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Top Differences Between Conversational AI vs Generative AI in '24

Updated on Feb 22
3 min read
Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is 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 focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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Top Differences Between Conversational AI vs Generative AI in '24Top Differences Between Conversational AI vs Generative AI in '24

AIMultiple team adheres to the ethical standards summarized in our research commitments.

Conversational AI and generative AI have been growing in adoption and popularity:

At first glance, these tools seem similar to each other. For instance, both conversational AI and generative AI models can generate answers, but how they do that differs. Therefore, we should carefully study conversational AI and generative AI’s distinct features.

Given that 60%1 of organizations are concurrently implementing four or more hyperautomation initiatives, not fully understanding the differences and similarities of the tools you’re investing in restricts your returns.

In this article, we will:

  • Explain the differences between conversational AI vs generative AI
  • Discuss how they can be jointly used
  • Provide a list of tools that leverage both conversational AI and generative AI

What is conversational AI?

Conversational AI (or conversational artificial intelligence) uses:

To create intelligent systems, such as chatbots, voice bots, and intelligent assistants, capable of engaging in natural language conversations and providing human like responses. This versatility means conversational AI has numerous use cases across industries and business functionalities.

What is generative AI?

Generative AI focuses on creative content generation, as its primary function. It can generate output across 70+ applications in text, image, music, or video format, thanks to:

What are the differences between conversational AI vs generative AI?

Conversational AI systems are generally trained on smaller datasets of dialogues and conversations to understand user inputs, process them, and generate responses in text/voice. Therefore, output generation is a byproduct of their main purpose, which is facilitating interactive communications between machines and humans.

Generative AI tools, on the other hand, are built for creating original output by learning from data patterns. So unlike conversational AI engines, their primary function is original content generation.

So generative AI is a more flexible tool by creating content in different formats, whereas conversational AI tools can only communicate with users.

How can conversational AI and generative AI be used together?

By combining:

  • Conversational AI capabilities for language understanding
  • Generative AI capabilities for original output generation

We get a conversational AI chatbot with generative AI capabilities, trained on trillions of data and topics, understands your questions and generates responses as text, video, music, or picture.

What are some tools using both conversational and generative AI features?

We created an alphabetical list of 5 tools that leverage both conversational AI and generative AI capabilities. Note that not all of these intelligent chatbots serve identical use cases.

1. Bing Chat

Bing Chat can:

  • Generate images by using DALL-E
  • Answer questions by searching the web
  • Give exact sources for its answers, thus being more usable for researchers and academics

2. ChatGPT

ChatGPT is arguably the most popular tool on our list. It can:

  • Answer questions, by using its training, in different languages
  • Give suggestions and recommendations
  • Write essays and songs
  • Generate and debug codes
  • Integrate with other applications with plugins

3. Character.ai

Character.ai is a novelty tool in beta mode that allows you to talk with historical and prominent figures, as well as fictional characters. However, Character.ai could still be used in:

  • Education: Teaching history or culture through storytelling and dialogue.
  • Marketing: Generating catchy slogans, headlines, or descriptions for their products or services through the mouth of a historical or fictional character.

4. Jasper.ai

Jasper.ai, with its flagship AI-writing tool, is more tailored towards writers, copywriters, bloggers, and students. But it also has a chat feature, similar to other tools on our list, for back and forth communication.

For more on conversational AI and generative AI

To learn more about conversational AI and generative AI, read:

And if you are looking to invest in one these solutions, visit our data-driven lists of:

If you have more questions, don’t hesitate to contact us:

Find the Right Vendors

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

Cem Dilmegani
Principal Analyst

Cem is 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 focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology 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.

Sources:

AIMultiple.com Traffic Analytics, Ranking & Audience, Similarweb.
Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
Data management barriers to AI success, Deloitte.
Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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