Conversational AI vs. Generative AI: What’s the difference?

Let’s breakdown the differences between conversational AI and generative AI, and how they can work together to create better experiences for your customers.

While much of the public focus today has been on the power of generative AI to create new content, its cousin conversational AI has also quietly made great strides over the past decade.

These two distinct AI technologies have, in many ways, greatly affected how humans interact with machines due to their power to not only mimic natural human conversation but also automate everyday tasks and processes.

Let’s explore both technologies and how they can work together to deliver unique experiences to users.

What is conversational AI?

Conversational AI is a type of artificial intelligence (AI) that can simulate human conversation, for example chatbots for online customer support.

What is generative AI?

Generative AI is a type of artificial intelligence that can produce various types of content, for example text, imagery, audio and synthetic data.

Conversational AI vs Generative AI

Conversational AIGenerative AI
PurposeInteracting in human-like conversationsCreating new and unique content
LanguageUnderstands natural language and intentLearns language patterns to create new content
OutputResponses for chatbotsCreates images, text, music, etc.
Use casesCustomer support and serviceGenerating new content based on input

While both conversational and generative AI make use of natural language processing to output human-sounding replies, conversational AI is more often deployed in customer service and chatbots, while generative AI creates new and unique text.

With its smaller and more focused dataset, conversational AI is better equipped to handle specific customer requests. For example, a telco customer seeking help for a technical issue would be better served with a telco chatbot that already has a pool of solutions and answers specific to the problem.

OpenAI and Microsoft have partnered to deploy their Open AI models such as ChatGPT and DALL-E

Challenges with integrating generative AI into existing systems

Generative AI can be incredibly helpful to create conceptual art or generate content ideas for pre-planning. However, the output is often derivative, generic, and biased since it is trained on existing work. Worse, it might even produce wildly inaccurate replies or content due to ‘AI hallucination’ as it attempts to create plausible-sounding falsehoods within the generated content.

AI Hallucinations

When an AI model creates false or illogical outputs that aren’t based on any real data but presents the information as a fact.

It is not hard to find horror stories of integrated generative AI chat systems gone wrong, such as a New Zealand supermarket company finding out that its online AI meal planner was generating odd or inedible food recipes – one that could potentially produce deadly chlorine gas.

There is also an issue about intellectual property rights as such generative AI is dependent on vast datasets, some of which may not have approval from their original owners. Generative AI systems can also be easily exploited by users to produce frightening outputs, such as deep-fakes that imitate people’s voices to exploit banks and even family members.

It is up to brands and vendors to tame the generative AI beast and come up with ethical solutions that will allow businesses to use the technology in a safe way that offers elevated experiences to users.

How conversational AI and generative AI can work together

This doesn’t mean that conversational AI can’t work together with generative AI. ChatGPT, for example, uses conversational AI to output human-sounding replies, while the replies themselves are made from generated AI. Conversational AI can serve as virtual guardrails to ensure generated AI responses do not go off track while ensuring responses sound more fluid due to development in voice recognition and natural language programming.

Some brands are already experimenting with a limited form of generative AI within conversational commerce tools to create more unique and customized customer experiences in various industries such as retail, healthcare, tourism, and transportation.

Examples of merging conversational AI and generative AI

Bloomsy Box

In a recent collaboration with Masters of Code, a floral subscription company, Bloomsy Box, was able to launch a Mother’s Day campaign with a generative AI eCommerce chatbot that created personalized greeting cards to the winners of its daily floral bouquet giveaway.

By utilizing GPT-powered conversational experiences, brands can integrate an intelligent AI assistant without having to know a single line of code while customers receive unique contest experiences tailormade for them.


LAQO insurance and Infobip created a GenAI powered conversational assistant that can help answer customer queries and assist in insurance claims. The engaging AI chatbot handles 30% of customer queries with minimal hallucinations, making the AI solution both safe for users and efficient.

LAQO AI assistant

The AI assistant has transformed the way LAQO approaches customer service. Using both generative AI technology and conversational AI design, we have created a unique and user-friendly solution that meets the needs of insurance clients.

How conversational AI boosts businesses

The technology behind generative AI is still relatively new, so brands looking to utilize AI within their businesses would be better off with more mature and proven conversational commerce solutions to offer customers the best experiences.

Many APAC brands and organizations today already utilize conversational commerce solutions powered by conversational AI and the cloud, using Communication Platform as a Service (CPaaS) and Software as a Solution (SaaS) tools with their internal and external applications.


of APAC organizations plan to increase spending in conversational commerce solutions over 2023-2024 to provide more personalized customer experiences

It’s no surprise to see growing adoption of conversational commerce among businesses and even government organizations since conversational commerce can reduce customer service costs by upwards of 30%.

Finding a solution provider for conversational AI experiences

Integrating a brand new omnichannel CPaaS solution is never easy but fortunately, there are many experienced, well-established technology solution vendors that can help you get started with conversational commerce.

Infobip offers a wide range of solutions to aid and support in conversational transformation:

[ We are proud ]

Infobip is named a Leader in 2024 Gartner® Magic Quadrant™ for CPaaS

Infobip continues to invest in automation, frameworks around ChatGPT, and enhanced self-serve and security features. This is ideal for international customers seeking an experienced conversational commerce partner with a strong global presence.

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