In recent decades, much has been said about how artificial intelligence will transform almost every industry by automating physical, transactional, and cognitive tasks. Since the 1990s, with the emergence of Interactive Voice Response (IVR), technology has been used to allow humans to interact with computers through the medium they feel most comfortable with: conversation.
These early attempts to enable humans to "talk" to computers left much to be desired. Conversations with IVR systems had to follow structured rules, often leading users to dead ends and frustration.
Intelligent virtual assistants can quickly adapt to the nuances of a conversation. They can recognize a greater variety of user inputs, including those they were not specifically trained for. Each new conversation becomes a "learning experience." These interactions become even more powerful when integrated with applications, allowing users to trigger backend processes with just a few words.
The popularity of Alexa, Siri, and Google Assistant has demonstrated the value of conversational AI. According to eMarketer, more than 40% of internet users use a voice assistant at least once a month, and NPR reported that 52% of smart speaker users use their device daily.
A basic definition of conversational AI is the design and orchestration of a digital assistant that resolves queries and simple questions without requiring human intervention.
Intelligent virtual assistants can retrieve data, provide information, and resolve user inquiries, escalating to a human only if the query is complex. This, in turn, frees up employees and human agents to focus on more challenging tasks.
We're not talking about simple chatbots. These digital assistants must not only be capable of recognizing speech but also of understanding intent.
“Agents are smarter than traditional chatbots. They are proactive and can make suggestions before you even ask. They perform tasks across applications, improve over time by remembering your activities, and recognize intentions and patterns in your behavior.”
The key to conversational AI is understanding the user's natural language, a process known as Natural Language Processing (NLP). There are many ways to implement NLP. The most advanced systems, such as conversational AI platforms, process data through multiple natural language understanding (NLU) engines and conversation engines to ensure the best match between intent and action.
The first step in the process is recognizing users' words, phrases, and sentences. The approach depends on whether the user is speaking over the phone or communicating via text. To process voice data, NLP algorithms must first convert it into text. Speech recognition algorithms consider multiple languages, accents, and peculiarities of human speech.
The user's expression is then analyzed to identify each word based on its meaning, position, conjunction, plurality, and other factors. Sentences as a whole are analyzed to determine relationships between words. Finally, meaning is derived by combining these analyses.
Determining what a user has written or spoken is only the first step. The next is understanding what the user is trying to accomplish. Many intents consist of simple combinations of verbs and nouns, such as "Find product," "Book a flight," or "Transfer money." Users may also use modifiers like "then" or "first" in phrases such as "Book a flight and then find a rental car." Multi-intent detection can identify multiple actions described by a user and execute them in a logical order.
An entity is anything that defines, shapes, or modifies the user’s intent and is necessary to execute it, such as dates, times, and locations. When a user asks an agent to book a flight, they will likely include a city, date, and time that must be considered.
Entity extraction identifies these elements in the user's words. Entities can range from simple numbers and dates to complex elements like addresses and airport names, as well as user-defined categories.
Conversational AI enhances customer relationships, improves cost efficiency, provides better customer feedback, offers deeper insights, and delivers uninterrupted service.
Sometimes, buzzwords and complex technology distract from what conversational intelligence can do for businesses, when the real question is: what can conversational AI do for you?
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Conversational AI provides continuous customer support, enhances problem-solving skills over time, and operates at minimal maintenance costs.
Conversational AI assistants don’t need breaks or shift changes. They work around the clock, providing uninterrupted support for your business.
Conversational AI can access a wide range of data, which can be used to explore customer information. While human agents learn about specific customers over time and apply that knowledge to improve service, a conversational AI system starts gathering data from day one, allowing it to provide valuable insights more quickly and consistently.
Conversational AI can gather user feedback at various stages of their journey. This feedback can be used to design more personalized offers and promotions, inspiring greater customer loyalty and improving overall service.
Conversational AI can reduce caller wait times, assist with many issues without human intervention, and free up agents to focus on more complex tasks, enhancing overall customer. experience and efficiency.
Over the next five years, we will see radical changes in how we interact with technology. Today’s chatbots, with their limited responses, will soon become obsolete, and intelligent virtual assistants will take the lead, eliminating the need for multiple applications and delivering a seamless experience.With conversational AI, businesses will improve customer service and employee satisfaction, eliminating wait times and making conversations more fluid.
Experience is the sum of interactions, many of them routine. However, as a company grows, it becomes harder to provide customers with personalized interactions led by a human agent. In the global race to offer efficient service, all industries are adopting conversational AI to bridge this gap.
EDSA offers a Discovery process to identify high-potential use cases that add value to the organization while enhancing the experience of customers, employees, suppliers, and everyone interacting with the company.
In just two weeks, you will have a roadmap of candidate processes for conversational AI implementation, along with a tailored deployment strategy based on your timeline and budget.
With over 25 years of experience in the corporate segment, EDSA consistently aims to understand and meet your business needs with end-to-end solutions.
EDSA’s Artificial Intelligence Office experts are ready to discuss your projects.