“In the past, AI was seen as a complex and expensive technology that was only accessible to large companies with deep pockets,” says Himadri Sarkar, govt vice chairman and world head of consulting at Teleperformance, a digital enterprise companies firm. “However, the development of easy-to-use generative AI tools has made it possible for businesses of all sizes to experiment with AI and see how it can benefit their operations.”
Organizations are taking notice with revolutionary use instances that not solely promise to enhance back-office operations but additionally ship bottom-line advantages, from value financial savings to productiveness features.
AI in motion
According to McKinsey’s 2022 Global Survey on AI, AI adoption has greater than doubled—from 20% of respondents having adopted AI in at the least one enterprise space in 2017 to 50% right this moment. It’s straightforward to grasp this expertise’s rising reputation: as difficult financial instances meet growing buyer expectations, organizations are being requested to do extra with much less.
“Companies are trying to optimize their use of resources in an inflationary environment,” says Omer Minkara, vice chairman and principal analyst with Aberdeen Strategy and Research. “Adding to the pressure is the fact that many companies have to defer their technology spend and headcount increases.”
Fortunately, AI and ML options can assist bridge this hole for a variety of industries by automating and optimizing varied back-office duties and processes. A retailer, for instance, might use AI-powered chatbots to deal with routine buyer inquiries, monitor orders, and reply to refund requests, bettering response instances, enhancing buyer expertise, and liberating up contact middle brokers. At the identical time, monetary establishments are discovering the facility of ML to determine anomalies inside massive volumes of information that will point out fraud—an early warning system towards monetary loss. Organizations throughout industries can make use of AI and ML instruments to extract and analyze info from paperwork, reminiscent of invoices, contracts, and stories, and to scale back the burden of guide information entry whereas dashing up processing instances and minimizing human errors.
Download the complete report
This content material was produced by Insights, the customized content material arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial workers.