How generative AI improves the customer and employees experience, with Olga Lagunova of GoTo, Podcast part 1 of 2

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In part one of our two-part series, we speak with Olga Lagunova, Chief Product and Technology Officer at GoTo, about one of the most pressing topics in technology today – generative AI. We dive deep into the utility behind GenAI, including how GoTo approaches this technology to improve employee and customer experience across industries and workforces.

GoTo is a global SaaS company providing solutions for business communications, contact centers, IT management, and IT support. The company serves 8,000 customers, ranging from small and medium organizations to large enterprises and MSPs. Over 1 billion people join meetings, classes, and webinars through GoTo’s communications products.

Olga says there is a significant opportunity to use generative AI to solve GoTo’s customers’ important problems, improving productivity and efficiency for businesses of all sizes. GoTo’s goal is to place the human at the center of its AI-powered products, in turn enabling enhanced customer experiences while making employees’ lives easier.

“The emotional connection with our products that GoTo customers have resonates with me the most,” said Olga Lagunova. “One of our small business customers told me, ‘It’s almost like I finally have a light on in my house. I can see what’s happening. It’s so profoundly changed the way we do work.’ This is what we want from our customers who use the products.”

The company’s usage of GenAI doesn’t stop with its customers. Internally, GoTo employees utilize GenAI tools to help with coding, development, and other tasks. This has helped to cut down on redundant, time-consuming work, while also empowering individuals with access to critical real-time information.

Visit www.goto.com

How generative AI improves the customer and employees experience, with Olga Lagunova of GoTo, Podcast part 1 of 2

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How generative AI improves the customer and employees experience, with Olga Lagunova of GoTo, Podcast part 1 of 2
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