As AI’s presence in our daily applications increases, the technology keeps getting smarter. Consider chatbots, for example. When they were first introduced, they responded based on how they were programmed for predefined inputs.
Chatbots in 2024, however, use AI to understand and respond to any message that comes in, just like humans. Chatbots are perfectly capable of simulating human conversations with the help of conversational AI.
Tech geeks can quickly tell the difference between chatbots and conversational AI. However, many people see them as similar and often use them interchangeably.
Conversational AI and Chatbots: What Are They?
Simply put, chatbots are the most popular application of conversational AI. Let’s dive deeper to explore more about why they’re different.
Conversational AI
Conversational AI is an umbrella term for technologies that help computers converse like humans. Natural language processing (NLP) and machine learning (ML) assist conversational AI in helping computers understand and respond to customer queries while learning from every interaction.
Conversational AI is still in its initial stage; in the future, it might have a human-like consciousness that would solve a broad range of problems. However, at present, it’s highly beneficial in:
- Increasing work productivity: Many contact centers use conversational AI software to make their agents more productive. The technology answers FAQs, cross-sells products, or gives simple advice while agents focus on the critical issues on their plates, delivering faster resolution.
- Improving accessibility: Conversational AI applications use text-to-speech technology to dictate or translate the output into the required language easily, reducing entry barriers for users who work with assistive technology.
- Automating workflows: Customer-facing teams can use conversational AI’s workflow automation while onboarding or between sales and service handoffs. Some businesses also leverage conversational AI as voice assistants in their interactive voice response systems, where they route calls based on customer responses and agents’ availability and skill set.
Conversational AI simplifies the way people interact with devices and interfaces. On the business front, it helps companies reduce the time and effort of using contact centers to address repetitive queries. It makes them more efficient and productive in handling larger customer or prospect interaction volumes with limited resources.
Chatbots
Chatbots are computer programs that simulate conversations with humans through messages or voice commands. There are two types of chatbots: rule-based and AI-powered.
Rule-based chatbots, also known as decision-tree bots, leverage a series of defined rules to interact with users. They solve common problems, and their rules are aligned with delivering the best solutions to those problems. These bots map conversational patterns like a flow chart. They’re designed by predicting the conversational flow the bot would have and how it would respond to it. These bots work within the scenarios you train them for.
AI-powered chatbots, on the other hand, understand a query’s context using NLP and respond accordingly. These AI agents have natural language understanding and natural language generation functionality that help them create responses. The agents leverage ML to improve with every interaction, helping them deliver more thoughtful answers as they mature.
Below are some ways chatbots help businesses:
- Support customers: Contact or call center teams have more time to address critical issues when text-based conversational AI chatbots address customers’ simple, repetitive queries. It reduces wait times while improving the overall customer experience.
- Generate leads: Users can leverage chatbots for lead generation. A chatbot becomes a text-based virtual agent that helps prospects on your website get answers to their queries. The chatbot can help a prospect set up a demo or navigate to specific content that can best address their queries.
- Perform simple tasks: Chatbots help customers in e-commerce know their order status, schedule appointments in the healthcare sector, or deliver credit card bills in the finance industry. When they go beyond simple tasks and perform activities like reminding you about a coming deadline, chatbots transform themselves into intelligent virtual assistants.
You might see a thin line between conversational AI platforms and chatbots. Think of chatbots as one type of conversational interface where bots receive and respond to user questions using AI, simulating human interactions. However, this is also true in the case of AI chatbots. Rule-based chatbots are completely different from conversational AI.
Key Differences Between Conversational AI and Chatbots
Take a look at these differing aspects of both technologies:
Complexity
Conversational AI technology is much more complex compared to traditional chatbots. The former uses ML to simulate conversations similar to interactions in human language.
On the other hand, rule-based bots rely on preprogrammed responses to respond to customers.
Understanding
Conversational AI apps can easily detect the user intent behind a query and adapt their responses accordingly. As AI systems deliver and improve their understanding of user inputs with time, they deliver a better user experience.
