answer or generates the document. AI can also automatically prepare reports (balance sheet, P&L) in an understandable format, even explaining it: "Your expenses this month are 15% higher due to raw material purchases, be prepared for lower profit." A useful function would be anomaly and fraud detection – AI monitors transactions and signals if any operation looks suspicious (e.g., a sharp increase in fuel costs may indicate driver abuse). For retail businesses, AI can integrate with POS terminals and maintain an online dashboard with key indicators: daily revenue, expenses, category margins. In essence, it's an "AI CFO" for those who cannot hire a real one. Another option is planning and budgeting: the owner sets goals (e.g., accumulate X hryvnias by the end of the year), and AI proposes a plan – how much to save monthly, where to cut expenses, etc. In crisis situations – it advises where to get a loan or grant, on what terms (analyzing available programs, like a consultant). For individual entrepreneurs (FOPs), an AI bot that automatically generates and sends tax reports, reminds about paying ESV (unified social contribution), and even generates a payment slip in Privat24 would be useful – currently, services like "Checki" do this, but without an AI component (they just substitute numbers). AI can also optimize taxation: by analyzing expenses, suggesting whether it is profitable to switch to another single tax group, or if everything is accounted for VAT tax credit, etc.

Level of Competition in Ukraine: Moderate (bordering on low). The online accounting market is represented by several solutions, but they mainly automate processes without applying artificial intelligence. For example, services like "Diia.Business" provide basic tools (tax calendar, document templates) but lack intelligent analysis. Banks have introduced some AI elements in business online banking – Monobank for FOPs suggests taxes, and Privat offers a chatbot for statements – but this is just the beginning. Western giants like Intuit QuickBooks are adding AI agents for automatic expense categorization and anomaly detection, but Ukrainian entrepreneurs mostly don't know about them or don't use them. On the other hand, the Mastercard SME Index 2024 shows that 21% of Ukrainian entrepreneurs have already implemented AI, most often for marketing, translation, content generation, and customer communication (cited in forbes.ua). This means finance is not yet a top priority – this is a niche worth filling. It can be predicted that the popularity of AI accounting will only grow: first, FOPs with a single tax will appreciate it (because their reporting is simpler), and then others will follow. Competition might come from global solutions if they enter Ukraine with localization, but such a movement is not observed yet.

Global Analogs: Xero, QuickBooks Online – popular platforms for small businesses that integrate AI elements. In particular, QuickBooks recently introduced the AI assistant Intuit Assist, which automates transaction categorization and assists with bookkeeping quickbooks.intuit.com. Pilot (USA) – a startup that combines AI and live accountants to provide outsourced accounting to small companies. Fonoa AI – a service for automatic completion of tax declarations for entrepreneurs (including VAT for e-commerce) based on transactions. There are also niche AI agents, such as Docyt or Vic.ai, which handle invoice recognition and posting to accounting without human involvement. All of them confirm: AI in finance can take over routine work, freeing up an entrepreneur's time for business development.

6. Marketing and Content Generation

Industry Potential: In the last year, generative AI has revolutionized content marketing. Small businesses have gained tools that allow them to create texts, images, and videos at a professional level, but faster and cheaper. In Ukraine, proactive entrepreneurs use ChatGPT for social media posts or Midjourney for advertising images. According to research, over 20% of Ukrainian SMBs already use AI in marketing and SMM activities. However, this is mostly ad-hoc use of general models. The niche, however, lies in creating specialized AI platforms for marketing, adapted to the Ukrainian market, language, and consumer specifics. Local competition is low: there are many global AI tools (Jasper, Copy.ai, Canva with AI, etc.), but Ukrainian products that consider the local context (cultural features, slang, trends) are few. For example, Netpeak developed Ringo AI for analyzing the tonality of customer inquiries and auto-generating responses in support, but a comprehensive AI marketing assistant is not yet available. Globally, the trend is clear: "generative AI is transforming creative industries, automating content, code, and graphics creation." For Ukrainian SMBs, this is an opportunity to get 24/7 marketing at an affordable price.

