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What is Conversational AI and How does it work?

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Conversational AI is a type of artificial intelligence that simulates human conversations to help customers solve problems. Usually, when talking about conversational AI, we refer to technologies such as chatbots or intelligent virtual agents (IVAs) that organizations use to improve their customer experience. 

Conversational AI has changed how customer service and contact centers operate. In previous years, organizations used limited and often frustrating interactive voice response systems (IVRs) to help their customers; IVAs are a much more dynamic and intelligent solution focusing on genuinely solving problems. 

This technology is possible given the combinatorial nature of technology at large. To mimic natural conversations, technologists generally combine natural language processing (NLP) and large language models (LLMs) with foundational information relevant to the organization. 

While the actual process for conversational AI technologies to function is much more complex, the following steps are often the standard:


  1. Input generation (reception). This is the input that users communicate to the machine. In the case of conversational AI, it would be the actual spoken words. 
  2. Input synthesis and analysis. In this step, natural language processing occurs, translating whatever the user says to information machines can successfully process, analyze, and compute. 
  3. Output generation. Depending on how the conversational AI is trained, the machine (LLM) generates the output that is most likely to help the customer. This can range from complex answers to simple responses or even additional information or repetition that may be required for the machine to improve its understanding of the conversation.
  4. Output delivery. Finally, the output delivery stage is where the requested output is sent to the user, moving along in the problem-resolution journey. 

Types and Use Cases of Conversational AI

As with all technology advancements, conversational AI is a vast field with multiple applications and use cases. While this fast-paced ecosystem is constantly evolving, below are some of the most common conversational AI subcategories organizations actively incorporate into their operations.

Conversational AI Systems

These systems are primarily focused on having the right conversations to solve all types of problems for end users. To do so, they are usually focused on NLP and LLM technologies orchestrated to increase call containment, thus solving more queries without any need for a contact center representative. 

Unlike some outdated IVR systems where users had to repeat themselves and learn to navigate a closed conversational system, these models focus more on having natural conversations around business needs. The training data can include human dialogue to help the machine better understand what the conversational flow may resemble. 

Conversational AI systems, in other words, are as close as you can get to having an intelligent machine that understands what your customers say and how to help them accurately.

Intelligent Virtual Agent

Organizations use intelligent virtual agents, commonly known as IVAs, to answer some of the most common customer requests. They generally use NLP to understand the information provided by users and are trained with a definite set of potential answers to solve simple customer questions.

IVAs are generally programmed using scripted rules combined with AI to handle customer conversations automatically. Once more complex issues arise, the IVA would transfer the interaction to a human representative who can make sense of the problem and provide an answer.  

Voice assistants 

While the lines between IVAs and voice assistants are blurry, the latter usually refer to software that uses voice recognition to help people with simple everyday tasks. Think of Alexa, Siri, or multiple other technologies that help us set alarms or get a weather forecast. 

The magic behind these technologies is that they convert voice messages into readable text to understand the user's intent and provide an answer. These are the precursors of more advanced conversational AI models. However, even though they may be more basic, they still use natural language processing, voice recognition, and synthesis to understand what is being said and provide an answer. 

Rule-based Telephony Systems 

Rule-based phone systems are the most basic conversational technologies that use specific rules to handle calls. The system is designed to decide what to do based on multiple scenarios, such as transferring a call to a customer representative, providing further possibilities via voice commands or touch-tone inputs, or sending it to voicemail after business hours. 

These systems were essential decades ago to improve customer service. They helped organizations respond to common issues without having people take calls all the time. By setting clear and all-encompassing rules, companies used these systems to solve problems and improve overall CX and information gathering.

Benefits of Conversational AI  

There’s a before and after implementing conversational AI for any organization. While multiple options and providers exist, the benefits are evident for companies trying to improve efficiency and customer satisfaction. 

It’s not a magical technology that can fix a broken experience, product, or service, but rather, a powerful way to enhance your teams to do their best work. 

Improved Efficiency and Productivity 

Implementing conversational AI to improve customer service helps your organization solve problems faster. This means happier customers, able to solve issues without having to be on hold waiting for the right rep to take the call, and a more efficient workflow overall. 

With conversational AI, your workforce is empowered to do the work that matters most instead of having to solve repetitive queries that can be easily solved without human intervention. This means more efficient and productive use of your talented customer representatives, allowing them to focus on high-impact conversations. 

Reduced Cost

Multiple studies state that companies can save up to $8 billion annually simply by reducing customer service costs by implementing conversational AI and chatbots. Solving multiple problems simultaneously without having to invest in a large workforce is one of the most significant ways in which conversational AI can help streamline operations. 

Furthermore, with conversational AI, you can provide support any day, anytime, and even reroute calls with more complex issues to the right customer representative.

Scalability

A vital advantage of implementing conversational AI is the ability to scale quickly. Growing means that your customer interactions also increase—sometimes at a rate that you can’t anticipate or prepare for. 

Hiring and training new staff tends to be costly and time-consuming. You’re also prone to human error, especially in the learning stages of any new contact center campaign. This is where conversational AI comes into play by helping organizations meet demand and handle as many interactions as needed at the same time without response time or accuracy hurdles.

With conversational AI, companies can build a solid and standardized customer experience regardless of size, growth rate, or other external factors.

