Top 12 Conversational AI in 2024: How It Works & Use Cases

Conversational AI market is expected to reach $1.3B by 2025, growing at a CAGR of 24%. However, there have also been numerous chatbot failures in late 2010s by first generation chatbots. Therefore, many enterprises decreased their conversational AI investments. In the 2020s, there has been significant improvement in conversational AI capabilities to first generation conversational technology, new generation chatbots are more successful.¹ Therefore, they can effectively improve experiences for both internal employees and external customers. 

Thus, the main objective of this article is to provide CEOs and executives with in-depth research of the most recent conversational AI technologies so they can make informed investment decisions.

Top 12 conversational AI platforms

Table features:

The table is organized by the number of reviews. We adopted a 3 stage screening process to determine the top conversational AI platforms.  

We evaluated the performance of the company and the platform by looking at criteria like the number of employees, reviews and average scores. Review numbers were calculated based on major platforms Capterra, G2 and Trustradius. Vendors with 10+ employees and 20+ reviews entered the list.

*Oracle Digital Assistant offers a wide price catalog.²

What is conversational AI?

Conversational AI 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 recognizing user intent and understanding the purpose in speech or text and imitating human speech (See Figure 1). 

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.

What are the benefits of conversational AI?

1. It provides clients with a direct line of communication via which they can communicate naturally. Customers can use text or voice to ask questions and get answers to their concerns 24/7.
2. Conversational AI allows digital workers to interact with employees via natural language. Employees use text or voice to request tasks from these digital workers. Digital workers rely on technologies like RPA and AI models to undertake these tasks. Thus, digital workers free up employees’ time to focus on creative tasks like determining corporate strategy, developing new products, or selling.

Why is conversational AI important?

Chatbots provide a faster, 24/7-available customer and employee experiences. With increasing competition and more 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 does a conversational AI platform work?

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 a subcategory of NLP that analyzes sentence structures in text and speech formats. NLU enables computers 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.

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 vendors in our list.

Our research compares different natural language platform providers, feel free to visit.

What are the use cases and applications of conversational AI?

Most common use cases include:

• Customer service
• IT service desk
• Sales support 
• Marketing
• e-Commerce 
• Digital workers

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 lines of  text on a webpage. Conversational AI is not needed when it comes to providing limited information. It may be easier to navigate FAQs as text.

What is the difference between conversational AI and chatbots?

Although conversational AI and chatbots are used interchangeably, it is important to recognize the difference.

Conversational AI is the core technology that enables chatbots and virtual assistants. It leverages AI and machine learning algorithms to allow its tools to understand human speech and generate meaningful responses. 

On the other hand, chatbots are tools which can understand users’ queries and generate responses, but not always via conversational AI. Many chatbots are rule-based and don’t leverage AI in deciding which answer to provide next.

To learn more about the differences between chatbot and conversational AI click here. 

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.

1. Performance

The user’s intent must be understood, no matter how complex the sentence. Moreover, he language supports must have a wide range. A multinational company will conduct business in many languages, and so the software it expects its conversational AI software to do the same. But in this specific example, understanding spoken word in SouthEast Asia is a challenge since

• There are more than 1,000 spoken languages in SEA
• In China, there are more than 20 dialects

2. 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. A data breach will expose the customers’ info that had been relayed onto the conversational AI solution, causing perhaps irreversible financial damage, lawsuits, and tarnishing the reputation of the bank in process. 

3. Integration

The conversational AI platform must be integrated well into existing applications or systems for quick problem resolution. This expands the range of activities the solution will be capable of carrying out. For instance, Tesla cars let drivers open the glove box (and use many other functions of the car) via voice commands thanks to its conversational AI integration.  

It is important to note that firms should test frameworks and techniques used to make sure everything is going well.

4. User Interface

Providing a seamless platform for users will enable them to communicate with conversational platforms more often. 

Further reading:

Feel free to explore some successful conversational UI examples and how to make this UI better.

Feel free to check out our data-driven article for more chatbot companies.

For more on conversational AI

If you have questions about how conversational AI can help your business, we can help:

External Link:

External Links

• 1. “Chatbots: The Great Evolution To Conversational AI Compared” Forbes. Retrieved on November 23, 2023. 
• 2. “AI Pricing” Oracle. Retrieved on November 23, 2023.