Recent advances in cutting-edge technologies such as artificial intelligence, machine learning, and natural language processing (NLP) have fostered a unique digital experience for both businesses and customers. With rapid technological advancements, Conversational AI has become prevalent these days, performing work faster and more accurately than humans. Conversational AI significantly automates communication and creates a personalized experience, saving companies lots of expenses for customer services. Integrating conversational AI with automation creates an extended omnichannel experience to facilitate.
Many businesses embrace conversational AI solutions in order to make a more effective transition to digital operational models. Automation is not new to modern enterprises. This AI-powered technology helps companies fast-track their digital transformation efforts while assisting them to better respond to uncertainties like the ongoing impacts of the COVID-19 pandemic. Indeed, a McKinsey report predicts that half of today’s work activities could be automated by 2055. Another report further suggests that even modern industries can automate almost 30% of the tasks that comprise 60% of their total workload.
Importance of Conversational AI and Its Benefits
Conversational AI refers to the execution of automated conversations between computers and humans. Its applications can be found in almost every domain, including sales, marketing, customer service, etc., in the form of chatbots, messaging apps, and voice assistants (VAs). While conversational AI allows one to accurately interpret customer conversations and automatically respond with relevant answers, what makes it prevalent today.
Enhanced Productivity: Intelligent virtual assistants (IVAs) offer 24/7 support and can handle customers’ requests, allowing customer care agents to deliver fast, personalized experiences by responding to concerns more quickly. These assistants improve employee productivity as they let human agents handle multiple conversations simultaneously and address tasks and requests effectively.
Cost Efficiency: By implementing conversational AI, companies can save lots of capital spending on customer support. The technology even requires a minimal up-front investment, lowering high operating costs. Conversational AI is able to process requests at a higher volume than humans. It delivers germane and correct information faster and augments accuracy and complexity over time.
Interactive Brand Experience: Conversational AI creates more interaction and loyalty through personal engagement. The technology is already made into human’s daily lives in the form of VA's such as Alexa, Siri, and Cortana. These VAs allow businesses to personify their brand and meet their customers on their preferred channel to create a truly interactive brand experience.
Heightened Employee Experience: Conversational AI has two user bases – customers and employees. We have already seen its ability to deliver effective customer experiences. For employees, this technology in the form of virtual assistants or chatbots minimizes the complexity of systems and allows them to focus on building robust and prolific customer relationships.
Scalability: Conversational AI is highly scalable as it can be integrated seamlessly and used in any language. This is mainly because this technology is trained based on customer language data. Conversational AI enables many higher-value functions in IT support, customer service, and employee services. For example, Vocalcom, a cloud call center software company, capitalizes on AI-powered predictive behavioral routing to connect customers and agents with similar characters.
How Does Conversational AI work?
Conversational AI comprises a blend of Natural Language Processing (NLP), Machine Learning, Natural Language Understanding (NLU), and other AI algorithms that process complex dialogue. These technologies make language processing and decision-making possible. To make conversational AI work efficiently, it is essential that AI must interpret the customer’s intent and behavior. Using advanced NLU, AI can understand the customer's intent, regardless of grammatical mistakes, shortcuts, and idiosyncrasies. The technology also retains context from one statement to the next, discerning what is being said throughout the conversation.
Moreover, AI must determine the right response based on its perception of the customer's intent using machine learning. AI can learn more variations of the same intent by understanding its surrounding. It can answer user questions more effectively that is easily understood by the user using natural language generation.
What if Conversational AI and Automation Integrate?
Conversational AI and automation are not new to modern businesses. They are prevalent these days and have become full-fledged and proven business strategies. Companies use them for multiple touchpoints to understand behavior performing customers behavior and their journeys. Scrutinizing and using these technologies intimately, a company can experience benefits, such as high-quality, consistent, and personalized customer service experiences along with enhanced revenue and support efficiency.
The convergence of conversational AI and smart automation creates an extended omnichannel and delivers more personalized customer service. What to consider when clearing the blurring lines between conversational AI and automation?
How to make them more productive and efficient? ---- Businesses need to follow these factors:
Streamlining both internal and customer-facing processes and incorporating automation
Seamless End-to-End Automation
Using an open integration framework
Processing behavior Performing effective data and analytics, and intelligent hyper-automation
The Current Scenario and Future Scope
As the COVID-19 pandemic hit the world, the way businesses operated has been instantly impacted and has urged them to explore effective alternatives. In order to respond to the crisis, businesses are actively turning to AI technologies to minimize operational costs been optimize limited resources. Conversational AI and RPA emerge as the two primary AI-driven technologies to power automation. Though they are distinct technologies, they share the common goal of lowering or eliminating costly manual steps in a process. While many businesses severely hit by the pandemic, business decision-makers are actively leveraging an automation-first approach to return to the pre-crisis scenario and get success.
The integration of Conversational AI and automation will continue to change every aspect of how enterprises engage and communicate with their customers. Enterprises will need to establish seamless conversations with customers across channels that their customers prefer. The more they use new automation capabilities, the more they able to tailor services to their customers.