Personalized Customer Interactions

One of the main issues of customer service is how difficult it is for customers to feel understood and valued. Given the nature of contact centers, which handle thousands of calls a day, it is difficult to provide the level of personalization that conversational AI technology can. 

Given the omnichannel nature of Mosaicx, for example, all previous interactions are logged, helping the customer navigate a more fluid and sensible journey. Likewise, by segmenting clients well, you can even find ways for VIP clients to skip conversational AI interactions and talk to a senior customer rep. 

Ultimately, what matters is helping people have significant interactions with your organization. By implementing AI, you can drive higher engagement, improve NPS scores, help people solve their problems faster, and allow your reps to focus on more complex conversations that have a higher impact.

Customer Insights and Data Analytics

Given how conversations happen with an artificial intelligence copilot, all information and signals are captured and categorized to help organizations find opportunities. With Mosaicx360, you get an entire ecosystem with everything needed to transform customer experience and improve outcomes across their whole journey. 

With conversational AI, you can reduce agent handling time, increase customer satisfaction, avoid unnecessary transfers, and even access true voice-of-the-consumer information to understand why people are calling. 

Moreover, Mosaicx's omnichannel and fully integrated essence allows businesses to have a unified view of the customer journey without adding additional technical debt to IT teams or having to "learn" to use our solution.

Better Accessibility Option

Conversational AI also helps organizations because it can handle multiple languages, adopt numerous communication styles, and help individuals solve their issues. Given the technology's text-to-speech and speech-to-text functionalities, people with disabilities can also massively benefit from conversational AI. 

This inclusive technology broadens your customer base while demonstrating a genuine commitment to diverse and inclusive customer service. With conversational AI, you embrace an inclusive by default approach that helps your organization standardize accessibility practices.

Conversational AI vs Generative AI, What’s the Difference?

While it is common to think of conversational AI and generative AI as similar types of technology, they are quite different given their purpose. Conversational AI focuses on understanding speech, ensuring conversations flow, and finding proper responses to multiple questions while skipping interactions beyond the model's scope. It's a closed information data set looking to help individuals solve issues based on previously interpreted information.

These conversational AI tools use NLP to analyze text and provide sentiment analysis, intent recognition, named entity recognition, and manage dialogues effectively. 

Generative AI, unlike conversational AI, is used to create new content. Instead of being limited by a data set, its purpose is to create texts, images, databases, etc., based on the data it has previously been trained with, often capable of tackling out-of-scope questions and interactions in original ways. Here, we find prominent examples such as DALL-E, creating images from text; Anthropic Claude, which can produce large texts on multiple topics; and ChatGPT, perhaps the most salient name in the generative space today. 

Today, leading customer service organizations use both technologies to serve their customers better. Conversational AI can process inputs and solve problems, and generative AI can create helpful content for each client.

Ultimately, enhancing the versatility of AI technologies is how companies can innovate and improve customer experience. To read more about generative and conversational AI technologies, click here. 

 

Limitations and Challenges

As with most technologies, conversational AI has multiple limitations and challenges. The first and perhaps most important challenge is that the hype around artificial intelligence is so prevalent across industries that organizations often rush into partnering with exceedingly technical solutions that are difficult to integrate.

Multiple providers in the space do not provide the level of service required to help your organization fully integrate conversational AI into their workflow. Among some of the most common issues we have seen are the following:

Limited support: While you may be able to buy conversational AI from multiple providers, not all of them are willing to provide the support required to help you make their solution work, at least not for free. With Mosaicx, you don’t just buy technology. Instead, our specialists help your IT teams integrate our solution while providing any other training required to ensure swift and effective implementation for your organization.

Technology learning curve: Many providers have robust solutions that can help your organization improve customer service. But, few of them go a step further by ensuring that their product is intuitive, easy to use, and has abundant documentation and customer support to ensure it can be integrated. 

All technologies have a learning curve. However, reducing the adoption pain as much as possible is one of the essential steps we prioritize. 

On-premises solutions: Another common hurdle limiting conversational AI implementation is the need for the infrastructure to host the computations required for conversational AI to work. Not only is it a physical dimension a potential issue, but it also represents a potential cybersecurity risk.

Adopting a cloud-based solution is a much safer option. It is also easier to implement and scale or reduce based on your actual needs. 

Conversational AI by Mosaicx

Mosaicx is the only conversational AI provider that supports phone and text service with end-to-end analytics, industry-leading voice features, and a success coach who maximizes value for the life of our relationship.

For over three decades, we have been delivering exceptional CX solutions to enterprises, empowering them to achieve unprecedented growth and impact the world.

WIth Mosaicx, you get:

End-to-End Dashboards: Insights360 tracks calls through transfers, collecting data throughout the call, including your IVR, queues, contact center, and partner sites. Measure effectiveness at every stage of the journey from dial to hang up.

Customer Care Channel Analysis: Capture the whole engagement experience, including all automated, agent-assisted, and outsourced segments. Optimize the performance of human and virtual agents to reduce call volume and costs per call.

Voice-of-the-Customer Listening: Get insight into why people call and how each step affects overall CX. Hear directly from customers what they think to gain first-hand knowledge about your services, products, and competitors without the limiting voice features of our competitors.


Ready to transform engagement with Conversational AI? Chat with one of our solution specialists and see how the right combination of AI, advanced technology, and human expertise can help your organization succeed.