Chatbots—virtual assistants that engage in conversation with customers—have become a permanent fixture in the Polish e-commerce landscape. Their development from the mid-2010s to the mid-2020s has undergone a significant evolution, progressing from simple script-based programs to advanced AI-powered assistants. This report is divided into three key periods: before 2022, the years 2022–2023, and the years 2024–2025. For each phase, we discuss the chatbot solutions used, dominant functions, expectations of stores and customers, and the most important changes over time. At the end, we summarize the key trends and highlight e-commerce sectors that stood out in terms of chatbot adoption.

Period I: Before 2022 – The Beginnings of Chatbots in Polish E-commerce The first chatbots in Polish online stores began to appear in the second half of the 2010s. This was a time of experimentation and learning—for both the companies implementing them and the customers adjusting to a new form of interaction. In the initial phase, simple script-based solutions dominated (often referred to as “first-generation chatbots”). These bots typically operated via messengers like Facebook Messenger—according to a 2018 report, 16 out of 18 analyzed Polish bots were integrated with Messenger. Messenger’s popularity stemmed from its widespread use and the platform’s openness to bots; many companies chose this channel to reach customers where they were already spending time. Gradually, bots embedded directly on websites (via live chat windows) and the first integrations with voice assistants on helplines also began to emerge, although the latter were less common in e-commerce.

solutions Used: In the early days, chatbots relied mainly on predefined scripts and basic keyword recognition. Many of them did not use advanced NLP (Natural Language Processing); users often had to choose from listed options or type in specific phrases to be understood. These were so-called block or process bots—leading the customer step by step through a fixed process (e.g., choosing a product, providing a delivery address) without allowing for free-form conversation. For example, a bot might guide a user through placing an order for a simple product by asking a series of sequential questions—product category, item, delivery details—all via button choices. Another common use case was notification bots—the equivalent of a newsletter sent through a messenger. Such bots could inform users about order status or send daily offers or tips, often achieving high reach due to Messenger being less saturated than email.

Dominant Functions: In the first phase, the most common chatbot functions in e-commerce focused on answering frequently asked questions (FAQs) and offering basic advice. Bots acted as 24/7 assistants—providing information about the product range, availability, payment methods, delivery options, return policies, and so on. This helped reduce the load on human agents and cut customer service costs. Some were also used to support sales in a limited way—for example, as virtual advisors helping users choose a product or gift guide bots suggesting ideas based on criteria (a scenario implemented, for example, in the gift shop Wyjątkowy Prezent). It’s worth noting that even at this early stage, chatbots were used for collecting marketing leads (e.g., Orange Polska’s bot collected contact details from potential telecom customers) and initiating customer contact (e.g., sending promotions or updates). Most early bots, however, focused on a narrow task area—each one “specialized” in a particular topic. For example, one bot might handle order status queries only, while another helped users select products. Personalization was in its infancy—advanced product recommendations weren’t yet common, though some bots could remember the user's name or previous choices to tailor the next interaction. As early as 2018, experts noted that a well-programmed chatbot could remember a customer’s preferences and offer personalized suggestions upon their return (regarding size, style, color, etc.)—though in practice, this required integration with user accounts or databases, which wasn’t always implemented in the earliest versions.

Expectations of Stores and Users: E-commerce businesses that adopted chatbots before 2022 primarily aimed to improve customer service accessibility. Traditionally, customer support operated on weekdays during office hours, while most online shopping happened in the evenings and on weekends. Chatbots were expected to fill this gap by offering 24/7 assistance—ensuring that customers didn’t abandon their carts due to unanswered questions after hours. Bots were also expected to speed up service—providing immediate answers to simple questions without waiting for an email or hotline reply. For stores, automation and cost savings were key motivators: a well-designed bot could handle dozens of percent of customer inquiries, which at scale translated into smaller call centers. Customers initially approached chatbots with curiosity, but also caution. Many appreciated the ease of getting quick answers in a chat window without having to search through FAQ pages. On the other hand, the limitations of early bots sometimes led to frustration—if a bot didn’t understand a question outside its script, the conversation stalled. It was therefore crucial for the bot to be able to smoothly transfer the user to a human agent when needed. Many companies followed this model: the chatbot acted as a first line of support for simple issues, escalating complex problems to live agents (the so-called hybrid model). Users quickly became accustomed to this division and accepted it—as long as the handoff was seamless.

