Latest Articles from Emerj

Explore our analyst articles on the impact of AI across industries

Personalizing Product Recommendations 
at Walmart@2x-min

Personalizing Product Recommendations at Walmart – with Dr. Charles Martin

The en masse shift to online shopping that transpired during and post-COVID appears as if it's destined to last. According to the Brookings Institute, one third of US adults have used delivery apps to order from a restaurant or store in the last year. 

How AI is Changing Cybersecurity in Banking 1@2x-min

Generative AI and Human Reward Systems

Many of today's most popular digital products — from video games to social media and beyond — owe their popularity (and profitability) directly to their addictive potential. 

What Enterprises Can Learn from How Google Models AI Readiness@2x-min

What Enterprises Can Learn from How Google Models AI Readiness – with Pallab Deb of Google Cloud

It is exceptionally difficult to get started, much less succeed, in AI adoption if one does not have at least a foundational education, particularly in those “modules” pertaining to AI capabilities, requirements, and organizational readiness. A business wanting to implement AI must understand the current state of adoption and how this current state matches up against AI readiness requirements.

Making AI Come 
to Life in Heavy 
Industry@2x-min

Making AI Come to Life in Heavy Industry – with Nikunj Mehta of Falkonry

While the steel industry may not be synonymous with AI adoption, steel manufacturers are not different from any other business in ensuring efficiency in their output and throughput. There are almost certainly opportunities for AI implementation across an industry worth hundreds of billions of dollars that currently lags behind in adopting AI technology.

Seven Non-Technical Enterprise AI Career Paths@2x-min

Seven Non-Technical Enterprise AI Career Paths

Relying entirely on consultants or vendors is not a viable strategy - as AI adoption inherently involves new capabilities to be built up within the company, both technical and non-technical. The only reason a company would put AI technical development and implementation entirely in the hands of a vendor is ignorance of how AI works.

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