Businesses are adopting conversational technologies to improve experiences for both internal employees and external customers. Conversational platforms are one of the most common uses for AI applications. Businesses aim to improve customer experience and also reduce costs, by integrating the right conversational AI technology.
What is Conversational AI?
Conversational artificial intelligence is the technology that enables automatic messaging and conversation between computers and humans. It enables companies to launch chatbots and virtual assistants.
Conversational AI programs can communicate like a human by understanding the purpose in speech or text and imitating human speech. The ultimate goal of conversational AI is to become indistinguishable whether it is a computer or a human being. Designing the flows that sound natural is an important constraint of a conversational AI.
The benefit of conversational AI technology is that it offers customers a direct channel through which they can communicate naturally. The benefit of conversational AI technology is that it offers customers a direct channel through which they can communicate naturally. customers can ask questions through text or voice in order to find answers to their concerns.
Why is conversational AI important now?
Chatbots provides a faster, 24/7 available customer and employee experiences. With increasing competition and demanding customers, businesses need to rely on conversational AI to keep customer satisfaction high while keeping support costs low. Feel free to read more in our chatbot article.
Conversational AI is the intelligence behind chatbots and improvements in conversational AI will enable bots that resolve more complex customer or employee problems.
How is AI used in conversational platforms?
The simplest example of conversational platforms are structures that send certain outputs to specific inputs. However, thanks to machine learning, conversational platforms can handle a wider range of queries. Additionally, conversational AI systems can consider the context (i.e. the rest of the conversation) while determining the users’ intent and the response.
Natural Language Processing: NLP is a sub-branch of artificial intelligence that allows you to break down, understand, process and determine the required action. NLP is the engine that performs tasks such as dialog control and task prediction.
- Dialogue control: According to the general flow of speech, the perception of conversational AI is shaped and dialogue control modules are used to control pragmatic adaptations in order to make the conversation natural.
- Task prediction: Speech flow gives an idea about the intention of the user(to buy something) is estimated and his/her action is recorded.
Natural Language Understanding (NLU): NLU is an sub category of NLP that analyzes sentence structures in text and speak formats. NLU enables computer to interpret the meaning in intent with common human errors like mispronunciations or transposed letters. NLU engines are fed with big data and they need verification. Technology giants like Google improve these engines by using their data. For more information about NLU and NLU engine providers, you can read our extensive research on NLU.
Natural Language Generation (NLG): Another sub category of NLP, this technology enables the response generation to the user. In order for the speech to be persuasive and fluent, natural answers must be produced to the user. Feel free to search and filter top NLG vendor in our list.
What are the use cases for conversational AI?
Most common use cases include:
- Customer service
- IT service desk
- Sales support
For more info, feel free to read our research on conversational AI / chatbot use cases in business:
- Use cases by industry
- Use cases by business function or business functionality enabled by the use cases
What are conversational AI alternatives?
FAQ text vs FAQ chatbot: There is not much difference in using FAQ chatbots and providing FAQ as a text. Conversational AI is not needed when it comes to providing limited information. it may easier to navigate FAQs as text.
What are the things to pay attention to while choosing conversational AI solutions?
Conversational AI has to take many factors into consideration in order for the person to understand what they want to tell. At this point, artificial intelligence should go a little further and behave intuitively. In addition, the platform must be secure to protect personal data.
- Performance: The user’s intent must be understood, no matter how complex the sentence. The language supports must have a wide range. A multinational company should support many languages. For example, understanding spoken word in South East Asia is a challenge since
- There are more than 1,000 spoken languages in SEA
- In China, there are more than 20 dialects
- Security and Privacy: the platform must provide the security of customers’ personal information and security of the personal data. Let’s assume a bank has a conversational ai platform. The level of data security of the customer is directly related to the reputation of the company.
- Integration: The conversational ai platform must be integrated well into existing applications or systems. The testing frameworks and techniques are used to make sure everything is going well.
- User Interface: Providing a seamless platform for users will enable them to communicate with conversational platforms more often. Don’t hesitate to read some successful conversational UI examples and how to make this UI better.
What are the conversational AI companies?
A recent Gartner survey states that the market for conversational AI, chatbots and virtual assistants includes as many as 1,000 to 1,500 vendors worldwide.
- IBM Watson Assistant
- SAP Conversational AI
- Oracle Digital Assistant
- Amazon Lex
If you have questions about how conversational ai can help your business, we can help:
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