AIMultiple ResearchAIMultiple Research

In-Depth Guide to 5 Types of Conversational AI in 2024

Cem Dilmegani
Updated on Jan 12
4 min read

Conversational AI is any software that a person can talk to, whether it is a chatbot, social messaging app, interactive agent, smart device or digital worker. These solutions allow people to ask questions, find support, or complete tasks remotely.

Despite the fact that there are numerous conversational AI/chatbot solutions available to organizations, not all of them are suitable to your organization’s needs due to their different characteristics. This article divides conversational AI into five primary sub-categories in an effort to assist executives in finding appropriate conversational AI solutions. 

1. AI chatbot / conversational AI system

AI chatbots use machine learning and natural language processing (NLP) to lead a conversation with the user. AI chatbots generate their own answers by analyzing the user’s intent and goal of the conversation. 

AI chatbots have the following benefits:

  • They serve complex customer queries thanks to both more advanced conversational capabilities and intent understanding.
  • They support digital workers that can understand employee queries and assist them to complete tasks.
  • Customize the conversation language according to the user. For example, they can speak in a fun or formal way.
  • With multilingual datasets available for training NLP models, AI chatbots can be programmed to recognize different languages.

2. Rule-based chatbot

Rule-based chatbots map out conversations like a flowchart via a series of predefined rules designed to solve specific problems or achieve particular goals. 

Rule-based chatbots have the following benefits:

However, rule-based chatbots are typically

  • not flexible, limiting the conversation flow and personalization
  • hard to maintain especially when many rules are added to the system

3. Hybrid chatbot 

Hybrid chatbots combine both AI and rule-based benefits such that they are trained to say specific things in response to user queries but can also leverage NLP in order to understand the user’s intent. 

For example, via machine learning or an extensive rule-set, the chatbot can infer that the user is referring to the BBVA bank in Turkey, even if they use different names, such as: 

  • Garanti BBVA (Current brand but it is less rarely used in conversation since it is long and includes a combination of words from different languages)
  • BBVA (Brand of investor)
  • Garanti (Previous brand)

Hybrid chatbots overcome some of the constraints of rule-based chatbots. However, rules can become difficult to maintain as the bot complexity increases.

Please note that it is hard to categorize bots between hybrid and AI categories since most bots rely on some rules. You can consider hybrid chatbots to be the same as AI chatbots for simplicity.

4. Voice bots / assistants

Voice assistants convert voice commands into machine-readable text in order to recognize a user’s intent and perform the programmed task. 

For instance, an HR employee can ask the digital assistant to fetch data about a specific employee without needing to manually search for this information. 

Some of their benefits include:

  1. Hands-free interaction: With voice and mobile assistants, users don’t have to go to a search engine and type their question, nor do they have to go to a note app to take notes. Instead, they  can issue such commands with their voice. Amazon’s Alexa can be the best example for such an interaction.
  2. Integrations: Once the purpose of the command is verified , the voice bot can use a variety of services (e.g. search engines, IoT applications, such as smart thermometer, etc.) to carry out the command. This is particularly helpful for users relying on a pure voice interface since they may not be able to access other systems via a voice interface.

5. Interactive voice assistants (IVA)

Interactive voice assistants (IVA) are an automated phone system technology that allows incoming callers to interact with a computer-operated phone system through the use of voice and keypad input. Interactive voice assistants are used for banking, retail orders, utilities, travel information, and weather conditions. Their benefits include:

  1. Call routing: IVA is able to route calls to specific departments, either based on voice commands or keypad entry.
  2. Support for rush-hours: IVA offers businesses the ability for their callers to self-serve and leave messages. During busy times, IVA can help employees by taking over mundane tasks like answering FAQs, following up on order status, or tracking shipments.

What are examples of conversational AI?

The following are the case studies of conversational AI in practice:

Chatbot: Bank of America

In 2018, Bank of America introduced Erica as its AI chatbot. Erica helps customers with simple processes like paying bills, receiving credit history updates, viewing account statements, and seeking financial advice. 

Banking chatbots improve the customer experience by streamlining such mundane processes that people usually don’t like to spend much time on (e.g. navigating through different web pages , constantly entering repetitive account details, etc.). By the year’s end, Erica was reported to have had interactions with 19.5 million enquiries and achieved a 90% efficiency in answering users’ questions.

Chatbot displaying account balance and offering advise

To learn more regarding conversational banking you can read our Conversational Banking: Everything You Need to Know article.

Voice assistant

Stanford University conducted a study, pitching professional typewriters against voice assistants. The researchers found that voice assistants were 3 times faster than typewriters in transcribing English and 2.8 times faster in Chinese. In addition, the error rate was 20.4% lower in English and 63.4% lower in Chinese.

For more on conversational AI and chatbots

To learn more about conversational AI and chatbots, read:

If you believe your business will benefit from conversational AI, feel free to check our conversational AI hub, where we have data-driven lists of vendors.

And we can guide you through the process:

Find the Right Vendors

This article was originally written by former AIMultiple industry analyst Bardia Eshghi and reviewed by Cem Dilmegani.

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
Follow on

Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

To stay up-to-date on B2B tech & accelerate your enterprise:

Follow on

Next to Read


Your email address will not be published. All fields are required.