Artificial intelligence makes it possible for us to communicate with our devices through natural language – simply by asking questions and formulating commands. In business, the most common application of a technology called conversational AI is the voice equivalents of chatbots, or voicebots answering questions about products and services. In today’s article, we will focus on the operation and business application of voicebots.
The operation and business applications of voicebots – table of contents:
Voicebots are based on voice interfaces. Until recently, they were mainly associated with tools that enabled visually impaired people to handle electronic devices. They read aloud the text visible on the screen and accepted simple voice commands. Unfortunately, their operation was very imperfect. It was difficult to understand sentences lacking intonation and rhythm, spoken word for word. The issuance of commands was also limited. Their recognition was determined by the sound characteristics of the pre-recorded command, so it could not be spoken by someone else. And the noisy environment made it virtually impossible to use the device.
Sound and meaning
When it comes to voice communication with devices, the rapid development of enhancement technologies has made a huge difference:
- speech recognition – which allows transforming speech into text (speech-to-text) understandable for the device
- speech synthesis – which is the spread of solutions that convert text to speech (text-to-speech)
It was their improvement that made possible today’s solutions known as conversational AI. Speech understanding alone, however, is only the beginning of the conversation. Indeed, conversations with artificial intelligence, although they seem to us the most natural way to communicate, are very complicated from a technological point of view.
The first challenge is the sound of the words, often spoken against a background of other sounds, such as urban bustle or music playing in the background. For artificial intelligence to answer a question, it must first extract and process our voice, or sound message. For this purpose, speech recognition is necessary. The sound received by the microphone is processed into text. This happens very efficiently through neural networks looking for a set of words that most closely match a pattern (pattern recognition).
The next challenge is to determine the meaning of the words, that is, whether the artificial intelligence understood the question. We wrote more about natural language processing and AI’s understanding of it in this separate article. Here we will only mention that it is hugely important not only to recognize the words but also:
- the language in which they were spoken
- the context
- emotional expression
Combining these solutions with the workings of artificial intelligence, Machine Learning (ML), Natural Language Processing (NLP), and the use of large-scale language models (LLMs), has radically changed the way machines understand language, and expanded the scope of their business applications.
Conducting voice conversations with artificial intelligence opens up a vast field for business applications of conversational AI.
The first frequently used solution using artificial intelligence coupled with a voice interface is call center operation. Banks and large-scale e-commerce often use it. This type of solution is also called dialogue AI. Such voicebots are also used for telephone marketing, although here, however, older-type voice automation still dominates. They often use pre-recorded longer portions of text by voice-overs. They are based on recognizing keywords in the customer’s speech. In response to them, they play back the relevant recording. In contrast, they are usually used to obtain personal information and make initial contact with potential customers.
A common and frequently used application is also the use of voice commands in-car navigation and in the smart home.
Educational and training applications of voicebots also have very interesting potential. They can help in:
- teaching foreign languages
- carrying out onboarding of employees
- effectively training new customers in the use of software offered by the company
However, the most recognizable role is that of a voice chatbot – a sales assistant available on websites or in-store applications. Its basic form is very similar to the functionality we wrote about for text bots. The simplest voice assistant in a store answers questions about products and store operations in voice form. However, more complex voicebots can combine functions:
- sales representative
- support department
Answering basic questions and redirecting the call to an employee only for tasks that are unusual or require a decision beyond standard operating procedures.
According to forecasts made by Gartner, by the end of 2024, 75% of companies using AI voice customer service pilot programs today will have implemented them permanently. For them, this means easier business scaling, reduced costs, and the ability to free up staff time to talk more freely with those customers who need a consultant’s support.
Finally, it is also worth mentioning artificial intelligence is trained simply to carry out conversations, rather than follow instructions and answer practical questions. One of its most interesting incarnations is Leta, the artificial intelligence that runs on the GPT-3 model. We will describe its operation and potential applications in more detail in an article on creative artificial intelligence.
Conversational artificial intelligence is capable not only of understanding speech but also of dealing with the context of spoken sentences and analyzing the intent and emotional expression of statements. Contacting voicebot-operated call centers and talking car navigation are already applications we encounter daily, while the future of voicebots is closely related to sales support, customer acquisition, and user support departments, as well as integration with virtual 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