Ai in utilities – transforming the cx for utility customers techsee electricity word search ks2


The utilities industry is shifting from a highly traditional, regulation-driven environment to a technology-driven, sophisticated marketplace. Utilities, such as energy, gas, water, and waste management, already rely on smart devices for optimization of infrastructure and the supply-demand balance.

This smart utility ecosystem generates huge amounts of data that must be analyzed to extract actionable insights. Artificial intelligence (AI) is helping to analyze this data in order to optimize supply-demand ratios, deliver proactive infrastructure maintenance and predict equipment failure. AI in utilities is also playing an increasingly central role in customer-facing interactions. AI in Utilities: The paradox

There is a telling paradox in the utilities market. While more than 90% of utility companies’ overall budget is dedicated to infrastructure and other operating costs, with less than 10% allocated towards customer service, the picture is very different when it comes to AI.

Gartner reports that the vast majority of utilities’ investment in AI is earmarked for customer service. 86% of utilities already use AI in customer engagement applications, call center service and support, or digital marketing platforms, far exceeding AI use in other areas of operation. Utilities recognize that in the short-term, investment in AI can deliver the highest ROI in terms of improving speed and efficiency, enabling better data processing and analytics, and enhancing the customer experience (CX).

Unlike high-risk investments that impact utilities’ infrastructure, investment in customer-facing AI is considered low risk due to the maturity of the market. In addition, the large number of repetitive customer inquiries traditionally received by utilities has driven these companies to use AI in the automation of specific tasks, such as:

Choosing off-the-shelf AI solutions to target specific quick-win use cases enables utilities to realize immediate gains, and increase their confidence in the capabilities of AI. Once success has been established, utilities can roll AI out to other applications and use cases, such as customer service chatbots or automated IT help desks.

Predictive analytics are helping utilities provide better energy management services by utilizing data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. For utilities, that means using data-driven insights to automatically deliver timely and relevant communications that wow consumers and optimize business operations.

According to Oracle , smart meters in the US generate one billion customer data points each day. Add to that customer information from demographics and call history, and utilities have all the data they need to predict customers’ wants and needs. For example, AI-based predictive analytics can help energy companies forecast high bills before the bills are generated, and deliver personalized alerts to customers. AI also allows utility companies to segment customers and automatically target specific segments for promotions or energy-savings tips, thereby reducing operational costs, and further cutting customers’ energy bills.

According to UIPath, utility providers who switch their business processes to robotic-process automation (RPA) see a significant decrease in human errors, usually over 60%. RPA is an emerging form of business process automation technology based on software robots or artificial intelligence (AI) workers. RPA can automate tasks such as meter reading, billing, processing customer payments, and other back office tasks.

This is especially relevant with the US Energy Information Administration reporting that there are more than 70 million smart meters installed in the United States, and that total is expected to reach 90 million by 2020. A team of RPA robots can be deployed to read smart meter information, freeing up valuable human resources.

The smart home market is in a stage of hyper growth, driven in part by the consumer-driven demand for smart energy management. According to Priori data, the global smart thermostats market grew 56% between Q2 2016 and Q2 2017 to $218.5M. The global smart lighting market grew even more – 81% between Q2 2016 and Q2 2017 to $101.2M.

These smart home devices generate a massive number of support requests for installation, set up, troubleshooting and maintenance, often overwhelming customer support centers. Using AI, utilities can implement self-service capabilities that instruct customers how to install and operate smart devices by themselves.

For example, an AI-powered virtual technician can use computer vision to view the customer’s environment and provide step-by-step unboxing , installation and activation instructions, eliminating the need for the customer to contact a human agent for assistance. Summary

AI is increasingly aiding utilities in managing, optimizing and maintaining not only their infrastructure, but their customer support operation as well. AI is helping utility companies automate repetitive customer inquiries and other tasks, thereby allowing them to concentrate on building customer relationships and taking their customer service to the next level.

Predictive analytics, RPA and virtual assistants are examples of use cases where AI has transformed the utilities industry, delivering an enhanced CX and added value for the enterprise overall. With 83% of top European utilities executives considering AI a high to medium priority for their business, customers can expect further transformation of the utility industry in the future.