Artificial Intelligence at Geico-1x-4-min

Artificial Intelligence at Gilead Sciences – Two Use Cases

Gilead Sciences, a biopharmaceutical company founded in 1987, has emerged as a leader in the development of innovative therapies for a range of diseases, including HIV, liver diseases, and oncology. With a commitment to advancing the field of medicine, Gilead has increasingly recognized the vital role that AI plays in its operations. Gilead Sciences achieved an annual revenue of approximately $28.3 billion in 2024, driven by its robust portfolio, and employs around 18,000 people globally, reflecting its substantial size and reach within the biotech industry​.

Procurement Data
for Business Intelligence in Life Sciences@2x

Procurement Data for Business Intelligence in Life Sciences – with Jennifer Sieber of Gilead, Len DeCandia of Johnson & Johnson, and Edmund Zagorin of Arkestro

From intelligent sourcing and predictive analytics to automated contract analysis and risk mitigation, AI is enabling procurement teams to focus on strategic activities while delivering significant cost savings and improved supplier relationships.

Making the Move to Saas in Financial Services-1x-3-min

Developing AI ‘Behind the Curtain’ for Financial Services” – with Nate Bell of Wells Fargo

Unlike industries that prioritize rapid technological implementation, financial services must navigate complex challenges when adopting AI. Ensuring AI systems perform reliably is not solely a technological hurdle—it requires addressing foundational issues in data management and implementing oversight to mitigate risks. These elements are critical to maintaining trust and alignment with business objectives in an increasingly data-driven environment.

Making the Move to Saas in Financial Services-1x-2-min

Use Cases in Driving Automotive Efficiencies with Tire Data Collection – with Chris Helsel of Goodyear

Autonomous vehicles encounter high expectations regarding safety and operational consistency across diverse driving environments. A significant challenge lies in ensuring that autonomous systems can adapt to variable road and weather conditions, something that can profoundly impact fleet efficiency and safety. 

Identifying and Mitigating Bias in AI Models for Recruiting@2x

Identifying and Mitigating Bias in AI Models for Recruiting – with Jason Safley of Opptly

This interview analysis is sponsored by NLP Logix and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Solving Data Management Challenges in Third-Party Logistics Spaces@2x

Solving Data Management Challenges in Third-Party Logistics (3PL) Spaces – with Vladimir Gofaizen of Wineshipping

This interview analysis is sponsored by NLP Logix and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Future Vision Highlight_ Integrated CX in Financial Services for GenAI at Scale-min

Future Vision Highlight: Integrated CX in Financial Services for GenAI at Scale – from Shankar Ramanathan at Capgemini

In a global economy where customer experience (CX) is the ultimate competitive battleground for so many sectors, businesses across industries face  daunting challenges in scaling CX solutions effectively. Despite massive investments in customer service technologies, many companies need help to deliver consistent, personalized support that meets user expectations, leading to frustration, lost revenue, and damaged reputations.

Artificial Intelligence at Geico-2x-3-min

Artificial Intelligence at American Family Insurance Group – Two Use Cases

American Family Insurance Group, founded in 1927, began as Farmers Mutual Insurance Company in Madison, Wisconsin, targeting farmers with auto insurance. Over the decades, it expanded its offerings and changed its name to American Family Mutual Insurance Company in 1963. As per the financials published by the company, it made $17.1 billion in revenue in 2023, up from $14.4 billion in 2022. 

Driving Synergies Between Software Development and Data Science Teams in the Analytics Space-min

Driving Synergies Between Software Development and Data Science Teams in the Analytics Space – with Yigal Edery of Sisense and Tsavo Knott of Pieces

This article is sponsored by Pieces and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Driving Personal Relationships in F&B Procurement-min

Data-Driven Decision-Making for Global Supply Chains and Procurement – with Luke van der Waals of SLB and William Seagrave of Arkestro

This article is sponsored by Arkestro and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.