Example Implementations in Poland (Before 2022): Even before 2020, several pioneering chatbot implementations emerged in Polish e-commerce across various industries. For example: Sports retailer Decathlon offered a simple bot to answer questions about product availability (using predefined replies in a block-based setup). Luxury fashion store Moliera2 deployed a chatbot on its website that greeted visitors and offered help with topics ranging from product queries to loyalty programs and discount codes. Shoe chain CCC used a Messenger bot integrated with its product catalog. Users could type what they were looking for (e.g., “red high heels” or “shoelaces”), and the bot would show matching products, including images, prices, and buy-now buttons. This foreshadowed more advanced sales features and was considered innovative for its time. Travel platform Travelplanet.pl launched a virtual advisor to help customers find holiday offers—interacting with the bot to select preferences (destination, date, vacation type), after which the bot presented relevant options with images and booking links. Gift retailer Wyjątkowy Prezent used a bot to help users find gift ideas—asking about the occasion or recipient’s interests, and suggesting relevant products or services. Outside of traditional online stores, bots also appeared in related e-commerce services. For example: Logistics company InPost launched a Messenger and web bot for package tracking and answering questions about parcel lockers. Furniture chain IKEA experimented with a bot that advised on products and answered FAQs. These examples demonstrated that sectors like fashion, footwear, and sports quickly adopted chatbots—often using them as interactive product catalogs with FAQ capabilities. The travel and gift sectors stood out with creative uses of bots to inspire customers. Overall, however, chatbot deployments before 2022 were mostly pilot projects—used primarily by larger players and market innovators testing how the technology affected sales and customer satisfaction.

Period II: 2022–2023 – Widespread Adoption and Turn Toward AI

The years 2022–2023 marked the period when chatbots in e-commerce moved from being a technological novelty to becoming mainstream. An increasing number of stores – including medium and smaller ones – began implementing virtual assistants, drawing on the experience of early adopters and the emergence of “chatbot as a service” platforms. According to expert estimates, by the end of 2022, most Polish online stores were already using some form of chatbot on their websites or messaging platforms (source: E-handel w 2023 r.: cross-border, AI, omnichannel, chatboty... - Omnichannel News). Chatbots were no longer seen as experimental, but rather as an almost essential element of a professional online store – similar to the earlier shifts toward social media presence or mobile apps. Retailers recognized that the growing scale of e-commerce (further accelerated by the pandemic in 2020–21) was generating such high volumes of customer inquiries that automating service became a necessity.

Implemented Solutions: During this period, chatbot technology saw a clear qualitative leap. Many tools based on artificial intelligence emerged, often referred to as “second-generation chatbots” (Polskie Chatboty 2018 – raport najciekawszych polskich wdrożeń | K2). In practice, this meant that e-commerce bots began to use improved NLP engines to understand natural language and conversation context. As a result, users were no longer limited to rigid commands or clickable options – they could increasingly phrase questions in their own words, and the chatbot would correctly interpret them. In the Polish market, platforms appeared that allowed companies to “train” chatbots based on company documentation, FAQs, and product catalogs, enabling bots to answer hundreds of product-related questions without manual programming of each variation. Furthermore, integration with store systems was increasing: a chatbot connected to a database could, for example, check the status of an order by its number or provide the current balance of a customer’s loyalty points – tasks that previously required calling customer support. At the same time, ready-to-use SaaS solutions developed by specialized companies gained traction – instead of building a bot from scratch, stores could use Polish platforms like SentiOne or K2 (PerfectBot), or international solutions like LiveChat/ChatBot or built-in tools within messaging apps (e.g., Meta offering an improved Messenger API for businesses). These tools increasingly offered user-friendly interfaces for training bots, conversation analytics, and ready-made integrations (e.g., connecting the bot to a Shopify or IdoSell store). In 2022, messaging apps like WhatsApp also gained enormous popularity – many stores began offering chatbot interactions on these platforms as well, especially after WhatsApp opened its Business API. Overall, chatbot contact channels became more omnichannel: the same virtual assistant could serve customers via the website, Messenger, WhatsApp, and even the store’s mobile app. A major technical breakthrough occurred at the end of 2022 with the public release of ChatGPT – this advanced AI demonstrated to the world the potential of truly natural conversations with machines. Already in 2023, the first attempts were made to apply GPT models in e-commerce customer service (e.g., some Polish stores began testing ChatGPT to generate answers to more complex questions or provide translations into other languages). This trend was still in its infancy in 2023, but it clearly set the direction for future development.