Typical Problems: Small businesses do not have large marketing teams or budgets for agencies. The owner often has to write website texts, manage Facebook pages, and come up with promotions themselves – often irregularly and of poor quality due to lack of time or skills. Visual content (banner design, catalog photos) also requires a professional, who may not be available. Launching an advertising campaign on Google/Facebook is a challenge for a novice; one can waste budget without achieving results. Marketing analytics (who is our target audience, which channels work) is often not conducted at all in small businesses. A separate problem is the language barrier: much content needs to be created in two languages (Ukrainian/Russian, and sometimes English for foreign clients) – this is double work. All these are areas where AI can become a "multi-armed marketer."

Possible AI Solutions: An AI marketing assistant – a universal SaaS or bot that can both generate content and plan/analyze campaigns. For example, a user makes a request: "Create a promo post for our new service for Facebook in Ukrainian" – and AI (considering the specified brand tone) generates text, selects a relevant image, or even creates it (via stable diffusion or Midjourney API). Such a post would only need minor editing and scheduling. Furthermore, AI could plan the content calendar itself: based on the business industry, suggest blog topics, publication schedules considering seasonality, holidays, etc. The next module – advertising automation: an AI assistant connected to Facebook Ads or Google Ads, which asks the entrepreneur about their goals in simple terms ("I want to sell 100 units of product X per month, budget is such and such") and itself forms advertising campaigns, selects audiences, and keywords. Then it optimizes them daily (increases bids on effective ads, turns off ineffective ones). Currently, specialists or basic Facebook algorithms do this, but proprietary AI can do it more transparently and with explanations. For example: "I analyzed your audience and found a segment 'women 25-35, Kyiv, interested in eco-cosmetics' – I recommend launching a separate ad for them." Creative generation: AI can create not only texts but also images and even videos. Therefore, the service could offer: "Here are 5 banner options for your promotion, choose which one you like." Or generate a short promo video for Instagram Reels from existing product photos, add an AI narrator's voice in Ukrainian for voiceover – all automatically. Translation and localization: if a business operates in several markets, AI can immediately translate content, taking into account cultural nuances (fine-tuning models for a specific brand would help here). An AI assistant can also save time on SEO: it will generate meta-tags, product descriptions, and articles with the necessary keywords. Finally, marketing analytics: a bot analyzes Google Analytics and social networks and answers questions: "Where do customers come to my website from? Which post received the most engagement and why?" It also gives advice: "I see that email newsletters give the highest ROI – it's worth enhancing them."

Level of Competition in Ukraine: Moderate. On the one hand, the Ukrainian market is already familiar with basic AI tools: 27% of SMBs worldwide use AI for marketing, and Ukrainian entrepreneurs are among them. Tools for text generation, translation, and customer communication are especially popular. This means there is demand for AI marketing, and it is even partially satisfied by global products (many use ChatGPT or neural networks for images). On the other hand, there are few local services that take into account market specifics. There are several startups in this field: for example, Crafted implements AI for generating advertising slogans, Reface offered B2B solutions for personalized video advertising, ZibraAI – generative graphics tools (but more for games). However, a comprehensive "all-in-one" solution has not yet emerged. This is also confirmed by global trends: the startup Jasper took the path of creating a full-featured AI platform for marketing, unlike universal chatbots. Jasper succeeded by specializing in marketers' needs – integrating brand voice, audience data, and learning to generate targeted content based on best practices. In Ukraine, similar specialization is only brewing. Therefore, competition is currently limited to a set of isolated AI tools, while popularity is high: according to Forbes, marketing is the most common application area for AI in Ukrainian small businesses at the moment. Thus, launching a convenient "AI junior for marketing" in Ukrainian means entering a prepared market and attracting an interested audience.

Global Analogs: Jasper (USA) – one of the leaders in AI content marketing platforms, positioned as an AI co-pilot for marketers, automating tasks from writing posts and email newsletters to creating advertisements. Jasper integrates large language models (GPT-5) with its own training on marketing data, allowing it to maintain a specific brand tone and create more relevant content. Copy.ai, Writesonic, Rytr – other popular text generation services for marketing. Canva – a graphic editor, added AI functions (image generation, auto-design selection). Adext AI – a platform for automatic management of advertising campaigns (selects audiences and optimizes budget across different channels). All these tools confirm the trend: marketing is increasingly automated with AI, and therefore, a local service that understands the Ukrainian consumer can successfully compete by offering better localization and support.

