AI Articles and Analysis about Data management

Explore articles and reports related to artificial intelligence for data management, including applications in data auditing, knowledge management, data collection, and more.

No One AI Tool Can Solve All Problems@2x

No One AI Tool Can Solve All Problems – with Jeff Mills of iMerit Technology

This article has been sponsored by iMerit Technology and was written, edited, and published in alignment with Emerj’s sponsored content guidelines.

The Fundamentals of Enterprise Data Fabric – Unlocking the Value in Enterprise Data@2x

The Fundamentals of Enterprise Data Fabric – Unlocking the Value in Enterprise Data – with Daniel Hernandez of IBM

This article has been sponsored by IBM, and was written, edited, and published in alignment with Emerj’s sponsored content guidelines.

Document Search and Discovery in Banking - An Analysis of the Field

An Analysis of AI-Powered Document Search Capabilities in Banking

The financial services industry is buried in paperwork, and the NLP use-cases in banking and insurance grow every year.

5 Phases of a Data Audit 950×540

5 Phases of an AI Data Audit – Assessing Opportunity in the Enterprise

Emerj serves enterprises to form their AI strategies, and data audits are part of Emerj's framework for identifying high-ROI AI projects. In this article, we'll break down a slice of this framework, walking through some pragmatic steps leaders can take to drive toward industry-leading outcomes in their organization.

Artificial Intelligence at Mitsubishi UFJ Financial - Current Initiatives

Artificial Intelligence at Mitsubishi UFJ Financial – Current Initiatives

Mitsubishi UFJ Financial (MUFG) is a Japanese holdings bank and financial services company ranked 5th on S&P Global’s list of the top 100 banks, and the largest Japanese bank on the list.

Critical Capabilities - The Prerequisites to Successful AI Deployment

Critical Capabilities – The Prerequisites to AI Deployment in Business

Over the last four years, interviewing hundreds of AI researchers and AI enterprise leaders, we've consistently heard the same frustrations about AI adoption said time and time again.
"Culture is hard to change."
"Leadership doesn't know what they're trying to accomplish."
"Nobody knows what to do with these data scientists we've hired."
etc...
In our one-to-one work with enterprise clients, we've taken the most prevalent, recurring challenges to AI deployment and put them together into a framework of "prerequisites" to AI deployment.

How Healthcare Leaders Can Get Started With Artificial intelligence

How Healthcare Leaders Can Get Started With Artificial Intelligence

This article was written by Sergii Gorpynich, co-Founder and CTO at Star, co-written by Perry Simpson, Managing Director of Star, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about reaching our AI-focused executive audience on our Emerj advertising page.

How to Get Started with AI in Healthcare - A 3-Phase Approach

How to Get Started with AI in Healthcare – A 3-Phase Approach

This article was written by Sergii Gorpynich, co-Founder and CTO at Star, co-written by Perry Simpson, Managing Director of Star, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about reaching our AI-focused executive audience on our Emerj advertising page.

Data management

Explore articles and reports related to artificial intelligence for data management, including applications in data auditing, knowledge management, data collection, and more.