AI Articles and Analysis about Business intelligence and analytics

DHL is a German logistics company that offers parcel delivery, express mail, freight forwarding, and third-party logistics. Its parent company is Deutsche Post (‘DPDHL’), the world’s largest logistics enterprise, operating in over 220 countries and employing more than 510,000 people worldwide. 

Although not often regarded as a technological first-mover, the insurance industry has recently seen robust, even rapid, adoption and deployment of AI capabilities, particularly in those related to natural language processing (NLP). 

A paradigm shift is happening in the manufacturing industry. Advancement in big data and machine learning is changing traditional manufacturing processes into the era of intelligent manufacturing. The concept of what gets called "industry 4.0" encourages the use of smart sensors, devices, and machines – going beyond the motives of collecting data about production. 

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.

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.

Actionable, decision-augmenting data can be obtained internally or externally. Of course, external data is a far richer and more diverse source, as it comprises every other piece of digital information outside of the four walls of an enterprise. 

Episode summary: In this episode, we speak with Alan O'Herlihy, Founder and CEO of Ireland-based Everseen. Alan speaks to us about how machine vision systems can be used to detect theft or mistakes at a checkout counter (including forgetting to scan items, customers intentionally hiding items, and more). Alan not only explains where these technologies are in use today, but he also breaks down some of his own predictions about what these computer vision systems might make possible in the workplace of tomorrow.