The relationship between computers and humans has undergone a significant paradigm shift over several decades. From the emergence of the web in 1995 to applications or apps in 2005, technology has grown by leaps and bounds as the years progressed. This growth has brought technology to the modern era, where artificial intelligence (AI) has ultimately begun to come of age.
Engineers and scientists have invested a great deal of effort, in terms of both energy and time, over the past few decades, which has allowed AI to be adapted into nearly every technological innovation in recent years. One such innovation is the intelligent virtual assistant (IVA).
An IVA is a conversational AI system that has the capability to emulate human interaction in order to carry out and optimize tasks—customer service, for example. Digital assistants are gaining widespread attention across the industrial landscape, owing to a plethora of technological advancements, including machine learning and deep neural networks, among others. What makes these virtual assistants intelligent is their ability to emulate three key elements that enable customer service agents to solve problems—learning, reasoning and understanding.
How did these conversational AI technologies achieve these capabilities? To answer this question, it is essential to delve into the evolution of the IVA market.
Evolution of IVAs
Although the terms “chatbots” and “intelligent virtual assistant” are often used interchangeably, and despite the fact that these technologies share a core commonality—i.e., their ability to facilitate consumer-enterprise interaction—these conversational AI technologies have some distinct differences. These differences lie mainly in complexity, scope and abilities, which IVAs’ possess more of than chatbots.
In simple words, IVAs are the result of a decade-long chatbot evolution.
Chatbots were first introduced in the late 60s and early 70s. These technologies were programmed with rudimentary capabilities, including scripted responses based on user inputs in the form of specific phrases and keywords.
However, with conversational flows becoming increasingly more complex over time, these chatbots began facing limitations in their scope, mainly owing to their lack of learning process and pre-programmed responses. With no memory or context retention capabilities, the bots were unable to comprehend relevant user information between sessions or even during the conversation.
However, conversational AI evolution reached a turning point with the emergence of two novel technologies, machine learning (ML) and natural language understanding (NLU).
NLU gives the digital assistant the ability to comprehend and interpret inputs from users in natural language, which can enable the bot to converse with a customer naturally, as a customer service agent would.
Meanwhile, ML allows the bots to self-train based on data such as previous customer service interaction transcripts or by observing live customer-agent interactions. This helps the IVAs to cater to customer needs in a more efficient and seamless manner.
The technological advantages provided by these technologies, therefore, facilitated the gradual evolution of simple chatbots into IVAs, which possess in-depth domain knowledge that they can leverage to understand customer preferences and intents, fulfill their needs and enhance performance over time by gaining new insights from each interaction.
As a result of these advanced capabilities, automation and customer satisfaction are assured outcomes of IVA adoption. Thus, brands that make use of this technology can make sure that they refocus on their primary objective: ROI.
The Gradual Shift of IVA Technology from a Personal to a Commercial Landscape
Starting out as an ideal solution for virtual personal assistants, such as Apple’s Siri which allows users to use voice-technology to perform myriad tasks like texting, scheduling meetings or making phone calls, IVAs are now gaining prominence as crucial tools for brands to implement effective customer engagement.
AI assistants are rapidly making their way out of personal applications and entering a more business-oriented landscape, for instance, Oracle’s Digital Assistant which is designed to be an ideal platform for sales, marketing and other industry verticals by interfacing with a vast software app portfolio.
IVA technology is used across a range of industrial applications, for example, taking up the role of sales agents or customer service executives, which makes it a scalable and appealing option for enterprises. Businesses predominantly adopt digital assistants to drive efficiency, enhance ROI, optimize processes and help reduce workloads.
As the industrial space grows increasingly more competitive, customer engagement has emerged as one of the most significant assets for a successful brand. In fact, studies have shown that almost 96% of customers across the globe believe that customer service is a significant factor contributing to their loyalty to a brand.
IVAs help brands deliver positive customer experiences by covering a number of different aspects. For instance, AI assistants can quickly solve customer problems through customers’ preferred channels, ensuring speed and convenience. They can also integrate with various systems and databases of brands, thus offering a robust knowledge base to provide tailored solutions to customers. Additionally, they are able to adapt their tone and language to context, which helps them emulate human conversations. All these factors help digital assistants play the role of an efficient and helpful customer service representative.
How Brands Are Leveraging Conversational AI Assistants to Drive Customer Engagement
Given the strong capacity of conversational AI technology to engage actively with customers and optimize customer service, more and more companies are adopting the technology as an integral part of their customer experience activities.
To illustrate, Volvo has plans to develop conversational assistance to guide drivers in the use of various in-car apps to deliver a more effortless connected car experience.
Likewise, Spotify has also earned positive reviews for its AI-based technology to track user patterns and make accurate recommendations and predictions based on preferences of individual customers, in turn elevating the overall user experience.
The IVA industry has witnessed several prolific advancements over the years. The future outlook for the technology seems positive, with even more exciting avenues as the years progress, and AI researchers investigating the prospect of enhancing the emotional intelligence of assistants. The ability to comprehend not just the user’s preferences but also their emotions would revolutionize the way customer service is delivered, thus positioning AI assistants as a pivotal component of the future customer experience landscape.
Organizations that are finding it difficult to handle the volume of support calls being made by often geographically distributed remote workers can employ chatbots via a SaaS platform in a few hours, Calhoun said. In many cases, IT staff are trying to respond to help desk requests using on-premises applications that they need to access remotely, often using cumbersome virtual private network (VPN) software. A SaaS platform provides an alternative approach that is designed from the ground up to be accessed remotely, he said.