Key Functions: In 2022–23, the range of chatbot capabilities significantly expanded. In addition to their still-basic role of quickly answering FAQs, bots increasingly served as active shopping assistants. A chatbot could greet a visitor to the e-store and ask whether they needed help, then suggest product categories to browse – personalizing the greeting based on past purchases or previously viewed products (E-handel w 2023 r.: cross-border, AI, omnichannel, chatboty... - Omnichannel News). Personalization became a key term: chatbots began using customer data to offer products tailored to individual needs. For instance, a returning customer could be shown new arrivals from a favorite brand or prompted to repurchase a complementary item from a previous order. Bots also became more effective salespeople – many stores used them not only reactively (to answer questions), but proactively for upselling and cross-selling, i.e., suggesting more expensive items or additional accessories that matched the cart contents. For example, if a customer inquired about a phone model, the chatbot could immediately ask whether to add a case or headphones to the order. In 2023, a new trend emerged: connecting chatbots with other parts of the sales ecosystem, such as enabling payment and order completion directly within the chat window. Although full transaction finalization within the chat was not yet widespread, some integrations allowed for sending quick payment links or generating an order in the system after customer confirmation. Another increasingly common function was post-sale support: chatbots helped users file complaints or return items (e.g., guiding them through the required steps, providing downloadable return labels, etc.). Naturally, all these new capabilities were based on the increasing “intelligence” of bots – thanks to machine learning, they could learn from conversations, recognize customer intentions more accurately, and understand more complex questions. In summary, by 2023, an e-commerce chatbot could perform multiple roles simultaneously: customer service consultant (answering FAQs, checking order status, handling technical issues), sales advisor (suggesting products and promotions), and customer care agent (facilitating returns, gathering post-purchase feedback).

Expectations of Stores and Users During this period, the quality expectations for chatbots increased significantly. As more stores adopted similar solutions, businesses wanted to stand out by offering a better conversational experience. As a result, there was a growing expectation that a modern chatbot should “sound like a real person,” meaning the conversation would feel more natural and less formulaic (E-handel w 2023 r.: cross-border, AI, omnichannel, chatboty... - Omnichannel News). Companies paid close attention to refining the bot’s language and tone of voice to ensure it matched the brand image and helped build positive customer relationships. Large online retailers also began to demand multilingual support from chatbots, driven by the cross-border trend (expanding into international markets). The ideal bot was expected to respond fluently in Polish, English, or Czech – depending on the customer’s location – thereby supporting international sales efforts (E-handel w 2023 r.: cross-border, AI, omnichannel, chatboty... - Omnichannel News). Another key expectation was measurable effectiveness: businesses wanted to see concrete results, such as increased sales conversion rates or a reduction in the number of conversations requiring human intervention. This led to greater focus on conversation analytics and performance indicators such as the percentage of cases resolved by the bot (known as FCR – first contact resolution) and the average handling time per conversation. Meanwhile, users in 2022–2023 had become much more accustomed to interacting with chatbots. Many customers expected that the first response after opening a chat window would come from a bot – and in many cases, they preferred this approach for simpler issues, associating it with quicker resolution. Thanks to improvements in AI, frustration caused by miscommunication decreased – bots were less likely to respond with “I don’t understand the question,” which helped build trust in this support channel. Of course, the option to talk to a live agent remained essential. By 2023, it had become standard for chatbots to respect customer requests to “talk to a human” at any time – either transferring the conversation to an available agent or logging the request for follow-up. User expectations were also influenced by the growing popularity of voice assistants (like Google Assistant and Siri) – consumers began to seek similar convenience in e-commerce, such as speaking their question instead of typing or receiving a voice reply. Not all stores were ready for this, but the direction was clear: increasingly natural, “human-like” interactions. In summary, by 2022–2023, the chatbot was no longer seen as a gimmick, but as a fully-fledged part of customer service and sales – subject to clear business requirements (higher sales, improved customer satisfaction) and expected to keep pace with a dynamic environment (multilingual support, personalized communication, etc.).

