Commissioned Artificial intelligence (AI) promises to change the world. But AI algorithms are only as good as the data sets they’re built on. Since most data is generated and consumed outside of traditional data centers and clouds, you need the ability to capture and process data where it’s created – at the edge.

AI is shaking up nearly every industry, with innovative new use cases that demonstrate the power of processes, products and services driven by AI. For example, the ability to perform real-time, AI-driven analytics on customer data enables hyper-personalized interactions at scale. Research shows that using AI for marketing personalization can increase sales by up to 20 percent and customer loyalty by as much as 15 percent. Other forms of personalization, such as AI-driven recommendations, can more than quintuple conversion rates, and other reports suggest dynamic pricing strategies can increase sales by 2 to 5 percent.

As impactful as these results are, AI alone isn’t the driving force. It’s the results of hard, fast math informed by mountains of data too large for the human mind to make sense of. But the conclusions reached by an AI algorithm are only as good as the data sets it feeds on. To get the results that keep you ahead of AI-enabled competitors, your AI algorithms need a rich diet of high-quality data. That means data that is copious, consistent, complete, correct and correlated to the task at hand. And, increasingly, that means data that is captured from your edge.

Great data leads to great AI

The edge is where people live, work and play, making it a space rich with valuable data. Analysts predict that data volumes for low-latency, edge-critical workloads will grow at an 80 percent compound annual growth rate (CAGR) over the next several years, nearly tripling from 5,700 to 194,000 petabytes by 2027 according to Building a Sustainable Enterprise Edge 2023, an S&P Global Market Intelligence Pathfinder Paper commissioned by Dell Technologies.

The need to generate business value from this data will drive significant growth in edge computing deployments, as organizations recognize that not every workload should move to the cloud.

The need to support ultra-low-latency workloads, the increase in very-high-volume data sources and data sovereignty and security requirements encourage enterprises to keep more data closer to its point of origin instead of sending it to and from the cloud for processing. At the same time, a proliferation of smart devices, sensors and endpoints – and the massive number of sites at which they may be located – have also increased demand for edge computing to make sense of it all.

In this atmosphere, it’s no surprise that 56 percent of organizations are already using edge computing infrastructure in production, and another 28 percent are in a trial or proof of concept stage. Spending on edge compute is poised to explode, as 79 percent of enterprises say they are planning to increase budgets for edge IT this year, 32 percent of those “significantly” according to the Building a Sustainable Edge report. As a result, analysts predict that just 38 percent of edge-critical data will be processed in cloud or core locations as early as 2027, as a range of on-premises and near-premises edge venues take on more of the processing load.

With the shift of compute power to the edge, we gain the ability to run AI workloads on edge data for immediate insights that we could not access in the past. That’s where the real magic happens.

AI at the edge in action

Here are just some of the results our customers see when they move AI-enabled compute out to the edge.

Dell Technologies recently collaborated with Atos, a global system integrator based in France, to unlock new business value across edge environments. Combining the Atos Business-Outcomes-as-a-Service (BOaaS) managed services solution with Dell NativeEdge, an edge operations software platform that centralizes deployment and management of edge infrastructure and applications across geo-distributed locations, speeds time to value for customers.

The unique edge deployment and management approach we’ve developed incorporates principles such as centralized management, zero-touch deployment and zero-trust security to provide a consistent, secure experience across edge hardware and devices. The combined capabilities of Atos and Dell Technologies can enable customers to obtain meaningful, rapid and repeatable business outcomes from Internet of Things (IoT) data streams and analytics while managing their edge ecosystem from a single dashboard.

In the vertical farming world, Dell Technologies has helped ZERO fuel a revolution in agriculture, by bringing AI to the edge to advance innovations that are both financially and environmentally sustainable. We’ve also helped Nature Fresh Farms accelerate sustainable greenhouse crop yields with faster, scalable access to AI and computer vision at the edge. We worked with Citizens of the Great Barrier Reef to develop a deep learning AI model that has transformed reef analysis and conservation. And we helped The Kraft Group reduce IT costs, improve employee and customer experiences and advance sustainability goals across their sports and entertainment ventures.

A great AI strategy happens at the edge

We’re shifting into an exciting new era, one where the relationship between machines and humans will change profoundly. In a recent keynote speech Mary Mesaglio, Managing Vice President at Gartner, said that “we’re moving from what machines can do for us to what machines can be for us.” Dell Technologies is excited to be a part of the evolution, helping machines be better, with great data from the edge.

To learn more about the benefits of edge data, check out our latest eBook, The journey to the edge, Vanson Bourne eBook (delltechnologies.com).

Brought to you by Dell Technologies.

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