Neurobiological and Cybernetic AI for Manufacturing, Part 1-min

Neurobiological and Cybernetic AI for Manufacturing, Part 1 – with Oleg Savin of Unilever

Modern manufacturing stands to benefit from integrating AI. The potential benefits are numerous, from improving efficiency and productivity by automating repetitive tasks to reducing unplanned downtime and cutting down on repair costs through predictive maintenance.

Understanding AI’s Expanding Role in Drug Discovery and Life Sciences R&D-min

Understanding AI’s Expanding Role in Drug Discovery and Life Sciences R&D – Liran Belenzon of BenchSci

This interview analysis is sponsored by BenchSci 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.

Long-Term ROI on GenAI in Healthcare

Long-Term ROI for GenAI in Healthcare – with Ylan Kazi of Blue Cross Blue Shield

Mobile technology, including smartphones and wearable devices, collects health-related data such as physical activity metrics (e.g., step counts, heart rate), sleep patterns, and self-reported health information through surveys and applications. 

Tackling Chargeback Challenges at Scale with Machine Learning and Dynamic Arguments-min

Tackling Chargeback Challenges at Scale with Machine Learning and Dynamic Arguments – with Roenen Ben-Ami at Justt

This interview analysis is sponsored by Justt 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.

Generative AI as a Catalyst for Enterprise Innovation_1x

Generative AI as a Catalyst for Enterprise Innovation – with Deborah Golden of Deloitte

Large enterprises' swift adoption of generative AI (GenAI) is driven by the quest for cost reduction and operational efficiency—but leaders risk falling behind competitors if these short-term gains stagnate without long-term innovation capabilities.

Artificial Intelligence
at Wells Fargo

Artificial Intelligence at Wells Fargo- Two Use Cases

Wells Fargo, a major financial services company, has its headquarters in San Francisco, United States. 

Keeping Up with AI Regulations
in a New Age of Data Privacy-min

Keeping Up with AI Regulations in a New Age of Data Privacy – with Leaders from OneTrust, Microsoft, and TELUS

This interview analysis is sponsored by OneTrust 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.

A Blueprint for AI-Driven Process Optimization for Regulated Industries – v2@2x-min

A Blueprint for AI-Driven Process Optimization for Regulated Industries – with Vrinda Khurjekar and Paul Pallath at Searce

This interview analysis is sponsored by Searce 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.

Unpacking the Positive Effect of AI with Customer Experience in Business – with Venkatesh Korla at HGS-2x

Transforming Contact Center Operations With GenAI – with Venkatesh Korla of HGS Americas

Generative AI (GenAI) is rapidly transforming customer service, helping enterprises cut costs, boost efficiency, and meet regulatory requirements.

AI Regulation and Risk Management in 2024-min

AI Regulation and Risk Management in 2024 – with Micheal Berger of Munich Re

As AI adoption grows, so do the associated risks, including errors, biases, and unexpected outcomes. However, as AI becomes more integral to core business operations, managing operational and financial risks becomes paramount. One way to offset that risk is to ensure AI models. However, that can be difficult to achieve as the process is complex.