First published on March 12, 2021, on Hewlett Packard Enterprise's Enterprise.nxt, publishing insights about the future of technology. Edge computing and AI promise to make healthcare delivery cheaper, easier, and better for everyone. It couldn't happen at a better time. Here's one problem the pandemic has underscored: A healthcare system that was not terribly efficient to begin with now seems stressed to the breaking point. Infectious diseases are on the rise.

AI is a retailer's automated helper, acting as a smart assistant to suggest the perfect position for products in stores, accurately predict consumer demand, automate order fulfillment in warehouses, and much more. The technology can help retailers grow their top line, potentially improving net profit margins from 2 percent to 6 percent -- and adding $1 trillion in profits to the industry globally -- according to McKinsey Global Institute analysis. It can also help them hold on to more of what they already have by reducing shrinkage -- the loss of inventory due to theft, shoplifting, ticket switching at self-checkout lanes, etc. -- which costs retailers $62 billion annually, according to the National Retail Federation. For retailers, the ability to deploy, manage and scale AI across their entire distributed edge infrastructure using a single, unified platform is critical. Managing these many devices is no small feat for IT teams as the process can be time-consuming, expensive and complex.

For decades, artificial intelligence (AI) lived in data centers, where there was sufficient compute power to perform processor-demanding cognitive tasks. In time, AI made its way into software, where predictive algorithms changed the nature of how these systems support the business. Now AI has moved to the outer edges of networks. "Edge AI happens when AI techniques are embedded in Internet of Things ( IoT) endpoints, gateways, and other devices at the point of use," explains Jason Mann, vice president of IoT at SAS. "Put another way, edge computing brings the data and the compute closest to the point of interaction," says Red Hat chief technology strategist E.G. Nadhan. Edge AI is a very real (and rapidly expanding) phenomenon, powering everything from smartphones and smart speakers to automotive sensors and security cameras.

Neville Vincent says the combination of hyperconverged infrastructure, edge computing and AI is driving value and insights to new levels. While cloud has been a key component to AI's exponential growth and its availability on nearly every technological device, the combination of hyperconverged infrastructure HCI), edge computing and AI provides the ideal environment to uncover patterns in data from multiple devices and predict future performance or issues. It is driving value and insights to new levels. The adoption of hybrid cloud -- enabled by HCI and public cloud and combined with AI and data gathered from the edge -- offers granular visibility into operations, enabling real-time, comprehensive and actionable intelligence. Through this combination businesses will become self-learning, flexible, self-determining and able to adopt next-generation infrastructure to help realign their operations, personnel, business and even business models.

According to the IHS Markit white paper, The Top Trends of 2019: Powered by Transformative Technology, three key trends are expected to have a major effect on both commercial and consumer markets in 2019. The increasing ubiquity of video is forcing significant industry change, as a growing number of players vie for consumer attention and revenue and as businesses adapt to cope with the rising demand. In fact, online video subscriptions from over-the-top (OTT) and traditional media players alone will more than double between 2017 and 2022, by which time they will approach the one billion mark. While TV, home entertainment, social media, video games and other media sectors are at the heart of the video everywhere trend, other industries – including security, education, and healthcare – are also becoming increasingly reliant on video technology. The edge is already transforming the way networks are deployed and devices are built.

The huge coverage devoted to the topics of AI and edge computing sparked an idea when I recently visited JFK Airport. My journey coincided with a severe weather storm that disrupted travel along the East Coast. This situation illustrates how customer service agents assist passengers (at the edge) when dealing with uncertainty and changing circumstances (relying predictive analysis and intelligent decision-making under uncertainty). The IoT is imminent – and so are the security challenges it will inevitably bring. Get up to speed on IoT security basics and learn how to devise your own IoT security strategy in our new e-guide.