How Thomson Reuters is leveraging AI to enhance productivity | TechCrunch

Thomson Reuters is a venerable information and data group, with its historic roots stretching all the way in which again to the nineteenth century. The 2 corporations merged in 2008 and supply a mix of stories and specialised info in areas like legislation, commerce and accounting.

The group processes a ton of knowledge yearly, counting on a employees of 27,000 topic consultants and journalists world wide to generate a wide range of content material. As generative AI has emerged in latest months, it will absolutely be tempting to make use of it within the newsroom, as other news organizations have finished, and see this functionality as a chance to scale back employees, minimize prices and automate, automate, automate.

Whereas the corporate sees the advantages of AI for each its staff and prospects, it isn’t within the employee alternative camp, no less than not but. As a substitute, it sees AI as a approach to assist prospects discover info sooner, and assist its staff function extra effectively, eradicating the mundane components of the job so individuals can do what they do finest.

It will be simple to suppose that a company as previous as Thomson Reuters would merely dismiss expertise like generative AI, however the firm tells TechCrunch+ that it’s all in relating to the most recent expertise, because it appears for tactics 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 for those who focus on that, you might miss a few of AI’s largest advantages.

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

That stated, she additionally acknowledges that giant 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.