We are living in a digital era and as the world is becoming more digital, we are focusing more on virtual assistants using advanced Artificial Intelligence. Broadly speaking, virtual assistants bridge the gap between the human and the digital world. As you feel excited with Alexa or Siri, they also offer consumers and businesses support with a wide range of tasks. Gartner predicts that, by 2025, 50% of knowledge workers will use a virtual assistant on a daily basis, up from 2% in 2019. By 2023, Gartner predicts that 25% of employee interactions will be voice-based communications.

But what exactly is a virtual assistant, and what could it do for you?

What is an artificial intelligence-powered virtual assistant?

A virtual assistant is a technological amalgamation of Artificial Intelligence (AI), natural language processing, RPA, and machine learning that extract complex data and information from conversations to understand them and process them accordingly. Not to mention, algorithms are instrumental behind it that combine information from the past and create data models. These data models recognize behavioral patterns and depending on additional data they are adapted.
By constantly adding new data about the history, preferences, and other user information, the virtual assistant can answer complex questions, make recommendations and predictions, and even start a conversation.

What does a virtual assistant do?

A Virtual Assistant can do a wide range of things. We use consumer-centric virtual assistants like Alexa, Google Home, or SIRI, which are able to answer general questions and provide recommendations based on the user’s profile, behavioral pattern, and additional behavior. But you can also use them for turning on the lights, making shopping lists, and turning off the heating while you are on holiday making them your digital assistant.
Organizations often use virtual assistants in customer service to handle incoming communication or internally, for example, to onboard new employees. But also, a lot of IT activities are supported by virtual assistants. They can be used to automate frequent tasks like system updates, knowledge management, and even transaction orders.

History of the Virtual assistant

Communication between people and machines is not new and it started back in the early 1960s. The first natural language processing computer program was ELIZA, which was developed by MIT professor Joseph Weizenbaum. After that, another advancement in digital speech recognition happened by IBM which was Shoebox – a voice-activated calculator, presented to the general public during the 1962 Seattle World’s Fair.

The 1970s was the decade of voice recognition where companies and academia including IBM, Carnegie Mellon University, and Stanford Research Institute collaborated. The result was “Harpy,” a machine that mastered about 1,000 words, with the vocabulary of a three-year-old that could understand sentences. 

The 1980s produced products like IBM’s voice recognizing typewriter, named Tangora, after the world’s fastest typist. It had a vocabulary of 20,000 words. The birth of the first virtual assistant; however, began with IBM Simon in the early 1990s. It was a digital speech recognition technology that became a feature of the personal computer with IBM and Philips.

In the early 2000s, the first chatbot, familiar to most today, was technically invented by Colloquis, which launched SmarterChild on platforms like AIM and MSN Messenger. It was entirely text-based and was able to play games, check the weather, look up facts, and converse with users. It is also considered the precursor to Apple’s Siri.

How does Virtual assistant work?

Virtual assistants are command-based passive listening devices that respond depending on the recognization of a command. Virtual assistants follow passive listening which means it hears what’s happening around them, which is a privacy concern too! The virtual assistant devices are internet-connected for internet searching to find answers or communicate with other smart devices. However, since they’re passive listening devices, they usually need a wake word or command to activate. That said, it’s not unheard of that the device could start recording without a wake word.

For example, voice search virtual assistants like Siri needs some trigger while asking it question without pausing. For example, “Hey Siri, what is the weather today?” If the virtual assistant doesn’t understand your command or can’t find an answer, it lets you know. In that case, you need to rephrase your question or speak louder or slower. In some cases, there may be some back and forth, like if you ask for an Uber. You might have to provide additional information about your location or destination.

Now, technically explaining, virtual assistants are like the highest level of Robotic Automation. By using data from multiple sources and placing them in context, a virtual assistant learns from each interaction. Using advanced language processing, the virtual assistant can process everything that is said or typed and is able to use that to formulate a correct answer. Using AI and machine learning, more advanced virtual assistants can process multiple tasks and complex questions. They gain insight into one’s preferences based on previous choices and data. This way, the interaction with the virtual assistant becomes a personalized experience that meets an individual’s needs.

Future of Virtual assistants for the enterprise

If we consider businesses across all verticals, 2020 kicked off a decade of innovation with Conversational AI along with cloud computing. We have seen complex problems have been addressed with advanced platforms from Amazon Web Services, Google Cloud, and Microsoft Azure. But now, it’s less about science projects with a voice-activated typewriter, and more about applied AI solving real problems. We are witnessing the application of true innovation rather than the AI itself.

Across every vertical, over 50% of companies surveyed by McKinsey’s “The state of AI in 2020,” have already deployed AI within at least one business function. And with an acceleration of digital transformation last year due to COVID, the use of virtual assistant technologies can be coupled with the benefits of expanded omnichannel and digital in general.

In this first of many in a series, we are going to double-click across the use cases and impact across various industries such as Retail, Automotive, Financial Services, Healthcare, Life Sciences, and more. Up first, let’s take a look at two particular instances of how this impacts: The retail industry (B2C) and the technology industry (B2B).

Conclusion

To conclude, using virtual Assistants, we are getting a unique opportunity to create a new digital workforce that augments the human workforce. Such virtual assistants benefit the B2C end-user consumer and/or B2B end-customer. We can also address external customer-facing use-cases effectively with conversational AI and cloud-enabled services, that can help companies to address the needs of the digital natives, and scale omnichannel digital virtual assistants. And most importantly, with technical advancements companies are developing “out-of-the-box” virtual assistant applications for augmenting specific enterprise teams – like marketing, sales, and customer success teams – which can turn a once complex build-it-yourself project into a simple SaaS-deployment project.