The Challenges to Overcome for Successful Conversational AI

Interest in chatbots is increasing and market is expected to be $1.3 billion by 2025. The research into NLP is developing rapidly, both within academia and those large industry players such as Google & Amazon. To remain relevant within their market, companies need to stay on top of current trends, but prepare for the future by understanding where the research is heading and how this will impact them. It is therefore imperative to understand the issues they are up against and solutions to overcome these challenges.

There are copious amounts of conversational AI solutions which make it difficult for customers to choose between, but it ultimately falls down to design and which will provide a better user experience. According to a study conducted by PwC, 43% of all shoppers are willing to pay more for greater convenience. Improved and more efficient experiences will lead to a higher satisfaction rate and repeat customer rate in the future, meaning it is in the best interest for customer-facing companies to utilise the technology.

Another complicated factor that conversational AI faces is the difficulty surrounding understanding language input, especially when simultaneous conversations occur. Dialects and background noises can affect AI’s comprehension of the raw input and chatbots should be able to differentiate separate voices from each other and be able to provide the correct response. Within this sits the greatest challenge for conversational AI; the human factor in language input where feelings and sarcasm can affect understanding and perception. Furthermore, only a partial amount of the world’s population speaks English which becomes a challenge for the voice assistant to converse in languages other than English. Therefore, it is important to consider building additional languages as well as cultural discrepancies into conversational AI. This will help create trust between the consumer and voice assistant.

Leading on from this, many businesses face difficulties in creating and developing an ethical conversational AI platform. As conversation is the primary way we caliber relationships with other humans, it is crucial that businesses can use techniques within natural language processing and natural language understanding to generate trust between the chatbot and the customer to allow for a better, more holistic approach. Data suggests that nearly 73% of people are unlikely to trust conversational AI such as Google Duplex, an AI-powered voice assistant that can call and book restaurant reservations and 70% say they are unlikely to trust AI to reply to simple emails for them. Through new advancements in conversational AI, businesses can learn to build trust in their AI systems.

Organisations that focus on conversational AI need teams that can articulate a product vision that is effective, memorable and inspiring. They’ll need to design experiences that are trustworthy and cost-efficient, and train high-performing machine learning and natural language processing models. People with these conversational skills are in high demand and short supply, which makes it difficult to build a successful team. However, if you can leverage the shortage of conversational talent to your advantage, you’ll be able to deliver a unique service experience that increases engagement and further your competitive edge.

Want to find out how you can overcome these challenges? Then join us at the Conversational AI Summit in London 17-18 May to learn more about how you can scale your business, build chatbots that consumers trust and network with like-minded individuals in the industry. Download the brochure for more info.

Super Early Bird tickets saving you £600 on tickets are available until 13 January. Get your ticket to the Conversational AI Summit today!