7. Customer Service and Support

Industry Potential: Customer service is an area where AI can significantly reduce staff workload and improve customer satisfaction. According to observations, in Ukraine, the most popular AI tools are chatbots and voice bots for customer support, which allow companies to operate 24/7 and save on operational costs. Large banks, telecom, and e-commerce companies have massively introduced consulting bots. However, small businesses are just beginning this journey: many believe that a quality custom bot is expensive or complicated. In reality, modern no-code platforms and GPT models simplify the creation of AI bots. The niche is in offering affordable, "smart" chatbots tailored to SMB needs: with natural language understanding (Ukrainian!), integration into popular messengers, and the ability to train on the knowledge base of a specific business (FAQ, product catalog). Competition is moderate: there are many chatbot builders (with scripts), but few of them use AI and deep contextual understanding. The popularity of such automation is growing – customers are getting used to receiving instant answers. According to Oschadbank, using voice assistants saves 10–30% of the contact center budget. This is a direct hint for SMBs that AI support means real savings.

Typical Problems: Small companies cannot maintain a large call center. Often, one or two support managers physically cannot handle all calls and messages, especially during peak hours. Customers wait for email or chat responses for several hours (or even days), which reduces their loyalty. There's also the human factor: some managers might respond impolitely or forget to provide complete information. New operators need extensive training on the company's FAQ. Simultaneously, 70-80% of customer inquiries are typical: "What's the status of my order?", "How do I return a product?", "How much does delivery cost?" These questions can be fully handled by a bot. Besides answers, businesses need to analyze the sentiment and issues of inquiries: what are the most common questions, what are the complaints – to improve the product. This can also be automated.

Possible AI Solutions: An AI chatbot for customer support is the main candidate. A modern bot based on large language models can freely understand customer questions "in their own words" and provide relevant answers, not just select a script based on keywords. For SMBs, it should be as easy to launch as possible: just upload your FAQ (frequently asked questions with answers), product/service information into the system, and the bot is ready to answer 24/7 in the selected channel (on the website via web chat, in Facebook Messenger, Telegram, Viber, etc.). Such a bot can cover up to 90% of text inquiries: from pre-purchase consultations to post-purchase support. For example, OTP Bank in Ukraine already uses a voice bot and chatbot "Omilia" for initial inquiry processing, as well as the Ender Turing language analytics system, which transcribes all calls and analyzes them using AI. This reduces response time and opens up a new layer of data for service quality analysis. For small businesses, a single omnichannel bot would be a good solution: so that inquiries from the website, messengers, social networks – everything is collected in one interface and answered by one AI agent. In addition to answering questions, the bot can perform actions: for example, a client types "I want to change the delivery address" – the bot will make changes in the CRM via API; or "Send me a copy of the invoice" – the bot will find it in the database and send a PDF. Such a "smart agent" would genuinely relieve a lot of routine work. Another function is voice assistants for calls. Phone inquiries are still relevant (especially for an older audience). AI can take a call, recognize the client's language, and provide answers with a synthesized voice. For small businesses, a "virtual secretary" service could take all calls, answer typical questions, and switch complex ones to a human or record messages. Next – AI analytics of inquiries. All chats and calls can be analyzed by AI for emotionality (negative/positive), frequency of certain topics ("defective product", "delivery delay", etc.). The business owner receives a regular AI report: for example, "Over the last week, 15% of inquiries were about order status – perhaps tracking should be implemented on the website. 5% of customers are dissatisfied with packaging quality – it needs to be checked." Such analytics was previously only available to large call centers with a quality control department, but now a bot can do it (in Ukraine, Ender Turing and similar solutions handle this). A separate niche is sales chatbots: the bot's ability not only to support but also to sell to the customer. If a client asks about product A, the bot can suggest accessory B ("People often buy a case for this phone, here are some options") and even process the order during the dialogue. This transforms passive support into an active sales channel.

