Latest Articles from Emerj

Explore our analyst articles on the impact of AI across industries

AI at Verizon 950×540

AI at Verizon – Two Use-Cases

Verizon is the second-largest telecommunications company by revenue and the largest by market capitalization. The company is also the largest wireless provider in the United States with a reported 143 million subscriptions. In its 2021 annual  report, the company reported revenues of $126.3 billion. Verizon is traded on the NYSE with a market cap of approximately $194.5 billion. The company employs over 118,000.

AI at Alibaba 950×540

Artificial Intelligence at Alibaba – Two Current Use-Cases

Per Alibaba’s annual report, its revenue in 2021 exceeded 717 billion yuan (approximately 109 billion U.S. dollars), while its active yearly customers reached nearly 1.3 billion people. As of March 2022, Alibaba trades on the NYSE and has an approximate market cap of $225 billion.

Customer Engagement in Financial Services - Two AI Use-Cases 950x540

Customer Engagement in Financial Services – Two AI Use-Cases

This article was originally written as part of a PDF report sponsored by Daitan, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.

Two NLP Use-Cases in Drug Discovery and Clinical Trials

Two NLP Use-Cases in Drug Discovery and Clinical Trials

This article was originally written as part of a PDF report sponsored by expert.ai, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Making AI Projects Easier to Manage

Making AI Projects Easier to Manage – and More Like IT Projects

Increasingly, technology and business leaders look to AI project managers to make the execution (and success) of their AI projects more predictable. Executives and decision makers want AI projects to mature so they are more like the software development projects that have been with us for a generation. But, any AI project manager hoping to deliver on those expectations knows that success in AI projects requires an end-to-end thinking rarely found today.

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