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We live in a digital age, and as the world becomes more digital, we’re focusing more on virtual assistants powered by superior artificial intelligence. Virtual assistants, in general, bridge the gap between the human and digital worlds. As exciting as Alexa or Siri are to use, they also provide consumers and organizations with assistance with a variety of jobs. According to Gartner, 50% of knowledge workers would use a virtual assistant daily by 2025, up from 2% in 2019. According to Gartner, voice-based communications will account for 25% of employee contacts by 2023.

But what is a virtual assistant, and what can it help you with?

What is an Artificial Intelligence-Powered Virtual Assistant?

A virtual assistant is a technology that combines Artificial Intelligence (AI), natural language processing, robotic process automation (RPA), and machine learning to extract complicated data and information from conversations and process it appropriately. Not to mention, algorithms are at the heart of it, combining historical data to construct data models. These data models recognize behavioral patterns and adapt them based on new information.

The virtual assistant can answer complex inquiries, make recommendations and predictions, and even initiate a conversation by constantly adding new data about the user’s past, preferences, and other information.

What does a Virtual Assistant do?

A Virtual Assistant can assist you with a variety of tasks. We employ consumer-focused virtual assistants such as Alexa, Google Home, or SIRI, which can answer broad questions and make recommendations based on the user’s profile, behavioral pattern, and other actions. However, you may utilize them as your digital assistant by using them to switch on the lights, make shopping lists, and turn off the heating when on vacation.

Virtual assistants are frequently used in customer service to manage inbound correspondence or internally to onboard new staff, for example. Virtual assistants, on the other hand, help with a variety of IT tasks. They can be used to automate routine processes such as system updates, knowledge management, and transaction orders.

History of the Virtual Assistant

People-machine communication is not a new concept; it dates back to the early 1960s. ELIZA, created by MIT professor Joseph Weizenbaum, was the first natural language processing computer program. Following that, IBM made another breakthrough in digital speech recognition with Shoebox, a voice-activated calculator that was unveiled to the public during the 1962 Seattle World’s Fair.

The 1970s were the decade of voice recognition, with collaboration between industry and academia such as IBM, Carnegie Mellon University, and Stanford Research Institute. The result was “Harpy,” a machine that knew around 1,000 words and could understand phrases, and had the vocabulary of a three-year-old.

The Tangora voice-recognition typewriter, named after the world’s fastest typist, was released in the 1980s. It had a 20,000-word vocabulary. The first virtual assistant, however, was IBM Simon, which debuted in the early 1990s. With IBM and Philips, it was a digital speech recognition technology that became a feature of the personal computer.

Colloquies, which released SmarterChild on platforms like AIM and MSN Messenger in the early 2000s, was technically the first chatbot, which most people are familiar with today. It was completely text-based and could play games, check the weather, search up data, and communicate with other users. It is also seen as a forerunner of Apple’s Siri.

How does Virtual Assistant work?

Virtual assistants are command-based passive listening devices that react when a command is recognized. Passive listening is used by virtual assistants, which means they hear what’s going on around them, which is also a privacy risk! The virtual assistant devices are internet-connected, allowing them to do internet searches and converse with other smart devices. They normally require a wake phrase or order to activate because they are passive listening devices. However, it’s not unheard of for the gadget to begin recording without being prompted.

For example, Siri, a voice search virtual assistant, requires some sort of trigger when asked a question without hesitating. “Hey Siri, how’s the weather today?” for example. The virtual assistant will notify you if it doesn’t understand your instruction or can’t find an answer. You’ll need to reword your query or talk louder or slower in that scenario. There may be some back and forth in some circumstances, such as when you request an Uber. You may need to supply more information about your location or destination.

Now, to put it another way, virtual assistants represent the pinnacle of robotic automation. A virtual assistant learns from each interaction by combining data from numerous sources and placing it in context. The virtual assistant can process everything that is said or typed and utilize it to generate an accurate answer using advanced language processing. More powerful virtual assistants can process many tasks and complicated inquiries using AI and machine learning. Based on previous selections and data, they get insight into one’s preferences. In this approach, interacting with the virtual assistant becomes a personalized experience tailored to the needs of the user.

Future of Virtual Assistant for the Enterprise

With Conversational AI and cloud computing, 2020 launched off a decade of innovation for organizations across all verticals. We’ve seen how advanced systems like Amazon Web Services, Google Cloud, and Microsoft Azure have solved challenging problems. But now, it’s less about science projects involving a voice-activated typewriter and more about using AI to solve real-world problems. Rather than AI itself, we are witnessing the application of actual innovation.

Over half of the organizations polled by McKinsey’s “The state of AI in 2020” had already implemented AI in at least one business function across all industries. The usage of virtual assistant technology can be combined with the benefits of expanding omnichannel and digital in general, especially given the acceleration of digital transformation last year owing to COVID.

We’ll double-click across the use cases and impact across numerous industries, such as retail, automotive, financial services, healthcare, life sciences, and more, in this first of many in a series.


To summarise, we have a once-in-a-lifetime opportunity to develop a new digital workforce to supplement human labor by utilizing virtual Assistants. End-user consumers and/or B2B end-customers profit from virtual assistants. With conversational AI and cloud-enabled services, we can successfully address external customer-facing use-cases, allowing businesses to meet the needs of digital natives and expand omnichannel digital virtual assistants. Most importantly, companies are developing “out-of-the-box” virtual assistant applications for augmenting specific enterprise teams – such as marketing, sales, and customer success – which can turn a once complex build-it-yourself project into a simple SaaS-deployment project, thanks to technological advancements.

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