Artificial Intelligence

Dell Has a Blueprint for U.S. Global AI Leadership

Infrastructure modernization, cybersecurity and energy resilience are key pillars to artificial intelligence success, according to the tech company.

Nathan Eddy

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill School of Journalism.

Dell submitted a blueprint for ensuring the U.S. maintains its global leadership in artificial intelligence in response to the White House’s request for comments on its forthcoming Artificial Intelligence Action Plan.

The blueprint is divided into six core areas: scaling infrastructure, energy resilience and infrastructure modernization, AI workforce development, leveraging AI to boost government efficiency, agile AI governance, and cybersecurity.

A federal action plan could solidify U.S. dominance in AI, and the White House Office of Science and Technology Policy aims to outline policy priorities for advancing innovation and avoiding over-regulation that could stifle industry development.

EXPLORE: Dell workforce solutions can help modernize your agency.

Scaling the Entire AI Ecosystem

Scaling AI computing infrastructure requires both sustained modernization and close collaboration across sectors because existing infrastructure often wasn’t built with AI in mind.

“There’s a need to continuously look at IT modernization as a whole,” says JP Marcelino, the AI/machine learning alliances manager for Dell Federal, pointing to the growing and rapidly shifting demands of AI workloads.

DISCOVER: The Department of Energy’s FASST initiative aims for a formidable scientific AI system.

Computing, storage and energy needs are deeply interconnected and must be scaled as a unified system.

“You’ve got to consider the whole ecosystem,” says Ken Rollins, federal technology architect for AI and edge at Dell Technologies.

Dell recommends establishing a national AI computing strategy to expand supercomputing capacity and boost domestic AI chip production.

Click the banner below to learn what’s next for artificial intelligence.

Modernizing Energy Systems To Power AI-Ready Data Centers

Sustainable AI growth depends on ensuring energy resilience in infrastructure from the outset.

“Looking at alternative energy sources will be key to a more energy resilient strategy for data centers,” Marcelino says. “That includes considerations around energy efficiency, for example, to more efficiently cool infrastructure.”

Scaling computing infrastructure also requires modernizing the surrounding energy systems.

“The government must strengthen, modify and modernize the grid,” Rollins says.

Innovations occurring with small modular reactors and solar will be needed to power the next generation of data centers.

“Updating the infrastructure gives you that increased compute capacity and allows you to do so in a smaller footprint,” Rollins says.

AI Workforce Development Hinges on Training and Retraining

Workforce development remains a core challenge in scaling AI across government, requiring a national education strategy emphasizing training in the technology and STEM.

“There’s a lot of things public companies like Dell can do to remove some of those challenges when it comes to not having enough resources readily capable of developing AI solutions,” Marcelino says.

Retraining current workers is just as important.

“We’ve got people in the workforce today, where the nature of their jobs is going to change over the next couple of years,” Rollins says. “Those who lean into how AI can enable them will be part of the momentum shift.”

Improving Government Efficiency With AI

AI can be used to automate repetitive processes and modernize outdated systems.

“Leveraging AI capabilities to do that in a more streamlined and efficient manner goes a long way to reducing costs,” Marcelino says.

Agencies might start with AI for automating HR processes or searching knowledge bases to save time and resources.

“We’ve got a chance to transform the way that government operates, how it interacts with the public and how it provides those services,” Rollins says. “The government should think about how it changes policies to make it easier for federal agencies to implement those changes.”

There must be a framework and governance model focused on how we can rapidly adopt new AI technologies to keep up with that pace of innovation.”

J.P. Marcelino AI/ML Alliances Manager, Dell Federal

Matching the Pace of AI Innovation Through Agile Governance

Agile governance must match the pace of AI innovation because the technology evolves faster than traditional oversight structures can handle.

“There must be a framework and governance model focused on how we can rapidly adopt new AI technologies to keep up,” Marcelino says.

Rigid, all-or-nothing approaches should be replaced with more testing environments and flexible regulation that recognizes the role of open innovation, Rollins says.

UP NEXT: Strategic optimization is key to navigating federal budget challenges.

Thwarting AI-Driven Cyberattacks With Sound Strategy

Cybersecurity must be embedded into every aspect of federal AI strategy as attack methods, many of which are AI-driven, evolve.

“There must be more coordination around AI security frameworks among federal government agencies, including maintaining zero-trust frameworks,” Marcelino says.

An AI cybersecurity strategy must encompass infrastructure, policy, technology, processes and people.

“Security is probably one of the hardest things that has to be tackled as we move forward with AI,” Rollins says. “We've got a whole new set of tools using AI to analyze vast amounts of data and respond proactively. It’s not an insurmountable challenge, but it will be a continual effort.”

Brought to you by: