Thomson Reuters third-quarter profit beats estimates
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1970-01-01 08:00
By Helen Coster NEW YORK (Reuters) -Thomson Reuters Corp on Wednesday reported higher-than-expected operating profit in the third quarter, helped

By Helen Coster

NEW YORK (Reuters) -Thomson Reuters Corp on Wednesday reported higher-than-expected operating profit in the third quarter, helped by strong performance at its "Big 3" segments, Legal Professionals, Corporates and Tax & Accounting Professionals.

The provider of information and tools for lawyers, accountants and other professionals reported adjusted earnings of 82 cents per share, above analyst forecasts for 71 cents.

Total revenue rose 1% in the quarter to $1.59 billion, missing expectations of $1.61 billion, according to LSEG data.

Thomson Reuters, which owns the Westlaw legal database, Reuters news agency and the Checkpoint tax and accounting service, said organic revenue was up 7% for the " Big 3" segments.

Thomson Reuters CEO Steve Hasker said the company achieved "solid momentum" in the quarter despite "an uncertain macro environment," and added "our confidence in generative AI continues to strengthen."

Organic revenues in the Legal Professionals segment increased 6%, while total revenue fell 2%, reflecting sales of some divisions.

Organic revenues in the Reuters News division increased 3% in the quarter, driven by a contractual price increase and growth in transactional events and digital advertising revenues.

Thomson Reuters has said it will use a “build, partner and buy” strategy to incorporate generative AI solutions into its products and services, and has earmarked $10 billion for acquisitions and about $100 million per year in investments in AI capabilities.

Generative AI is a type of artificial intelligence that generates new content or data in response to a prompt, or question, by a user.

In August, the company closed on its $650 million cash acquisition of Casetext, a California-based AI company that helps legal professionals conduct research, analysis and prepare documents using generative AI.

(Reporting by Helen CosterEditing by Nick Zieminski)

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