The world of artificial intelligence is rapidly merging with the real world. The ever evolving and expanding AI sector has many technologies under its umbrella. Two of these types are Gen AI and conversational AI, known for their widespread use in daily life. When many organizations are shifting towards implementing AI solutions in their workflow, it is important to know the types, purpose, functioning, and use cases of these technologies. A basic knowledge of AI technologies can help business owners adopt the right tools and combinations for their desired results. In this blog, let us break down Generative AI vs Conversational AI to understand how these technologies differ from each other.
Overview of Generative AI and Conversational AI
Both generative AI and conversational AI leverage Natural Language Processing (NLP) and large language models (LLMs) for their functioning, but they serve different purposes. Generative AI turns your ideas and imagination into a reality by generating new content like texts, code, images, music, etc. On the other hand, conversational AI focuses on human-to-machine interactions. It tries to engage users with human-like conversations.
The Fundamentals of Conversational AI and Generative AI
Even though both generative AI technology and conversational AI use NLP, their functioning differs significantly. Let’s dive deeper into the fundamentals of generative AI vs conversational AI.
What is Conversational AI?
The main goal of conversational AI is to enhance humans’ interaction with computers using natural language. It can read and understand human language, pick up important details from the interaction, and also understand the emotion behind the interaction. This type of AI is usually seen in chatbots, AI virtual assistants, and other places that require human interactions.
What is Generative AI?
Compared to other forms of AI, generative AI is distinct. The term “generative AI” describes a system that can produce unique and creative material. To teach itself and mimic human ingenuity, it uses a significant amount of data. This makes it possible for generative AI to produce completely realistic and new content that appears to have been created by humans. It may generate a wide range of content, including code, music, synthetic data, text, and graphics. The main goal of generative AI is to create new things.
Generative AI vs Conversational AI: Key Differences
To effectively use AI technology in business growth, it is important to understand its differences. Conversational AI works best for interactive purposes, like in customer service, while generative AI boosts innovation in various fields. Here are the key differences between Generative AI vs Conversational AI:
Core Function
Generative AI’s core function is generating various forms of new content like text, images, and sound. On the other hand, conversational AI focuses on enhancing human-machine interaction through domain-specific dialogue.
Use Case
Conversational AI is used in functions like customer service, virtual assistance, and chatbots. While generative AI is used to create new content like writing fiction, creating ad copies, marketing content, and generating code.
Learning and Training
The training data required for conversational AI includes large datasets with human inputs, interactions, user queries, and responses. On the other hand, generative AI uses large and varied data sets to study patterns of content and then utilizes them to create original content.
Input and Output
Humans input data in conversational AI for a response, and in generative AI, the input data is used to create new content rather than a response.
Use Cases of Generative AI vs Conversational AI
The best way to differentiate and understand Generative AI vs conversational AI better is by exploring their use cases. Once we can relate to the real-world application of technologies, it is easier to understand them. Let us see how both Generative AI and Conversational AI work in the real world.
Generative AI Use Cases
Generative AI is rapidly making its place in various sectors with its impressive features. From banking and finance to the obvious beneficiary sector of marketing, generative AI is being adopted across industries. These are a few of the main industries where generative AI is being used.
Investment and banking
By altering the way banks provide customer service, generative AI is transforming the banking industry. GenAI technology can generate a personalized and successful savings plan by analyzing individual consumer data.
Healthcare
Generative AI in healthcare aids in monitoring genetic history and patient information for improved diagnosis. Additionally, it aids in the development of predictive diagnoses and individualized treatment regimens.
Insurance
In the insurance industry, generative AI can automate processes including document verification, underwriting, and claim processing. Generative AI technology can help insurance businesses save money and increase efficiency.
Drug Discovery and Pharma
The pharmaceutical and drug development industries are among the greatest places to apply generative AI. GenAI can accelerate drug testing and innovation by mimicking drug interactions and learning molecular behavior.
Conversational AI Use Cases
Conversational AI focuses on enhancing human interaction with machines in natural language. This technology is highly used in chatbots, virtual assistants, and other interactive platforms.
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Finance
Finance companies can use conversational AI for customer support chatbots. These chatbots can provide assistance as well as suggestions to customers. Quick response enables lower customer churn.
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Insurance
With conversational AI, Insurance companies can streamline their processes, like claims handling, policy inquiries, and insurance renewals.
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Healthcare
Unlike generative AI in healthcare, conversational AI is like a friend that schedules appointments, engages patients, solves their treatment-related queries, and also provides medication reminders.
Are Generative AI and Conversational AI exclusive of each other?
Conversational AI and generative AI are frequently combined in practical applications. In AI systems, they coexist and provide advantages of both. For example, while being a chatbot—technically conversational AI—ChatGPT uses both technologies to generate text, graphics, and code, much like generative AI.
Conclusion
Both conversational AI and Generative AI are subfields of broader artificial intelligence technology. Leveraging natural language processing, machine learning, and neural networks to generate content as well as to mimic human interactions, both of these AI technologies are quite advanced. With reliable AI development companies like AnavClouds Analytics.ai, you can harness the potential of AI for your business growth. Get in touch for a consultation session to understand the role of AI solutions in your organization.
FAQs
What is the difference between generative AI vs conversational AI?
The key difference between generative AI vs conversational AI lies in their core function. The main function of generative AI is to create original content, while that of conversational AI is to enhance human-machine interaction.
Is conversational AI better than ChatGPT?
ChatGPT leverages both conversational AI and generative AI for human interaction and generative content, respectively. So, ChatGPT has features of both the AI technologies and can be said that it is better than any one of the technologies it utilizes.
What are the four types of generative AI?
The major types of generative AI are generators, reimaginators, synthesizers, assistants, and enablers. These types of generative AI focus on different functions and altogether bring out the features of generative AI.
What is conversation AI?
Conversational AI is a technology that is dedicated to enhancing human interaction with machines in natural language. It leverages Natural Language Processing and LLM (large language models) for its functioning. Some examples are chatbots and virtual assistants.
What is better than generative AI?
Generative AI is by far one of the most advanced technologies humanity has created. However, if there’s something even more advanced and better than generative AI, then it is predictive AI. This technology can make predictions based on historical and real-time data. Predictive AI is considered even more advanced technology than generative AI.