AI-assisted text chatbots have made their way into the landscape of e-commerce and online services. They offer help on bank and auction sites, answer questions about restaurant menus on Messenger, provide entertainment and even take care of our health. How have chatbots changed with the spread of AI?
AI-assisted text chatbots – table of contents:
- How do AI-assisted text chatbots work?
- Examples of using AI-assisted text chatbots
Chatbots without AI support are based on rules entered manually by programmers. They display appropriate texts in response to keywords. The problem arises, however, if the customer does not use the right word, or if the chatbot does not include an algorithm to understand the contextual question, for example, “Will the stationery store be open the day after tomorrow?”. In such a situation, the chatbot repeats the request to change the query over and over again or redirects the customer to talk to a consultant after several attempts. Such problems in new-type chatbots are solved by implementing artificial intelligence.
How do AI-assisted text chatbots work?
AI-assisted text chatbots operate on completely different principles than their predecessors. The new chatbots learn by interacting with customers through the use of new technologies:
- Natural Language Processing (NLP),
- Machine Learning (ML),
- Deep Learning (DL)
Because of this, interactions with them feel more natural to customers, while the chatbots themselves become more perfect with their application. Over time, they learn the language used by customers, for example, recognizing and understanding abbreviations, or colloquial product names. AI-based chatbots also correctly interpret words containing typos.
A new chatbot using artificial intelligence can also be taught using a record of conversations conducted by a legacy bot. This is very important for the continuity and consistency of business and customer communication. On the other hand, from the very beginning, the chatbot’s interactions with customers provide valuable material for user experience research thanks to its ability to analyze the emotional overtones of the conversation (Sentiment Analysis).
Such a solution, although very modern, does not have to weigh heavily on a company’s budget at all. This is possible because you don’t need to create a separate technology solution for each company. You can use an AI-assisted chatbots using the AIaaS model and teach it to work on your database.
Of course, implementing an AI-based chatbot also requires time and work from a specialist. However, its operation can produce very tangible business results that are difficult to compare with those of rule-based bots. An example of the difference between the way a rule-based chatbot works and a chatbot using AI is illustrated by the following excerpt from a dialogue:
The quoted dialogue shows the flexibility of a chatbot using AI – from the short question “What time do you close?” it guesses from the context that the question is about the store’s operating hours and today’s day. Such a chatbot can also be taught to answer in a specific style that sustains the impression of a conversation with a specific person.
Examples of using AI-assisted text chatbots
The role of chatbots in a business context is growing. Most often, they function as virtual salespeople greeting customers as soon as they enter an e-commerce site. They also improve the experience of customers using large-scale websites whose reach would make it too expensive to be served by assistants. An even more advanced application of text chatbots is to use them for detailed, personalized product presentations.
AI-assisted chatbots are also used to carry on conversations with customers on WhatsApp, Messenger and other popular messengers, as well as used as standalone applications. Of particular note is the use of chatbots for:
- preliminary medical diagnosis – after describing symptoms, the chatbot asks additional questions that allow a doctor or pharmacist to quickly select the appropriate treatment
- supporting training and learning – an interesting example is SimbiBot, which helps students prepare for exams by asking questions, correcting answers and giving advice on learning
- assisting the elderly – to hold casual conversations, but also to remind them of important dates and activities.
Chatbots operating with artificial intelligence are very different from their rule-based predecessors. They can answer questions contextually, make inferences based on incomplete data, and provide expert care and advice to customers, for example, when using e-commerce. However, their application potential is much broader – they can dock customer needs, provide training, or act as assistants.
AI in business:
- Artificial intelligence in business - Introduction
- Threats and opportunities of AI in business (part 1)
- Threats and opportunities of AI in business (part 2)
- AI applications in business - overview
- What is NLP, or natural language processing in business
- Automatic document processing
- AI and social media – what do they say about us?
- Automatic translator. Intelligent localization of digital products
- AI-assisted text chatbots
- The operation and business applications of voicebots
- Virtual assistant technology, or how to talk to AI?
- Business NLP today and tomorrow
- How can artificial intelligence help with BPM?
- Will artificial intelligence replace business analysts?
- The role of AI in business decision-making
- What is Business Intelligence?
- Scheduling social media posts. How can AI help?
- Automated social media posts
- Artificial intelligence in content management
- Creative AI of today and tomorrow
- Multimodal AI and its applications in business
- New interactions. How is AI changing the way we operate devices?
- RPA and APIs in a digital company
- New services and products operating with AI
- The future job market and upcoming professions
- Green AI and AI for the Earth
- EdTech. Artificial intelligence in education