Implementation Examples (2022–2023) During this period, virtually every major e-commerce platform in Poland had already implemented some form of chatbot. Allegro, the largest marketplace, launched an improved assistant to support users in its Help Center, automatically answering questions about orders, payments, and returns. Empik – the market leader in books and multimedia – deployed a bot that helped users navigate the store and recommended products from various categories based on customer preferences. InPost significantly expanded its parcel service chatbot – by 2022, it was one of the most recognizable bots in Poland, used by hundreds of thousands of users to track packages or retrieve pickup codes 24/7. IKEA Poland also employed a virtual assistant to answer product-related questions and provide availability information for stores – although it primarily operates offline, many online customers received support through the chatbot (Chatbot w sklepie internetowym). Industry-specific solutions also emerged. For example, in 2023, the IdoSell e-commerce platform announced the development of its own AI “e-salesperson” tailored to stores using its system (E-handel w 2023 r.: cross-border, AI, omnichannel, chatboty... - Omnichannel News). Notably, in 2023, Polish digital agencies and software houses began developing GPT-3/ChatGPT-based bots for early-adopter retailers. These chatbots could generate unique responses even to unusual questions by leveraging vast language knowledge. While such projects were still pilot initiatives, they reflected a growing interest in using generative AI for e-commerce customer service. As for standout sectors – beyond fashion and electronics, which continued to use chatbots extensively – the financial and insurance industries (with products sold online) also invested in assistants for things like insurance or loan offers. However, in the core e-commerce space, fashion and footwear stood out as particularly effective use cases for shopping inspiration (e.g., suggesting outfits or collections), while the electronics and home appliance (RTV/AGD) sectors benefited from bots that helped filter large product ranges (e.g., “which 55-inch TV do you recommend?” – and the bot could list a few models matching the criteria). In any sector where the product range was broad and many technical questions arose, chatbots proved extremely useful in helping customers quickly find the exact information they needed.

The Years 2024–2025 – The Era of AI-Powered Chatbots (Current Phase)