In contrast, rule-based chatbots might struggle with complicated questions or deviations from scripted interactions. In such cases, chatbots hand over the conversation to a human agent who can better assist the customer.
However, when these handovers don’t happen seamlessly, it creates a poor customer experience.
Learning
Conversational AI learns from previous user interactions and improves over time using its ML capabilities. This helps the chatbot adapt to users’ messages as it has more interactions.
However, if you’re working with a traditional chatbot, you’ll have to make manual updates to help the bot improve its responses.
Strengths and Weaknesses of Conversational AI Solutions and Chatbots
Below are some of the strengths and weaknesses of the two technologies that should help you choose the best solution for your needs:
Strengths of conversational AI
Conversational AI solutions simulate natural and engaging human-like conversations. When you integrate conversational AI solutions with your CRM or customer data platforms, they create highly personalized responses based on previous conversations.
The technology is capable of handling complex questions and requests. However, when complexity goes beyond the scope of conversational AI, it allows the user to talk to a human agent. These applications make the transition seamless so customers don’t experience recognizable interruptions in conversations.
Moreover, conversational AI agents improve with time through ML, helping them better navigate customers’ complex requests.
Weaknesses of conversational AI
Conversational AI requires a significant upfront investment to develop and train. Some third-party applications can shorten this period, but it depends on budget constraints.
However, these investments have more returns when you consider how the conversational AI agent can automate complex inquiries and more complicated workflows for you. The return on investment will manifest in the increased efficiency and productivity of your customer-facing teams.
Conversely, conversational AI might not be suitable for all types of interactions. For example, if you have set conversational flows that you want to automate, a rule-based chatbot will better suit your use cases and help you maintain control over budgets.
Strengths of chatbots
In some use cases, traditional chatbots are better than conversational AI chatbots. They have unique benefits such as ease of setup and cost-effectiveness. You can trust them to handle routine tasks for you or respond to common FAQ from customers or employees.
Users can easily add these chatbots to websites, messaging applications, and other channels to improve customer service efficiency.
If your support teams don’t usually receive complex requests to address or want to automate responses to only specific topics, chatbots will be a suitable option for your use case.
Weaknesses of chatbots
Chatbots have a limited understanding of user intent, leading to frustrating experiences for users when they input complex questions. The responses from a rule-based chatbot might feel repetitive and impersonal, making it a less engaging and monotonous interaction for customers.
Basic chatbot software programs learn manually, making real-time adaptation based on live interactions difficult.
If you’re seeking a chatbot for customer support use cases, it’s advisable to go with AI chat support. Predicting the complexity of requests you’ll get when delivering an omnichannel conversational experience is tricky.
How to choose the best platform for your business
You should consider a few things when choosing the best platform to use in a business:
- Complexity: If you deal with simple and repetitive inquiries, it’s best to use a simple chatbot. However, as the complexities of your inquiries increase, so does the need for conversational AI to support customers with more personalization.
- Budget: Determine how much you are willing to spend. Conversational AI will require a significant upfront investment.
- Scalability: Consider how your needs might change in the near future. Think about your expansion plans and how you anticipate your customer base to grow. Account for the complexities that can arise in the future, like payment policies for different geographies or return policies for different categories of products you might add. Conversational AI scales well as the business grows.
As AI evolves, we’ll likely see hyper-personalization of interactions becoming an expectation of your customers. Conversational AI will help you cater to this and have a future-proof solution for your business.
Power Your Customer Conversations With Nextiva
Both conversational AI and chatbots have different strengths and weaknesses depending on their use cases in a business. You can choose the solution that best aligns with your company’s needs based on your use case.
Ideally, you should choose a solution that delivers the best conversational AI and chatbot capabilities. Such a solution will be future-proof when your company grows and customer expectations of AI bots change over time.
Nextiva delivers the best of conversational AI and chatbots to power your customer interactions at scale.