Level of Competition in Ukraine: Moderate. On the one hand, the market is not new: chatbots are very popular and provided by hundreds of agencies and platforms. But traditionally, these were script-based bots: scenarios had to be manually programmed. With the advent of GPT models, the quality of bots has increased – they have become more "human-like." There are several startups with AI bots in the Ukrainian market: for example, BotsCrew operates globally (they had experience with medical bots), Skilful.ai offers an AI bot for e-commerce. Large outsourcers (Intellias, etc.) also have developments. However, mass penetration of intelligent AI bots into SMBs is not yet widespread. Many companies do not even have an online chat, let alone a bot. According to the aforementioned Mastercard index, 34% of businesses in Ukraine only show interest in AI technologies (i.e., they have not yet implemented them). This means that the wave of bot implementation in small companies is still ahead. Their popularity will inevitably grow, as customers expect an instant response. Let's recall how quickly everyone got used to writing to brands via Instagram direct messages or messengers – now they expect replies within minutes. Competitors: global platforms like Dialogflow (Google), Watson Assistant (IBM) offer AI backends for bots, and there are many no-code services (ManyChat, Chatfuel – but they do not use AI). However, for local businesses, the value lies in a turnkey solution in Ukrainian and with support for local channels (Viber, calls). Here, competitors are few. Therefore, a company that offers a simple and smart AI bot can capture a significant market share of SMBs. After all, "businesses are actively looking for new tools, but there are not enough quality developments to satisfy all demand" – as the CEO of IT-Enterprise notes about AI solutions in Ukraine. This fully applies to customer bots as well.

Global Analogs: Ada Support (Canada) – an AI chatbot platform for support, allowing non-technical teams to create bots that respond based on NLP. Intercom Fin – a GPT-based AI bot integrated into the Intercom support system (can independently answer customer questions, learning from a knowledge base of articles). Zendesk Answer Bot – an AI module in the well-known Zendesk system that scans customer questions and automatically finds answers in the knowledge base. Also, Omilia – a global provider of voice bots (incidentally, with Ukrainian R&D, used by OTP Bank) for call centers, capable of natural language conversation. These analogs confirm that even multilingual AI bots are already a reality – for example, Omilia successfully recognizes Ukrainian in phone dialogues. Thus, Ukrainian businesses can leverage these developments or offer their own product, more adapted to local needs.

8. HR and Personnel Management

Industry Potential: Automation of HR processes using AI is still a less developed area in Ukrainian SMB, which makes it an attractive niche. While marketing and support have obvious AI use cases, HR is only beginning to adopt AI: some large companies are experimenting with resume screening or chatbots for internal communications, but medium-sized businesses mostly operate in the old way. At the same time, the HR direction has many routine tasks that can be delegated to AI: candidate selection, staff training, personnel document management. Competition here is currently low – there are few Ukrainian products, global solutions (e.g., Workday, Oracle HCM with AI functions) are complex and expensive for small businesses. Therefore, the opportunity to create “AI-HR for SMB” is quite real. According to surveys, in 2024, companies worldwide planned to invest in AI for HR transformation, particularly in candidate assessment algorithms and recruitment automation. Ukraine is unlikely to lag behind.

Typical Problems: Recruitment. When a vacancy opens, a hundred resumes might come in – the HR manager spends days reviewing them to select a few for an interview. This is long and tedious. Communicating with candidates also takes time: agreeing on interview times, answering typical questions about the company. Newcomer Onboarding: every new employee needs to be explained the same basic things (schedule, company policies), collect documents, sign applications – a lot of administrative work. Staff Training and Development: small businesses don't have an L&D department, but people need to be trained – often this responsibility falls to the manager or HR, and not always systematically. Internal Communications: employees have questions about vacations, salaries, sick leave – HR answers each personally, although the questions are typical. Likewise, employee satisfaction assessments are rarely conducted (due to lack of time), and management may not be aware of brewing problems.