In 2024–2025, we entered a new era—chatbots in e-commerce became more intelligent, self-learning, and even more tightly integrated with the sales process. We are now speaking of an era of assistants powered by generative artificial intelligence, capable of holding conversations that are nearly indistinguishable from those with a human. In Poland, as globally, 2024 brought a real boom in AI-driven solutions for commerce, with chatbots at the heart of these trends as a key element of the online customer experience. Solutions in use: The chatbots currently used in e-commerce are most often advanced AI platforms integrating multiple technologies. Many stores have upgraded their existing bots by equipping them with large language models (LLMs)—often based on the GPT family or comparable models—which has given them a much greater ability to understand context and generate responses. These chatbots can be trained on vast datasets (e.g., comprehensive product knowledge bases, store policies, manuals, customer reviews), enabling them to answer questions that were not explicitly pre-programmed. Integration with internal systems has become nearly standard in 2024–2025: bots are connected to product databases, CRMs, warehouse management systems, and store ERPs. This allows them to check real-time product availability, order status, or even estimate delivery times based on courier data. “AI sales assistant” solutions have also become accessible to smaller online retailers through SaaS platforms. In the Polish market, services have emerged that allow stores to deploy an intelligent bot in just a few steps—an example is IdoSell’s eSprzedawca AI, a product dedicated to online stores. This tool integrates with the store’s admin panel, analyzes product data and the store’s offering, and then independently handles conversations with customers (source). Importantly, modern bots not only react—they also learn and optimize: using machine learning mechanisms, they analyze every conversation and draw conclusions (e.g., if they often don’t know the answer to question X, they report it so the knowledge base can be updated). One could say that the chatbot of 2025 is a “living” product, continuously improved based on data, rather than a static program. Emotion and intent analysis is also playing an increasing role—some bots can recognize the customer’s tone (e.g., that they are upset due to a delayed delivery) and respond with calming scripts or escalate the conversation to a human consultant as a priority. In terms of channels, 2024 saw the further strengthening of the omnichannel trend: the same chatbot is available on the website chat, mobile app, messaging platforms, and—newly—via voice channels. There are now integrations between text chatbots and voice assistants, enabling customers to talk to the bot over the phone or in a voice app (for example, Google Assistant now supports Polish e-commerce services in the Polish language). Technically, this involves combining a speech-to-text module (converting speech into text for the bot) with a text-to-speech module (reading out the bot’s response using a voice synthesizer). Although voice commerce is still in its early stages, it represents a clear direction for the market’s development. In summary, today’s AI chatbots are highly advanced solutions operating 24/7, connected to all essential company data, capable of self-improvement, and available wherever the customer is—whether typing or speaking.

Dominant features: The functionality of chatbots in 2024–2025 focuses on making the entire purchasing journey as easy as possible for the customer while boosting store sales. All previously common tasks (FAQs, product advice, post-sale service) are now handled more efficiently, but additional new capabilities have emerged. The chatbot has essentially become a virtual sales concierge, capable of managing the customer experience end-to-end—from the first question, through product recommendations and order assistance, to post-purchase care. In practice, this might look like the bot asking at the beginning of a conversation: “How can I help you? Are you looking for a specific product or need some inspiration?” If the customer expresses a need, the bot can ask a few follow-up questions (about preferences, budget) and then present personalized product suggestions—complete with images, descriptions, prices, and purchase links (source). This personalization happens in real time: the chatbot continuously analyzes the customer's responses and available data (such as browsing history, if accessible), and dynamically adjusts its recommendations. Conversational product search is another dominant feature—the customer can ask the bot in a very natural way, e.g., “I need a gift for a 5-year-old boy, around 100 PLN,” and the chatbot understands the intent, searching for relevant items (e.g., toys) that meet the criteria, narrowing down the options much faster than a traditional search engine. What’s more, bots can now offer contextual discounts and promotions. If they detect that a customer is hesitating or has a full cart but hasn’t completed the purchase, they can proactively suggest: “I see you’re considering these products. Here’s a 5% discount code to encourage your purchase—valid for one hour.” (source). Such personalized offers previously required human interaction (like chat-based negotiation), but can now happen automatically based on predefined AI rules. Post-sale support via chatbots has also become more advanced in 2024: bots can initiate contact after a purchase—for instance, asking for feedback, sending user manuals for purchased devices, or suggesting complementary items (e.g., offering printer ink some time after a printer was bought). Naturally, traditional customer service tasks remain fully supported—modern bots seamlessly answer questions about store policies, warranties, technical support, and more, often drawing from large knowledge bases, sparing the customer from digging through long documents. Finally, it’s worth mentioning reporting and analytics, which have become an integral “feature” of modern chatbots. E-commerce owners receive detailed data about interactions: how many customers were served, the most common inquiries, how many orders were generated by the chatbot. For example, IdoSell reports that as many as 15% of conversations conducted by their eSprzedawca AI result in a purchase (source)—a concrete metric that enables measuring the bot’s impact on sales conversion. This demonstrates that chatbots have become important “sellers” in their own right—generating a noticeable share of revenue, not just answering questions. In summary, the dominant feature of chatbots in 2024–2025 is their versatility combined with intelligence: a single assistant can do (almost) everything a customer needs in the shopping process—and does it in a personalized, fast, and on-demand way.

