Utility Week

20 www.utilityweek.co.uk/fLeX A I A N D C U S T O M E R S Allowing customers to use voice controls to conduct a range of actions, from optimising home heating to charging an electric vehicle, is just the start of where the technology could develop. Octopus is currently collaborating with a number of start-ups and technology companies taking different approaches to driving a smarter energy future. "Fresh innovation that shifts demand away from peak times and maximises flexibility is central to building a smarter grid, and the businesses that can unleash that will build the market of the future," says Jackson. C h a t b o t s v e r s u s r e a l p e o p l e For utilities, it will be essential to manage customer expectations while the sector's use of the technology remains in its infancy. Susannah Richardson, director for field service and contact centre solutions at IFS, admits that a major barrier to AI technology at this stage is its self-learning capability. Current forms of AI need large quantities of data for algorithms to learn, with an average 200 variations of data needed for AI to seamlessly answer a customer's request without review. Consequently, there is a bottleneck around the amount of data needed for each specific use case. "We recommend that you don't expect the bots to answer every question or resolve all the requests, instead analyse your most common use cases or frequently asked questions and train your bot to resolve these, while seamlessly handing over more unusual or specific questions to a human agent," says Richardson. e real evolution of the chatbot will be its ability to employ improved self-learning capability to optimise itself. When the bot needs to transfer to an agent, it copies and learns next time how to recognise, respond and process this request automatically. " is is possible today, but with improved machine learning this will become more and more powerful," says Richardson. As an enterprise software business, IFS's solutions aim to help companies offer more connected services for their customers. By incorporating data from different front and back office systems, the IFS Customer Engagement (CE) platform operates as a centralised interface to manage requests from utilities customers. e platform uses AI chatbots and natural language processing (NLP) to offer self- service options and automatically retrieve the necessary information to address the customer's need. Welsh Water's Lloyd agrees; the company hopes that its fresh approach to customer engagement and innovations such as the chatbot will continue to increase customer trust. But despite successfully using AI to facilitate the consultation, the technology is not without its limitations, he says: FIELD MARSHALS Beyond using AI to improve engagement with customers, there is scope for the technology to help utilities deliver more responsive repairs in the field. While the adoption of AI in the field is in the early stages of development, there are already a few common use cases. " e simplest is to help customers help themselves: before they make that call to the support centre, a chatbot or online triage employing NLP can be used to diagnose and frequently resolve the issue," says Susannah Richardson, director for field service and contact centre solutions at IFS (pictured). "Research shows that customers would much rather use self-service to resolve most issues if given the option." If an issue remains unresolved, or the customer chooses to go straight to the support centre, the agent is empowered with the knowledge base and tools to diagnose and remotely resolve the issue, potentially negating the need for an engineer. "In the background, AI can be employed to increase the accuracy and probability of resolution, analysing the likely failure modes for a specific asset," says Richardson. If the fault requires a field technician to repair the issue, then the data from the triage, plus data on the in-field asset, can be analysed to ensure that the technician dispatched has the appropriate boot stock to provide a first-time fix, she adds.

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