Potential AI Solutions: AI Recruiter. This is a set of tools that helps at all stages of hiring. For example, resume screening: An AI model, trained on data about successful company employees, automatically evaluates each resume according to set criteria and ranks candidates. It can pay attention not only to keywords but also to the semantics of the description (e.g., recognizing that "managed a department" experience is similar to "led a team"). According to ITExpert, AI algorithms can analyze resumes and previous hiring history to recommend the best candidates for a specific role to a recruiter itexpert.work. Next is – chatbot for candidates: A potential hire visits the company website and can chat with a bot that answers questions about the vacancy ("what's the work schedule?", "is it remote?"), collects basic candidate information, and even conducts an initial video interview. Video interview: The candidate answers a few questions in front of a webcam, AI analyzes their answers (textually, and possibly facial expressions) and provides the recruiter with a summary – which applicants are most communicative, motivated, etc. Such solutions also exist (HireVue, though it has been criticized for bias), but adapting them to the local market is a prospect. Interview Scheduler: A bot integrated with the recruiter's calendar automatically schedules interview times with candidates – suggesting slots, confirming appointments, and sending reminders. Onboarding and HR Bureaucracy: an AI assistant can also help here. For example, a new employee fills out all necessary forms via a chatbot, and the same bot answers typical questions ("how to apply for leave?", "where to find the compensation policy?"). Leena AI is a well-known example of an HR chatbot that automates onboarding, answers internal HR questions, and so on. A similar service in Ukrainian would fill a considerable niche. Staff Assessment and Team Morale: AI can regularly conduct pulse surveys of employees (via a bot: "rate on a scale of 1-5 how tired you are today," etc.) and analyze them. Or analyze the tone of internal correspondence (if ethically permitted) for signs of declining morale. Then HR receives analytics: "The sales department has seen an increase in negativity over the month – it might be worth holding a meeting to find out the reasons." Development and Training: an AI trainer can create individual development plans: for example, knowing that a manager lacks leadership skills, they can recommend a course (possibly also AI-generated or selected) and even test knowledge afterward (test, case study). HR Document Management: generation of typical documents (hiring order, certificate, contract) according to specified parameters – AI quickly substitutes the necessary data into a template, no need to manually edit. Also, candidate document verification: for instance, uploading a passport scan – AI checks for completeness.

Level of Competition in Ukraine: Low. Today, most of the listed tasks are performed manually or with simple tools (Google forms, Zoom polls, etc.). There are few specialized AI products on the Ukrainian HR market: perhaps some recruiting platforms add ML elements for candidate search in their databases (Work.ua, Djinni – and even that is minimal). Therefore, the implementation of AI in HR is currently happening in isolated cases, through the efforts of the companies themselves: for example, SoftServe created an internal bot "Sofia" to answer employee questions; some IT firms use ML to analyze employee feedback. But massively SMB currently does not use AI in HR – this is not mentioned among the top application scenarios (unlike marketing or translation). This means there is an untapped niche. The popularity of such solutions can grow quickly when successful cases emerge. People get tired of routine, and finding a good HR is difficult – so businesses will be happy with a tool that unloads the team. This is especially relevant now, when many companies have cut staff and one person handles HR, recruitment, and administrative work simultaneously. Competitors: globally there are Oracle HCM Cloud, SAP SuccessFactors – large systems with AI modules, but they are enterprise-oriented. For SMB, the following startups are known: Paradox (Olivia) – an AI recruiter that communicates with candidates, Eightfold.ai – a platform for talent acquisition and management with deep ML. However, few people use them in Ukraine. So the space is almost free, the main thing is to consider local specifics (Ukrainian language, our labor norms, etc.) and overcome possible skepticism about "a robot deciding who to hire."

Administrative tasks. In a private clinic, an administrator spends time on patient registration, visit reminders, explaining preparation for procedures, etc. This is routine and can be automated.

Possible AI solutions: Medical chatbot consultant. The user describes their symptoms in plain language, and the bot (backed by a medical knowledge base) asks clarifying questions and provides a preliminary assessment: what it could be, how urgent it is, and which doctor to consult. Important: the bot does not provide a final diagnosis (to avoid legal issues), but acts as triage: «Based on your symptoms, X or Y are possible. It is recommended to consult such-and-such a specialist. This does not appear to be an emergency, but it's better to get checked.». Or vice versa: «There are signs of a stroke – call an ambulance immediately!». Such a bot could be integrated into the eHealth system or clinic websites. Example: the global AI-based Ada Health app does exactly this – it asks questions and assesses symptoms. For Ukraine, it is worth training the model on local protocols and terminology. Psychotherapeutic bot. It will not replace a human psychologist, but can act as a «listener» and coach: to communicate with a person experiencing stress, provide basic calming techniques (breathing exercises, advice), and redirect negative thoughts into a more positive channel. Such bots, like Wysa, Woebot, show effectiveness for mild cases. A Ukrainian analogue could help veterans, displaced persons, and other groups who are currently facing particular difficulties. AI assistance for doctors in diagnosis. For example, a service for X-ray/CT: the doctor uploads an image – the AI model analyzes and highlights suspicious areas (spots in the lungs, opacities, tumors, etc.) and offers a preliminary description. In Ukraine, 9 AI systems have been implemented that help diagnose tuberculosis and other lung pathologies based on X-ray images (phc.org.ua) – this saves time and increases accuracy. Similarly, AI can analyze mammograms for signs of breast cancer or retinal images for diabetic retinopathy – such models exist. For laboratories – an AI analyzer of microscopic images (blood, tissues) to detect atypical cells. 