Expectations of Stores and Users: In the current period, expectations are very high—but to a large extent, they are already being met by modern solutions. Online stores expect a tangible return on investment from chatbots—the bot should not only reduce costs but actively drive sales. The guiding phrase has become “a chatbot that sells”, which is exactly what the aforementioned eSprzedawca AI and similar tools aim to deliver, integrating seamlessly into the sales process at every stage (source). It is now expected that a chatbot cooperates effortlessly with human teams—escalating issues only when truly necessary (with human agents increasingly focusing on atypical or high-value customers, while routine support is delegated to AI). A key expectation is also brand consistency: companies want their chatbot to reflect their brand's “personality” and use appropriate language (e.g., more casual for a youth-oriented brand, more formal for a luxury one). As a result, chatbot development now involves not just IT professionals but also marketers and copywriters, who teach the AI the brand's tone of voice. From the end-user perspective, the expectation is simple: even faster, smoother, and more convenient service. In 2024, customers have grown accustomed to resolving many issues instantly via chat—or even voice commands—and they expect stores to support this. A chatbot is expected to respond immediately and provide the correct answer on the first try. Tolerance for errors has decreased: if a bot doesn't know something or makes a mistake, users are quicker to give up—especially if a competitor does it better. Fortunately, thanks to advances in AI, modern bots rarely make mistakes on standard issues. And when they don’t know an answer, they can recover gracefully—asking clarifying questions or offering to follow up later. There is also growing demand for proactive behavior—some users appreciate when a chatbot offers help on its own or points out a relevant promotion while browsing (subtly, of course, without being intrusive). Finally, users now expect seamless cross-channel experiences: if they start chatting with a bot on their phone, they want to be able to continue on their laptop—with the bot remembering the conversation’s context. Thanks to cloud technology and integrations, this is often achievable—chat sessions can be continued across devices when the customer is logged in. In summary, for 2024–2025, both stores and customers treat chatbots as a natural part of the online shopping experience, expecting them to be mature and provide real added value. A modern chatbot should be fast, helpful, polite, and effective—in short, it should deliver a positive shopping experience that leads to greater customer loyalty and increased revenue.

Implementation Examples (2024–2025): The latest examples from the Polish e-commerce market demonstrate the capabilities of this generation of chatbots. Many stores operating on the IdoSell platform have begun implementing eSprzedawca AI—for instance, fashion retailers report that the bot recommends products with images and purchase links, and that as many as several percent of conversations with it end in a sale (source). Retail chains such as CCC have enhanced their chatbots with generative features—they can now respond to more open-ended customer questions, such as fashion trends ("What shoes are trending this spring?"), and suggest specific products in reply. In 2024, Allegro experimented with an AI-powered conversational search engine, where users could describe what they were looking for in full sentences, and the AI would help find the most relevant offers. While a slightly different context, it reflects the merging of chatbot, search, and recommendation technologies. Empik introduced an AI assistant in its mobile app that recommends books based on a brief conversation about reading preferences—an example of a specialized bot acting as a personal advisor. The grocery sector has also seen movement: some online grocery stores are testing bots that take quick shopping orders—the customer writes a shopping list in the chat, and the bot converts it into a cart with selected products. The insurance and banking sectors in e-commerce are also evolving: for example, banks selling products online have bots that guide users through credit card or insurance offers, using AI to explain complex topics in plain language. As for traditional e-commerce categories: fashion and beauty still lead in creative chatbot applications—offering personalized styling advice, or cosmetic bots that analyze a customer’s skin needs and recommend skincare products. Meanwhile, electronics and home/interior sectors use bots as intelligent technical consultants (e.g., answering questions about device compatibility or product specs—bots can pull accurate answers from knowledge bases, even quoting parts of technical specifications). It’s also worth noting that chatbots are beginning to appear in physical stores, in the form of kiosks or communication apps—for example, a customer in a brick-and-mortar store can scan a QR code and chat with a virtual advisor about a product, bridging the gap between online and offline (a phygital trend). In summary, 2024–2025 is the time when nearly every major e-commerce brand in Poland has its own advanced chatbot. The differences lie primarily in the level of AI sophistication and the creativity of use within specific industries.

