77 learning to create standardised scripts for agents to follow the next time a similar question arises in future.” Once organisations have these scripts in place, they can offer human agents the opportunity to let an AI-enabled bot take over during certain parts of the conversation. “It might be that the bot can autofill some of the responses in a text chat, for example,” says Karsten. Crucially, though, the agent will always retain full control throughout the entire conversation. “If the bot is leading the conversation and an issue arises – such as the customer entering their address incorrectly multiple times – it will notify the human agent so they can resume control and offer additional assistance,” says Karsten. “The AI and machine learning tools will enable the bot and the human agent to work together in harmony, ensuring the conversation is so seamless that the customer will never feel like they’re interacting with a bot at any point. They will simply be satisfied that their query was resolved in a quick and efficient manner.” Although AI-powered agent assist services are still in the nascent phase, Karsten predicts they will rapidly become a mainstream solution for many businesses. “Many enterprises are already experimenting with using AI-powered chat or voice bots to help them manage basic customer queries automatically, but the real opportunity lies in developing AI bots that help the agents,” he says. “Anywhere365 is already using this technology for text chats, but the next step is to develop similar capabilities for voice chats over platforms like Microsoft Teams – and it won’t be long until we reach that stage. “In this scenario, the agent would be able to see their real-time NPS scores, suggested dialogue flows, useful information and more on their screen while talking to the customer. This will really show the power that AI and machine learning have to transform the query resolution process and both the agent and employee experience.”
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