“Previously, AI was seen as a fancy and expensive technology that was only accessible to large corporations with deep pockets,” says Himadri Sarkar, executive vice chairman and global head of consulting at Teleperformance, a digital business services company. “Nevertheless, the event of easy-to-use generative AI tools has made it possible for businesses of all sizes to experiment with AI and see how it might probably profit their operations.”

Organizations are taking note with modern use cases that not only promise to enhance back-office operations but in addition deliver bottom-line advantages, from cost savings to productivity gains.

AI in motion

Based on McKinsey’s 2022 Global Survey on AI, AI adoption has greater than doubled—from 20% of respondents having adopted AI in not less than one business area in 2017 to 50% today. It’s easy to grasp this technology’s growing popularity: as difficult economic times meet increasing customer expectations, organizations are being asked to do more with less.

“Corporations are attempting 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 proven fact that many corporations need to defer their technology spend and headcount increases.”

Fortunately, AI and ML solutions may help bridge this gap for a big selection of industries by automating and optimizing various back-office tasks and processes. A retailer, for instance, may use AI-powered chatbots to handle routine customer inquiries, track orders, and reply to refund requests, improving response times, enhancing customer experience, and freeing up contact center agents. At the identical time, financial institutions are discovering the facility of ML to discover anomalies inside large volumes of knowledge which will indicate fraud—an early warning system against financial loss. Organizations across industries can employ AI and ML tools to extract and analyze information from documents, reminiscent of invoices, contracts, and reports, and to scale back the burden of manual data entry while speeding up processing times and minimizing human errors.