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This article is sponsored by Arkestro, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.

This article is sponsored by Arkestro, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.

The manufacturing industry has changed in recent years. Humans on the shop floor have always used their senses and experience to anticipate machine failure before it occurs. Now, AI can be used in conjunction with human expertise.

ExxonMobil is the largest investor-owned company in the world and the largest oil company by revenue in the Western world.

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. 

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. 

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.

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.

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.

Insurance is a growing arena for AI adoption and in many cases, automation is leading the way to streamline customer experiences and the organizational pipelines behind them along the entire customer journey.