On a global scale, businesses have gone through a significant transformation while riding over the shoulders of technology. Whether it is cutting-edge tech innovations, globalization, or behavioral change on the consumer side, evolution has occurred for the better. One of the primary reasons for joining this bandwagon is to deliver a top-notch customer experience. With the tremendous rise in customer interactions, conversational AI as a tech innovation comes to their rescue.
For both online and offline selling, most brands have deployed conversational-AI based chatbots to streamline customer support. Particularly for contact centers, AI has helped improve the lives of agents dealing with consumers round-the-clock. Similarly, it also provides employee assistance and helps in workforce management.
Back to the Basics of Conversational AI
Conversational AI is a form of AI that allows humans to engage with computer programs using natural dialogues. These programs are developed to simulate human conversations and voice interfaces. If you wish to dive deep, here’s everything you need to know about Conversational AI.
With conversational AI becoming mainstream in both personal (Siri and Alexa) and corporate worlds, almost every industry has witnessed the changing interaction between machines and humans. But to predict the future of conversational AI, it is crucial to have a 360-degree view of the current market.
Let’s look at some important numbers signifying the spread of conversational AI:
With both pluses and minuses of conversational AI right in front of our eyes, let’s dig deeper into its expected future.
As the awareness around conversational AI increases, more people will better understand that AI is not about machines that can act like a complete human. Rather, it represents an explicit set of functionalities that can automate simple tasks and help augment individuals working at complex problems.
Certain AI applications focus on handling mundane tasks and helping individuals in coping up with the work pressure in the post-Covid environment. However, the next evolution stage is expected to focus on the mainstream development of emotional intelligence to execute innovative, higher order tasks.
According to a Verizon survey report, only 20% of respondents considered the emotional intelligence of AI as an important skill before the pandemic. The number has jumped to 69% in the post-pandemic period, indicating the need for further development of conversational AI technology. This side of AI, when developed, will enhance workplace culture and help strengthen the bond between businesses and their customers.
While humans take pride in their job roles, we need assistance most of the time. We forget things, do tasks in the wrong manner, and have shortcomings. It is expected that many of such human issues can be reduced or corrected with the help of AI.
As Gartner predicted, 70% of white-collar employees will interact with conversational AI platforms daily. Also, there has been a 160% rise in the client interest to implement chatbots and related technology. It only goes forward to show that AI can offer a superior, error-free human interaction based on historical data. AI coaches or advisories will enable the workforce to reduce errors in the daily tasks while also improving their decision-making skills.
Take the case of conversational AI to provide customer support. The AI bots can improve the customer experience by adding a personalized touch in real-time. If a customer wants to know about the status of his/her last enquiry, the bots will provide instant results and faster query resolution. But what if the AI is not smart enough to offer the desired result?
This is where the need for closed-loop systems is highly felt. Over time, these systems are expected to become the new standard with improved AI capabilities. They can measure and observe the interactions and learn from the usage patterns to become smarter and more effective in achieving a particular result.
Amidst the emergence of AI, several businesses have become concerned about the bias and discrimination introduced by AI and Machine Learning (ML). For example, several cases have been reported in which the credit rating algorithms have treated individuals from certain demographics unfairly. Similarly, various image processing models have incorrectly classified people based on skin color. As a result, it is expected that the technology companies will further develop their programs to mitigate bias in their AI solutions.
As a part of the future of conversational AI, the next-gen solution will be more focused on the implementation of the FAIR framework to use data collection and ML techniques to reduce the bias effect.
Context will be the key to the next level of conversational AI solutions. For example, if a customer interacts with a voice bot, asking for flight booking from Place A to Place B, the bot should be able to understand the related factors. If the flights are available during a specific period and the customer asks for documents required, then the bot should be capable of understanding the context of a conversation.
Contextual awareness is a primary asset when it is about serving customers with AI-powered solutions. This is possible with advanced ML models to make the solutions aware of customer sentiments, intent, and emotions.
No customer would want to repeat the query they asked to a brand on one channel while interacting with a support executive on some other channel. Taking the conversations forward with AI-backed assistants will no longer be limited to one platform. Rather, it needs to be integrated across platforms to create an omnichannel approach for brands.
This way, support and sales agents can have a hover-vision across multiple channels to create personalized experience for each customer. This can be further combined with emotional intelligence and sentiment mapping to improve customer conversations.
As the Covid-19 pandemic occurred, many business operations were frozen, leading to a surge in conversational AI usage. Amidst the consistent layoffs and capital losses, people also could not travel due to the pandemic-imposed restrictions and social distancing. All of this led to the rise in usage of virtual assistants and chatbots. The accelerated adoption of AI-based bots and assistants has made people across the globe recognize the power of AI.
Hence, it can be expected that both businesses and consumers will continue to adopt AI-powered solutions to offer more efficient customer services in the time ahead.
For businesses targeting linguistically-diverse regions or multiple nations to acquire customers, having a multilingual chatbot or voicebot will be an exceptional asset. This will be particularly useful to grow your business in foreign nations that have a large population of non-English speakers. With English being a globally-accepted language, it is fair to assume that the targeted businesses will find it easier to use the AI products. However, to achieve global expansion and adoption of conversational AI, it is quite important that the bots are configured to understand regional languages.
Multilingual chatbots will help serve customer queries at a faster rate and deliver a superior experience. They can also help businesses in targeting regional markets to target and convert potential customers.
The advancements in AI technology over the last decade have made voice commerce a key retail channel for different types of businesses. The result of this development includes the large-scale adoption of AI-powered speakers and the growing demand for contactless shopping experiences. Since more consumers are adopting a voice-first world using voice assistants in their smart devices, more brands now embrace the shift in paradigm.
All these factors are expected to support the further development of voicebots for e-commerce. Moreover, brands will look forward to leveraging voice interfaces to cater to the changing dynamics of consumer behavior.
Calling the virtual assistant on your smartphone represents a single intent to be fulfilled by a single user command. But what if you could instruct the AI bot to clear your meetings for the day ahead and book a flight to a nearby city available within the next three hours? Most conversational AI-based bots cannot fulfill such a complex request as they are designed to handle simple, short queries. They actually fail to understand multiple intents in a single user command, hence making the consumer experience inefficient and even frustrating.
The future versions of conversational AI are expected to handle a series of tasks and manage a wide range of conversations with customers more effectively.
Conversational AI products do have their limits but many of them have proven their worth. With technological improvements going underway, the solutions will get better. Enhanced AI technology and good experience design backed by behavioral science will form the foundations of engaging and conversational solutions for the masses. Contemplating these vectors of progress, conversational AI is likely to have a considerably long life span. Let us help you enhance your customer experience with Conversational AI.