Sponsored Feature You may have already analyzed AI use cases for artificial intelligence (AI) within your business and identified potential efficiencies, revenue opportunities, and more.

Now comes the hard part: building an infrastructure to support your mission. Computing capacity is a critical part of that portfolio, but companies often overlook another equally important ingredient: storage.

Investing heavily in the latest GPUs or cloud capabilities to give yourself a head start in training and inferring AI models is important, but it will all be for naught if you can't feed the beast the data it needs to deliver results . That's where scale-out technology comes in – to help organizations answer the infrastructure questions posed by this new world of AI.

"Data is a differentiator for companies involved in AI," said Tom Wilson, a product manager at Dell Technologies with a strong focus on AI workloads, which analogizes data as fuel, compute as engine and storage as fuel tank.