Chatbots, virtual agents, and voice assistants have become a part of our daily lives. Whether it’s interacting with a company over chat or asking Siri a question on a mobile device, we’ve gotten used to using language to get things done. This is all thanks to conversational AI technology.
With conversational AI, we can get quicker responses to issues and questions, often without lifting a finger. This technology is powering different applications across a range of industries, like healthcare, customer service, human resources, and more.
In this post, we’ll get an in-depth look at conversational AI, including how it works, applications, benefits, and some examples of what this technology looks like today.
What Is Conversational AI?
Conversational AI is a type of technology that allows humans and machines to understand each other. This type of AI makes it possible for machines, like computers, to process human language and respond accordingly.
Whether the language is spoken or text, conversational AI is able to simulate human interactions to reply to inquiries. There are many ways conversational AI appears in our daily lives and in professional settings, such as chatbots and virtual agents.
How Does Conversational AI Work?
Conversational AI relies on a few main AI-powered language technologies to facilitate interactions between humans and machines. Each technology plays a part in handling a part of the conversation, whether it’s understanding, processing, or responding to language. Let’s break down the technologies that make up this process.
- Machine learning (ML) is the base of conversational AI. With ML, systems are trained on vast data sets that contain different samples of languages in all forms and using different patterns. This helps a conversational AI system learn and grow over time.
- Natural language processing (NLP) uses algorithms to understand human language. By learning the intricacies of language, such as sentence structure, grammar, metaphors, nuance, and more, NLP can accurately detect speech and text.
- Natural language understanding (NLU) is where comprehension comes into play. Using AI and ML, NLU algorithms can detect user intent and context in conversations. This helps a conversational AI system deliver accurate results that are based on a user’s intention, even if the language used can have different meanings.
- Natural language generation (NLG) comes in at the end of this process to create a response that’s contextually relevant to the original input. In conversational AI, NLG helps systems like chatbots provide clear, human-sounding spoken or text-based results.
What Are Some Different Types of Conversational AI?
Conversational AI comes in handy in many different ways, helping us find answers to common questions, check the weather, and even complete work tasks just by speaking or using natural text. Below are some examples of the different types of conversational AI that exist today.
Chatbots
Traditional chatbots have a bad reputation as conversational tools companies use to provide auto-responses that aren’t usually relevant. However, modern chatbots are based on language models and use AI to decipher the context of a conversation to provide targeted and accurate answers to complex queries.
Voice assistants
Alexa, Siri, and Google Assistant are all voice assistants that give users answers to their questions or help them complete tasks like setting reminders and alarms or noting down information. These technologies have become a part of our daily routines, and last year there were 149.8 million voice assistant users in the US alone.
Virtual agents
Advanced virtual agents can help users complete complex tasks, particularly in professional environments like IT support and customer service. For example, IBM Watson uses AI and ML to provide complex responses and data analytics based on user conversations and inputs.
Interactive voice response (IVR) systems
IVR systems are often used to route callers to the right agent or department in call centers or customer service scenarios. Using AI and other language recognition technologies, IVR systems can also offer automated responses to natural language queries, freeing up agents and reducing wait times for customers.
Popular Use Cases of Conversational AI
Conversational AI is reshaping interactions in many industries while improving user experiences and making operations more efficient. Below, we’ll look at some common use cases for this technology.
1. Online customer support
Conversational AI is powering new tools like chatbots and virtual agents. These technologies are allowing companies to provide around-the-clock service and solutions to issues without involving any agents, reducing workloads and improving response times. Customer service software solution, Zendesk, offers AI-powered chatbots that can resolve tickets without any agent intervention.
2. Accessibility
Thanks to the hands-free nature of conversational AI, individuals with disabilities can more easily control different devices like mobile phones, computers, and smart home devices. With speech-to-text functionality and voice commands, it’s possible for people with accessibility challenges to complete the same actions as able-bodied people. With Amazon Alexa, anyone can use voice commands to control smart home devices or even complete online orders.
3. HR Processes
AI-powered systems can parse through text in job applications to sort through mountains of applicants and focus on the right ones. This can make recruiting more efficient when big companies have hundreds or even thousands of applications to go through for one role.
4. Healthcare
Patient care can also be improved with conversational AI as it can help reduce the workload on staff members by scheduling appointments and offering basic health information. With conversational AI, doctors and nurses can also create summaries just by speaking, making it easier to log and file reports on patient conditions and progress. For example, Hyro is a conversational AI for the healthcare industry that helps teams improve patient engagement.
5. Internet of Things (IoT) Devices
As we saw earlier, conversational AI systems can connect with linked IoT devices to allow for seamless control. Smart home devices like light systems and appliances can be controlled by voice with conversational AI, and the same can be done in professional settings. With Google Assistant or Alexa, anyone can say a command such as “turn on the lights in the bedroom” to control an IoT device.
Why Do You Need Conversational AI in 2025?
The short answer: to stay competitive, work smarter, and offer better service. Beyond that, there are countless benefits to conversational AI that will supercharge your business and allow your team to work more productively.
Research from IBM shows that 97% of customer service providers acknowledge that using virtual agents powered by conversational AI has a positive impact on customer satisfaction. If your company isn’t using this technology yet, it risks falling behind the competition. Here are a few key benefits of using conversational AI:
- Improved customer experience: Provide instant answers through different channels for better customer satisfaction
- Increased sales: Customers who are more engaged by human agents or conversational AI with personalized recommendations and proactive support are more likely to convert and stay loyal
- 24/7 availability: With round-the-clock service, conversational AI can do the heavy lifting while your staff is away or preoccupied
- Cost savings: By automating repetitive tasks, you can minimize the need for a large workforce and cut down on operational costs
- Scalability: Conversational AI systems can be scaled as needed to handle higher volumes in busy seasons or as your business grows
- Personalized interactions: Data analytics can help tailor responses to create meaningful and relevant conversations
- Data insights: Analyze each interaction to discover trends, customer preferences, and metrics that can inform decision-making and improve performance
Optimize Operations with Conversational AI Like aiOla
Conversational AI helps companies improve operations across the board. Whether customer-facing like improving service with quicker responses, or for internal business procedures by using natural language to create summaries or access and collect data, conversational AI can change the way we work.
With platforms like aiOla changing the way frontline workers complete tasks through speech AI, companies can make the most of this technology without disrupting their existing workflows. aiOla can empower employees with conversational AI that allows them to speed up processes by reducing manual workloads, stay safer by keeping their eyes on their work, and collect data that can inform high-level decisions and increase productivity.
Book a demo with one of our experts today to learn more about how aiOla can help your business with conversational AI.