Summary of Trends and Market Evolution Over the past decade, chatbots in Polish e-commerce have undergone an impressive transformation. Before 2022, they were mainly a novelty and a tool for handling simple tasks—online stores were experimenting with automating FAQ responses and testing whether customers would accept talking to a machine. Despite their limitations, the foundations for key benefits were already being laid: 24/7 availability, faster service, and cost reduction. In 2022–2023, chatbots matured and became widespread. They became ubiquitous in online stores, and their intelligence (NLP) significantly improved. As a result, bots began playing a greater role in sales—recommending products and building more personalized customer relationships. Stores started expecting real business impact (increased sales, cross-selling, customer loyalty), while users increasingly turned to virtual assistants as the first point of contact, appreciating their speed and convenience. Today, in the 2024–2025 period, we are witnessing full integration of chatbots into the e-commerce ecosystem and the use of state-of-the-art AI. Chatbots have become an integral part of customer service and sales strategies, offering high-quality, round-the-clock support. Thanks to artificial intelligence, they can engage in natural, in-depth conversations and directly contribute to business performance—for example, by boosting conversion rates or recovering abandoned carts. Trends indicate that this evolution will continue—chatbots will keep improving, potentially gaining even more human-like qualities such as emotional understanding, and integrating with new media (e.g., AI avatar video chats, or augmented reality experiences where the bot displays a product in AR while answering questions). Importantly, the Polish e-commerce market has unique local conditions—such as the Polish language and consumer behavior patterns. Domestic tech companies have risen to the challenge, delivering solutions tailored to our language and service culture. As a result, Poland is not lagging behind global trends—in fact, it boasts numerous successful chatbot implementations across different industries. Sectors such as fashion, footwear, electronics, and travel were early adopters of this technology and continue to develop it, demonstrating to other industries (like grocery or construction) the benefits of an interactive assistant. The effectiveness of chatbots has also been proven—numerous reports and case studies from the Polish market show that a well-implemented chatbot can significantly improve customer satisfaction and deliver a measurable return on investment. (See: Chatboty w e-commerce – jak sprawdzają się w sklepach internetowych? – Komerso.pl; Aplikacja eSprzedawca AI – chatbot, który sprzedaje za Ciebie – IdoSell) In conclusion, the chatbot market in Polish e-commerce has matured and evolved from simple FAQ bots into intelligent sales assistants. This technology is now accessible even to smaller stores and is increasingly expected by customers. Looking ahead, we can expect a continued fusion of AI and e-commerce—chatbots will become even more versatile, and the line between “bot” and “human” in customer service will continue to blur. For online stores, the key will be how well they leverage these capabilities to fully deliver on the promise: a better customer experience that leads to increased sales and loyalty. Polish e-commerce is already well on its way to fulfilling that promise, supported by a rich selection of chatbot solutions and growing knowledge of how to apply them effectively. Sources: The above information is based on numerous market reports, industry articles, and implementation examples, including the K2 Digital Transformation report Polskie chatboty 2018 (NowyMarketing), e-commerce guides (NowyMarketing, Komerso.pl), expert commentary from the IdoSell platform (E-handel w 2023 r.: cross-border, AI, omnichannel, chatboty… – Omnichannel News), and official communications from AI solution providers (Aplikacja eSprzedawca AI – chatbot, który sprzedaje za Ciebie – IdoSell).