Conversational AI – The Future
Enterprises have started building great expectations for conversational AI – they are envisaging a future full of smart and powerful virtual platforms that will help humans with just about any kind of support, very substantially.
Conversational Artificial Intelligence (AI) allows enterprises to implement chatbots, messaging applications, and virtual assistants to build vastly engaging and valuable relationships with clients. conversational AI is one of the most wanted technologies in the enterprise world today, fascinating business leaders across the globe.
How much of this is hype, and how much is closer to reality? In this blog, we have tried to cut through the noise and discuss the key expectations and future trends of conversational AI. Read on.
1. Conversational Voice AI and the growing preferences
Preferences for both voice and chat support platforms are largely industry and geo-specific. While chat is more adopted in emerging markets, in geographies like North America and Europe, voice continues to be the largest contact channel preferred by users. Chat is great for customers seeking support for low-level queries; they can multitask while waiting for a response. The inadequacy of chat communication is that it lacks emotion, and may get misinterpreted. Although it is faster than emails, it lacks the fluidity of spoken language. Voice comes into play for queries that are complex and require explanation. Voice support is still the quickest way for a customer to ask a question and get the required support.
In the coming years, voice will make a definitive transformation in the world of conversational AI. Rule-based, rudimentary chatbots deliver canned responses to predicted requests and statements. These bots are often remote applications, quite meek, and not integrated with other enterprise platforms or data. They can’t comprehend context, making them one-dimensional to offer the level of support expected today.
Users have started to understand the experience that a cognitive AI bot can give them – understand complex scenarios and recognize human sentiments, and carry out personalized conversations. Conversational AI platforms are deeply unified with information systems and can communicate across channels, including text messaging and voice interfaces. Most importantly, they listen to the users with the intent to understand, add value, and enrich the experience with augmented intelligence coming from data. Enterprises on the other hand are focusing more on customer delight and accomplishing first-rate Net Promoter Scores, of course with the help of conversational AI bots.
A Gartner report states that by 2022, 70% of white-collar workers will interact with conversational platforms on a day-to-day basis.
2. Platforms will be Low-Code or No-Code
Enterprises today seek Low-Code or No-Code platforms to address these issues and meet the evolving conversational AI needs.
With use cases increasing from hundreds to thousands, and conversation types snowballing from thousands to millions, not all enterprises have the ability and technical talent to execute large scale coding. Coding for each tiny change in the requirements can be monotonous and time-consuming. Low-code platforms have all possible features for a variety of use-cases in one place, enabling the customization of bots in a few clicks. Also, with ML-centric coding platforms, the need for specialized talent comes into the picture.
With more voice recognition products coming in, startups are abstracting a lot of the complexities around the technology. They are presenting pre-built products for a variety of use-case in one place, where enterprises can customize in just a few clicks, rather than write ML code. Low-Code and No-Code platforms increase the agility and effectiveness of enterprise support and will continue to gain traction in the coming years.
3. Virtual Assistants will flood enterprises
Millennial employees prefer smart work over hard work. There are various routine activities that limit the employees’ capability to accomplish their core job and deter their efficiency. Most of them believe that personal assistants like Alexa can help them efficiently handle routine activities related to their jobs.
Mail searches, managing meetings, and tasks like retrieving documents from knowledge repositories and different applications – these are typical areas where enterprise employees spend close to 25% of their time and effort. These activities can be achieved smartly by an intelligent virtual assistant, paving the way for the future of work-life.
Over the past few years, many organizations have been conducting pilots with the elderly population to understand how they work with conversational AI systems. They have been successfully using devices like Apple’s Siri, Amazon’s Alexa, and Voice AI has seemingly proved to be a powerful medium to connect with the elderly population too.
4. Personalization
Conversational AI bots of the future will bring about vastly personalized and contextual conversations with a human touch. For instance, they can comprehend and remember the conversation context, carry the context across multiple past interactions and dialogs, user preferences, etc., and delight the users with this suaveness. The human-like aspect of understanding users’ sentiments, moods, and responding accordingly will be one of the biggest reasons for these bots to be widely leveraged to cross-sell/up-sell products or services.
5. AR+Robotics+voice AI
AR in conversational AI is an exclusive technology that can take user engagement to greater heights. Users will more frequently begin interacting with digital and robotic avatars – the ones where augmented reality, robotics, and voice AI are combined. Although AR is a rather new technology for mobile/web apps and users are not familiarized with the practice of AR, the combination will soon be a revolutionary possibility. Also, the avatars will be built with more personification; they will demonstrate more personality to make the interactions as human-like as possible.
A chatbot within an app can simplify the use of this technology. Based on user behavior and their stage in the buying cycle, bots that use AR can encourage them to become buyers. For instance, if a user wants to get a feel of how a couch would look in their living room, or how a shirt would fit them, AR is the technology that enables them to envisage it. Although adaptability is less today, enterprises like IKEA and Zara among others are testing AR’s potential. The cognitive capabilities of Conversational AI bots can be an online concierge to support the buying journey of users.
6. App convergence
On average, a person uses 9 apps every day, with about 75 apps installed on their smartphone. They use different apps for various reasons – travel, utility, banking, learning, entertainment, and so on. The constant flow of notifications from these apps consumes data and battery, resulting in app fatigue. An important trend in this aspect will be the convergence of many apps into a multipurpose conversational bot. The conversational bot will integrate with multiple apps at the backend to perform activities and will be lightweight.
Industry adoption and the way forward
Conversational AI bots are being adopted in practically every industry. Banks have empowered their customers to interact with bots to get answers for queries on account balance and statements, transfer funds, create deposits, investment advice, and so on. The hospitality sector has deployed bots 24X7, to offer a better guest experience. The Airline industry is deploying conversational AI bots to simplify purchases, facilitate web check-ins, personalized search, and simplify travel. Industries such as Insurance, manufacturing, Telecom, etc., are fast catching up with the deployment of Conversational AI.
As conversational AI continues to evolve at prompt speed, there’s no doubt that businesses and consumers will benefit from the less human dependency that the bots offer. The rapid pace of development of Conversational AI, and technologies like IoT, will ensure that these innovations will become the norm in the next few years, enhancing the quality of interactions between customers and brands.