Administrator-bot for the clinic. It communicates with patients via messenger or phone: schedules appointments (offering available slots in the calendar), sends reminders "you have a visit tomorrow at 3:00 PM, don't forget your test results", answers queries "how to prepare for an abdominal ultrasound?" (according to protocol). This will reduce unnecessary workload on reception. 

Personal fitness/wellness assistant. For B2C – an AI application that, based on user data (weight, blood pressure, goals), creates a personalized exercise or diet program, tracks progress, and encourages. There are many global ones (like BetterMe, created in Ukraine for the world), but something localized or niche can be done (for example, AI for rehabilitation of the wounded – suggests exercises, tracks performance via camera).

Level of competition in Ukraine: Low to moderate. In the public sector, there are some shifts: separate AI systems are being implemented in hospitals (as with tuberculosis), and telemedicine pilot projects are being conducted, which have shown positive results. Even family doctors in rural areas have started using AI algorithms (probably for basic diagnostics) thanks to the new telemedicine law. However, for the private sector and even more so for ordinary citizens, AI medicine is still almost inaccessible. Several Ukrainian startups are working in this area globally – Esper Bionics (prostheses with AI elements), AI PSY HELP (semi-automatic psychological support), etc. However, there is no mass-market product. Many use foreign apps (for example, women – Flo for cycle tracking, athletes – MyFitnessPal), but the Ukrainian user would like localization and consideration of local realities (our units of measurement, our food products in the database, etc.). So, competition is mainly global for now (apps in marketplaces), and local solutions are minimal. Popularity is potentially very high, as health concerns everyone. The need for accessible psychological support has particularly increased – and here AI can become a solution for those who cannot frequently see a psychotherapist.

Global analogues: Ada Health (Germany) – an AI-based medical symptom checker, has millions of users, conducts interactive questioning, and provides possible causes for symptoms. Woebot, Wysa – popular therapeutic chatbots that talk to users about their problems and apply cognitive-behavioral therapy techniques. SkinVision – an app that uses AI to analyze a photo of a mole or skin rash and assesses the risk of melanoma. Doximity GPT – a tool for doctors (generates visit summaries, suggests treatment plans based on symptoms). All these services show how AI is penetrating diagnosis, treatment, and prevention. For Ukraine, such tools are needed in Ukrainian and taking into account our treatment standards – this is a niche that can be filled.

Potential B2C niches: AI services for consumers

In addition to B2B directions, there are many consumer niches (B2C) where AI services can attract a wide audience of Ukrainian users. Below are a few promising ideas:

• Personal finance and budgeting. A chatbot financial assistant that analyzes user spending (by connecting to bank statements or even reading SMS from the bank) and helps manage a budget. It can suggest where to save money, set limits (“don’t spend more than 500₴ on coffee this month”) and even give investment advice for beginners. A global analogue is the bot Cleo, which calls itself the “first AI financial assistant” and helps millions of users plan expenses, build savings, and even communicate by voice (according to vox.com). There is no mass analogue in Ukraine yet, although Monobank is partially moving in this direction (showing expense analytics). The level of competition is low, and the need is high, especially among young people.
  
  

• Mental health and self-support. An AI chat with which one can “talk it out” at any moment, receive emotional support or advice for stress relief. It can guide through simple mindfulness exercises, teach breathing techniques, and track user mood with daily questions (“How are you feeling today?”). Such a service would be especially relevant now, given the number of people with anxiety disorders due to the war. Competitors: global Wysa, Woebot (English-speaking therapist bots), and among Ukrainian initiatives – perhaps only some Telegram bots from volunteer psychologists (but they are not AI). The niche is practically free, provided anonymity and correctness of advice are ensured (for example, if the bot “notices” suicidal tendencies, it should redirect to a specialist).
  
