How Thomson Reuters is leveraging AI to reinforce productiveness

How Thomson Reuters is leveraging AI to reinforce productiveness

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Thomson Reuters is a venerable information and knowledge group, with its historic roots stretching all the best way again to the nineteenth century. The 2 firms merged in 2008 and supply a mixture of reports and specialised info in areas like legislation, commerce and accounting.

The group processes a ton of data yearly, counting on a employees of 27,000 topic consultants and journalists all over the world to generate quite a lot of content material. As generative AI has emerged in current months, it will absolutely be tempting to make use of it within the newsroom, as different information organizations have achieved, and see this functionality as a possibility to cut back employees, minimize prices and automate, automate, automate.

Whereas the corporate sees the advantages of AI for each its workers and prospects, it’s not within the employee alternative camp, at the least not but. As a substitute, it sees AI as a approach to assist prospects discover info quicker, and assist its workers function extra effectively, eradicating the mundane components of the job so individuals can do what they do finest.

It might be simple to assume that a company as outdated as Thomson Reuters would merely dismiss expertise like generative AI, however the firm tells TechCrunch+ that it’s all in in the case of the most recent expertise, because it appears for methods to enhance and modernize its operations.

The individuals half

Chief individuals pfficer Mary Alice Vuicic, says Thomson Reuters sees automation as solely a part of the story, and in the event you consider that, you could miss a few of AI’s largest advantages.

“We predict AI is an exceptional alternative for the professionals we serve by our merchandise, and equally internally for our colleagues,” Vuicic instructed TechCrunch+. “We predict it’s a software for augmenting the potential of our colleagues in new methods, serving to them do work higher, quicker, extra successfully.”

That stated, she additionally acknowledges that enormous language fashions (LLMs) don’t at all times present good solutions, and Thomson Reuters is already counting on inner experience to assist appropriate the fashions.

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