- Conversational AI uses natural language processing and machine learning to enable machines to understand and respond like humans, powering tools from chatbots to virtual assistants.
- It operates by recognizing user intent, extracting key details, and generating natural language responses while learning from past interactions to improve over time.
- 62% of consumers prefer chatbots over human reps.
- Key benefits include 24/7 availability, scalability, personalized experiences, cost savings, fast responses, and valuable data insights for businesses.
As AI technologies rapidly expand in popularity, more organizations are considering using conversational AI to increase their bottom line and user experience.
Conversational AI entities like AI chatbots and AI agents can be used in endless use cases, from selling software to providing emotional support.
Let’s dive into the world of conversational AI – including how it works, real-world examples, and how to use it.
What is Conversational AI?
Conversational AI is a collection of technologies that enable machines to understand and respond to human language.
Using natural language processing (NLP) and machine learning, conversational AI is used to power AI agents, AI chatbots and AI assistants.
Conversational AI entities are commonly employed as voice assistants, customer support chatbots, information retrieval agents, or chatbots like ChatGPT.
How Does Conversational AI Work?
See also: How does an AI chatbot work?
Conversational AI is usually activated by user input – a user asking a question or making a demand.
The conversational AI agent identifies the user input and the intent behind it (using natural language understanding), including key details like dates or names.
Once it understands the request, the AI generates natural language that feels conversational and relevant.
Through continuous interactions, the AI refines its responses, learning from past exchanges to improve accuracy and adapt to user needs over time.
Common Use Cases of Conversational AI
Conversational AI is no doubt a transformative technology – but what exactly is it transforming?
Here are 5 examples of conversational AI:
1) Customer support
80% of consumers want the same 5 things from a customer service interaction – and conversational AI enhances all five.
Conversational AI is commonly used for enhancing digital customer experience (CX). Not only can they help scale operations, but they can assist sales teams and customer reps to do their job even better.
AI agents can provide experiences that feel personal, friendly, and efficient – exactly what customers want. In fact, 62% of consumers would rather use a chatbot than wait for a human service rep.
2) Sales and lead generation
Another common use for conversational AI is AI sales and AI lead generation.
You can think of AI lead generation tools – like chatbots and AI agents – as an employee that’s working around the clock. They can interact with website visitors, answering their questions, gathering their information, and directing them to relevant products or pages.
Conversational AI is used at every stage of an AI sales funnel, from advertising awareness to following up with customer post-purchase.
3) E-commerce
Conversational AI in e-commerce is popular for a reason. It improves the customer experience with 24/7 access and personalized recommendations, and it can streamline order processing for employees.
E-commerce AI agents often:
- Provide personalized product suggestions
- Track and provide updates on orders (71% of consumers prefer to chat with a chatbot when checking the status of an order)
- Send follow-ups about cart abandonment
- Send behavior-based promotions
4) HR and IT
On the rise in popularity are conversational AI agents for internal use – chatbots built by organizations for their companies.
HR chatbots often assist with onboarding, manage leave requests, process benefits inquiries, or provide policy information. They’re especially useful as enterprise chatbots, since larger companies have a high volume of HR requests.
On the other hand, ITSM chatbots can provide relief for internal IT requests, like resetting passwords or handling support requests.
6 Benefits of Conversational AI
1) 24/7 availability
Unlike human agents, conversational AI can operate around the clock, ensuring customers get answers anytime they need.
2) Scalability
AI can handle multiple interactions simultaneously, making it ideal for scaling customer support without increasing staffing costs.
3) Personalized experiences
With the ability to analyze and remember user preferences, conversational AI provides tailored responses, creating a more engaging and satisfying experience.
4) Cost efficiency
Automating routine tasks and inquiries can lower operational costs, freeing up human agents to focus on more complex issues.
5) Data collection and insights
Conversational AI gathers data on customer interactions, helping businesses better understand customer behavior, identify pain points, and refine their strategies.
6) Faster response times
AI-powered chatbots respond instantly, reducing wait times and improving customer satisfaction.
Components of Conversational AI
Conversational AI consists of several different AI technologies – here are a few of the most essential.
Artificial intelligence
Of course conversational AI is made possible by artificial intelligence.
At its core, AI is a simulation of human intelligence, used to complete tasks that previously required human cognition.
Conversational AI is AI that hones in on understanding and generating human-like dialogue.
Natural language processing
Natural language processing (NLP) is a branch of artificial intelligence that focuses on the interaction between computers and humans through natural language.
It enables machines to understand, interpret, and generate human language in a way that is both meaningful and useful.
Generative AI
Generative AI is a type of artificial intelligence that generates new content – like text, images, video, or music.
In the case of conversational AI, it typically generates text, but could also generate images or videos in specialized contexts.
Best Conversational AI Platforms
The easiest way to implement conversational AI – in your personal life or your professional workflows – is to use an AI platform.
Conversational AI platforms streamline AI setup and can jumpstart development, but choosing the right one matters.
When selecting from the best AI platforms, ensure you choose one that meets your individual needs.
Key features to look for include:
- Seamless integration with CRMs, analytics tools, and other systems
- Scalability
- Advanced analytics
- Multichannel support, so you can deploy across the web, social media, and messaging apps like WhatsApp
- Broad customization options
Deploy a Unique Conversational AI Agent
Botpress is a platform for building next-generation chatbots and AI agents.
It’s endlessly extensible, and integrates with everything. The opportunities are endless.
With high security standards, a built-in library of integrations and templates, and autonomously intelligent bot building, Botpress is the best way to build AI chatbots.
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FAQs
Is conversational AI the same as generative AI?
No, conversational AI is a broader category that includes technologies like NLP and dialogue management, while generative AI specifically refers to models that create content, such as responses in a conversation. Generative AI can be a component of conversational AI, but they’re not the same.
How is conversational AI different from a virtual assistant like Siri or Alexa?
Virtual assistants like Siri or Alexa are specific applications of conversational AI with limited, pre-defined capabilities, whereas conversational AI can be custom-built for a wide range of tasks across industries, offering more flexibility and domain-specific intelligence.
Can I integrate conversational AI into my existing mobile app or website?
Yes, most conversational AI platforms offer SDKs, APIs, or widgets that allow easy integration into websites, mobile apps, or messaging platforms.
How do you write effective prompts or scripts for AI chatbots?
Effective prompts for AI chatbots should be clear, user-centric, and goal-oriented. For writing effective scripts for AI chatbots, anticipating user needs, guiding the conversation naturally, and aligning with the chatbot’s tone and purpose are important considerations.
What accessibility features should be considered for conversational AI?
Some accessibility features that should be considered for considered for conversational AI include: ensure compatibility with screen readers, support for voice input/output, keyboard navigation, and use simple, inclusive language to accommodate users with varying abilities.
