AI IN ENERGY
One example of this in practice is the Chinese green energy company ENN Group Ltd , which tapped into hyper-automation to boost productivity and reduce costs .
At a time of remote work during the pandemic , the energy giant – serving customers across 80 cities in China – launched a cutting-edge virtual assistant that merged AI from IBM Watson ® Assistant and IBM Watson Discovery , while incorporating the automation capabilities of IBM ® Robotic Process Automation ( RPA ) with Automation Anywhere . This new tool was able to understand and answer IT employee service desk requests . In just half a day , the virtual assistants significantly improved the remote work experience for thousands of employees , providing them with the technology they required .
According to Li Qiang , the IT Platforms Executive at ENN Group Co . Ltd ., the company ' s AI automation platform enhances the work of employees by providing them with AI-powered tools and freeing them from mundane , repetitive tasks . This allows employees to tap into their creativity and imagination . The platform , based on IBM RPA technology , also features an automated financial assistant that can handle basic back-office duties , such as generating reports and managing monthly ledger entries .
The results were impressive , with the assistant completing 2,000 to 3,000 tasks daily and supporting over 70 business scenarios . The impact was substantial , resulting in millions of dollars of value and a 60 % reduction in processing time .
Shaping the energy market of tomorrow with RPA Adopting RPA , cutting-edge analytics , and AI is crucial in attaining climate change objectives and satisfying the increasing demand for clean , affordable energy . Promoting widespread usage in support and technical functions will play a crucial role in the enhancement of efficiency and customer satisfaction , as well as in transforming operating and business practices .
Older business models with longterm agreements backed by large capital expenditures are being replaced by smaller players and projects – such as shale oil , rooftop solar panels , and microgrids . For the energy and utilities sector to thrive in this dynamic environment , it ’ s imperative to adopt automation and AI on a large scale .
86 April 2023