  

• Personal learning assistant. An AI tutor that helps with school curriculum or language learning. For example, a student asks: “Please explain the Pythagorean theorem, I don’t understand” – the bot explains in simple words, gives examples. Or a student asks to check and improve their essay – AI does it. For learning English or another language, the bot can act as a conversational partner, correct mistakes, and suggest new words. Global analogues: Duolingo added an AI chatbot for language practice, Khan Academy is testing the Khanmigo assistant to help students. In Ukraine, an Ukrainian-language educational bot that knows the school curriculum and ZNO/NMT (Ukrainian standardized tests) could be in high demand. Competition: educational websites (like "Na Urok") do not yet have such bots, tutoring services are expensive – so an AI alternative looks promising.
  
  

• Personal assistant for everyday life. A chatbot that integrates into a smartphone and helps with daily tasks: from schedule planning (reminding about a meeting, creating a to-do list) to shopping recommendations. Example dialogue: “Hi, I need to buy a washing machine under 15,000 UAH, what do you recommend?” – the bot analyzes reviews, characteristics and provides 2-3 optimal models with explanations. Or: “Schedule me runs three times a week at 7:00 AM and remind me in the evening to take vitamins” – the assistant will add this to the calendar and send a reminder. This is similar to a combination of Siri/Google Assistant with ChatGPT, but with a local emphasis. The main thing is to learn to understand the context of Ukrainian life (holidays, geography, etc.) better than global assistants. Competitors: Apple Siri, Google Assistant are already available in Ukrainian, but their intelligence is limited to scenarios. New AI agents (Replika, X.AI from Elon Musk in the future) are potential competitors, but there is currently no clear leader in the Ukrainian market.
  
  

• Smart advisors in niches. Here, smaller B2C niches can be identified where AI can help make decisions. For example: AI lawyer for the public – will answer typical legal questions in simple words (how to apply for a subsidy, what to do in case of an accident, how to file a lawsuit for alimony). Projects like DoNotPay exist – a “robot lawyer” for disputing fines, which successfully helped overturn hundreds of thousands of parking fines mezha.net. It is available in the USA in all states, and in Ukraine, an analogue could advise on our laws. Another example: AI stylist – you upload your photo or enter parameters, and the bot suggests clothing options, hairstyles, makeup that suit you, taking into account current trends and even suggests where to buy (monetization – partnership with stores). AI travel planner – based on interests and budget, will create a route, schedule, find and book tickets/hotels (Skyscanner has similar functions via ChatGPT-plugins, but for Ukraine, nuances of national carriers and local resorts can be taken into account). AI assistant for motorists – analyzes the sound of the engine through a smartphone microphone and suggests if everything is fine, or advises on what to do in case of an accident (who to call, what documents to fill out). The list can go on – essentially, any information consumption industry can receive an AI add-on. Currently, there are very few such specialized assistants on the Ukrainian market, making this a wide field for experimentation.

Overall, B2C AI services in Ukraine are currently minimally represented – mostly people use global applications or just general ChatGPT for their own needs. Localization and targeting specific problems of Ukrainians will allow creating original products with low initial competition. It is important to remember about trust and ethics: consumers must be confident that AI will not harm (will not give wrong advice in a critical situation, will protect data privacy). The one who first wins the trust of users with their AI service can gain a significant advantage in the nascent market.

Сonclusion

Artificial intelligence opens up many opportunities for automating both business processes and everyday tasks. For the Ukrainian audience, niches that combine high demand, low market saturation, and the possibility of localization to our specifics are particularly promising. These include: agricultural sector, logistics, industry, financial and legal support for SMBs, personalized marketing, customer service, as well as B2C services – from personal financial bots to AI psychologists. As global experience shows, implementing AI in these areas allows saving 20–30% of resources, minimizing routine and human factors, and most importantly – freeing up time for more creative and strategic tasks. Ukrainian business and society are rapidly catching up with global trends: about a quarter of companies use AI in some way, and 2026 promises a real boom in implementations. Demand is high, but quality products are still lacking. Therefore, now is the ideal time to launch new AI services that address the specific needs of the Ukrainian audience. The listed niches and ideas are not an exhaustive list, but they can become a starting point for a startup or project that aims to create an original AI-based service and gain a loyal audience with minimal competition at the start.