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Conversational Artificial Intelligence (AI), often considered a cross between Natural Language Processing (NLP) and Natural Language Understanding (NLU), is an algorithm-based intelligence that helps computers listen, process, understand and understand human language. As COVID-19 accelerates the momentum of digital transformation, organizations have increasingly embraced new ways to meet customer expectations for timely resolution of questions. An important part of the customer experience process, conversational AI, is quickly taking center stage.
A Living Person survey found that 91% of customers prefer companies that give them the choice of calling or texting. Chatbots are an effective way for businesses to meet this demand. As customers increasingly expect 24-hour availability from businesses, chatbots have become an effective way to make this possible. Chatbots are cost-effective, efficient, and can routinely handle human queries, allowing difficult questions to be reserved for human agents.
With the influx of AI-powered chatbots comes the need for sophistication, as well as the need for chatbots to understand questions and produce the right answers to help customers get the best experience. This is particularly relevant to the emerging metaverse space as companies look to improve their presence and user experiences in a virtual world.
Kore.ai, a Florida-based company focused on providing AI-powered virtual assistants to businesses, aims to bring conversational intelligence into the metaverse. Kore.ai CEO Raj Koneru told VentureBeat in an exclusive interview that conversational AI is the foundation of the metaverse.
The Rise of Conversational AI
More and more companies have made use of conversational AI in recent years. Open-source AI language models have now helped developers and businesses in the conversational AI space to build better chatbots, accelerate the customer experience, and also improve the employee experience.
Conversational AI combines the functionality of AI to create a human-like interaction between the human asking the questions and the machine answering. Chatbots powered by conversational AI can recognize human speech and text. Conversation also takes place with an understanding of intent, allowing for more precise answers.
As voice and conversational AI support an increasing number of customer interactions, it is also increasingly important for bots to leverage historical data, connecting voice call data with message conversation data. Conversational AI helps make this possible by helping machines understand the human voice they listen to, understand prejudices, and process the answers humans seek.
Speed up shipping and deployment without skimping on usability
Companies need their chatbots built with conversational AI, Koneru said. The problem, however, is that building such solutions from scratch requires a long process, involving a lot of code writing. This can hurt the customer experience, as chatbots will remain less effective at creating conversational AI. The long wait time is often the result of issues such as sophistication levels, language, and geographic support. Consideration should also be given to the time needed to train the AI and ensure it is ready for market adaptation.
To reduce latency, many companies are turning to companies like Kore.ai, which offers a no-code automation platform that meets the conversational AI needs of companies looking to improve customer experience and interaction with their products.
Gartner Magic Quadrant for Enterprise Conversational AI Platforms 2022 lists Kore.ai as a leader in the conversational AI space, showing the company’s upward trajectory in the industry. Other companies on the list include Amelia, Cognigy, Omilia, IBM and OneReach.ai.
Koneru said Kore.ai uses a combination of NLU approaches — including core meaning (semantic understanding), machine learning, and knowledge graphing — to identify user intent with a higher degree of accuracy and execute complex transactions. He said Kore.ai can achieve a high level of accuracy by following specific methods, including:
- basic meaning: Analyzes the structure of a user’s utterance to identify words based on meaning, position, conjugation, capitalization, plurality, and other factors.
- machine learning: Uses state-of-the-art algorithms and models to predict intent.
- knowledge chart: Provides the information needed to illustrate the importance of key domain terms and their relationships in identifying user intent.
- Ranking and Resolution Engine: Determines the winning intent based on the scores of the three engines.
Gartner predicts that 25% of people will spend at least an hour a day in the Metaverse by 2026, prompting companies to join the race to claim their place in the Metaverse. Companies prepare customer touchpoints and proactively map user experiences.
According to Koneru, people in the metaverse will have conversations with avatars, essentially chatbots. It is therefore essential to create avatars that can understand and process the dynamics of human conversations and produce accurate results, even with all the human nuances that might interfere. This is where conversational AI comes in.
Using conversational AI to enhance virtual experiences in the Metaverse shows great promise, as Koneru noted, “The Metaverse is ripe with many use cases that traditional businesses can take advantage of.”
“There must be good reasons in the business processes that lend themselves to having a physical presence that prevents them from doing so digitally. The same goes for the post office and many educational services. When you think of telehealth, one of the strongest use cases can be to step into the metaverse and come across a virtual representation of your doctor who can monitor your vital signs.
According to Koneru, Kore.ai’s effort to improve the Metaverse world with conversational AI will make it the first conversational AI company to target Metaverse businesses while meeting the needs of everyday businesses. However, G2’s review reveals that Kore.ai has competition in Intercom, Zendesk Support Suite, Drift, Birdeye, and others.
Kore.ai has raised $106 million in equity financing over the past eight years and currently serves more than 200 Fortune 2000 companies.
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