Think of software as a self-sustaining unit capable of connecting seamlessly with the human mind, and your first thought is the virtual assistant. Voice command devices are the most prevailing breakthrough in Artificial Intelligence. This technology relies on location awareness and user input. To provide meaningful insights in response to queries, virtual assistants often depend on digital data pertaining to traffic congestion, user schedules, retail prices, stock prices, weather conditions, and news.
Conversational capabilities and emotional intelligence are at the core of virtual assistants that hold promise for the future. You are most likely to encounter voice command devices in the areas of customer service, voice-to-text dictation, email management, data analysis, help desk management, and team collaboration.
AI virtual assistants are targeted at a wide customer base: business management personnel, executives, and lay customers. Intelligent virtual assistants such as Apple’s Siri, Amazon Alexa, Google Now, and Microsoft Cortana perform important business functions for personalized and engaging customer service.
What Statistics Say about the Market Growth of Virtual Assistants
Estimates from voicebot.ai indicate that one in five Americans has smart speakers. That makes 47.3 million adults, or about 20% of the US population.
Trends resonate with Gartner predictions: about 25% customer service operations relying on virtual assistants by the year 2020 may reach the USD 11.5 billion mark by the year 2024. This report indicates that speech recognition will grow by USD 7.5 billion, and automotive applications will rise to USD 2.8 million.
What Tech Companies are Doing to Achieve Natural Conversations
It all started with Microsoft’s Cortana which used Bing search to answer voice queries for its Windows 10 users. Cortana reminds users based on time and location. It provides weather updates, answers questions, and schedules tasks in response to voice queries.
Amazon Alexa was launched in 2014 and functions as a household assistant. Alexa Echo devices come in many forms from an assistant with a built-in camera to a TV-style assistant. The device possesses built-in skills such as ordering pizzas, shopping Amazon products, or providing basic information. Alexa can organize tasks, perform a list of daily “routines”, and buy products online.
Apple’s Siri personalizes responses to natural-language user queries. Scheduling, reminders, translation, payments, navigation, phone actions, Internet search, and access to third-party applications are all integrated with Siri. Much like others, the Google Assistant answers queries, sets up routines and alarms, plays music, and provides nutrition and health information.
Nuance, an innovation specialist focusing on conversational AI, feeds its advanced Natural Language Processing (NLU) algorithm with transcripts of chat logs to help its virtual assistant, Pathfinder, accomplish intelligent conversations. According to Paul Tepper, machine learning expert at Nuance, their three main focus areas include understanding user intent, delivering all kinds of answers, and ensuring two-way dialogues. Business processes are a far more complex area, as a dialogue with the virtual assistant may depend on the status or completion of business processes. This is where sociolinguistic experts and conversational designers guide the flow with graphical and flow-charting tools for a more human feel.
Mica is another innovation breakthrough with augmented reality in action. Powered by Magic Leap’s technology, Mica is able to mimic human expressions such as making eye contact, yawning, and smiling for more personalized conversations. For Mica, ethical and security issues are major concerns.
A Quick Rundown of AI Virtual Assistant Use Cases
The limitless nature of Artificial Intelligence makes it possible to target almost any niche area with an intelligent personal assistant capability.
Retirement Planning: Take the case of Industrial Alliance virtual assistant, an AI companion designed to predict retirement savings or the most appropriate contribution to RRSPs. The IA virtual assistant integrates a number of features, such as user personalization, lifestyle modifications, and insurance advice for intelligent financial planning.
Buying a New Home: The perfect advisor for new home buyers is Nationwide Building Society’s digital assistant, Arti. This AI assistant will derive learning from IBM’s Watson and will be able to answer a question in three seconds. It is configured to deal with a range of subjects, including transfers and withdrawals, investments, loans, and account payments.
Flight Booking: In the airline industry, AI assistant Ada serves AirAsia as a customer self-service solution. Ada works for the web and mobile to manage accounts, flights, and booking information. Air Asia serves 80 million customers yearly across 130 destinations and 21 countries. Ada leverages AI to support non-technical teams and increase the engagement of a culturally-diverse audience. The airline carrier benefits in terms of time and cost savings.
Mobile Banking: Intelligent personal assistants are increasingly employed in digital and mobile banking applications. Banking enterprises have imbibed AI capabilities into their digital banking operations to increase efficiency in data analytics and automate back-end workflow. Significant success has been achieved in the USA by Bank of America’s Erica for guided finance and investment, Capital One’s Eno for personalization by learning consumer behavior, and Ally bank’s Ally Assist for personalized voice-based banking experiences. In India, HDFC bank launched Eva for personalization and ICICI bank’s iPal chatbot with impending advancements for improved customer and employee experiences. Similar AI assistants have been deployed by Australia’s Commonwealth Bank (called Ceba — a chat assistant) and Hong Kong’s HSBC bank (called Amy).
What Challenges and Innovations Lie Ahead in the Future for Virtual Assistants
In a nutshell, most virtual assistants work with deep neural networks focusing on not just finding the right answer to a query but also feasibly converting text and voice back and forth. Voice assistant technology is all set to evolve into more complex neural networks that scale and combine the elements of image, language, and speech processing. Some of the major advances to watch out for may be the intent discovery by Nuance, and Mica’s expressive conversations.
In an effort to make the voice assistant as close as possible to human behavior, several privacy issues may surface. The largest proportion of risks may be tied to hardware flaws. But a seemingly significant proportion of errors and misuse may occur when companies record personal information to render a better user experience and assist in machine learning. One such story is about Amazon echo recording a private conversation in a Portland home and sending it to a random user.
As a final thought, malicious attacks, either politically motivated or otherwise, may become a major concern in the future. As automated personal assistants such as Mica become more and more human-like, the risk of hacking, fishing, spreading fake news, and leaking personal information increases considerably. Experts believe that success is directly related to their predictive ability to foresee malicious use of the near-human digital assistant and include it in its Artificial Intelligence engineering.