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Hitachi Vantara Federal’s Pragyansmita Nayak on How Agencies Can Navigate AI Use Case Repository

Pragyansmita Nayak, chief data scientist at Hitachi Vantara Federal, said federal agencies should learn how to navigate the repository of artificial intelligence use cases as they work on strategies to incorporate AI into their workflows and align such strategies with their specific requirements.

In an opinion piece published Thursday in Federal Times, Nayak wrote that agencies can use a list of search terms to extract key information and insights from the repository without conducting extensive searching.

She called on agency leaders to understand their specific needs before deploying AI and stated that conducting training courses “tailored to the intricacies of AI applications” is one of the ways agencies can do.

“Training initiatives can bridge this knowledge gap, ensuring that leaders make informed decisions about AI implementation and align the technology with their specific objectives,” Nayak stated.

“This approach not only optimizes the benefits of AI but also guards against the potential pitfalls of uninformed adoption,” she added.

The Hitachi Vantara Federal executive said agency officials should take part in interagency evaluations, establish connections with points of contact, examine case studies and promote collaboration and knowledge sharing to facilitate AI implementation efforts.

With the release of the AI executive order, Nayak urged agency leaders to engage stakeholders and align AI implementation with organizational goals.

“Simultaneously, meticulous attention to regulatory compliance, scalability assessments, and user-centric training programs forms the bedrock of a robust AI strategy. Ongoing monitoring, agile implementation, and transparent communication foster adaptability and trust,” she added.

Register here to attend the Potomac Officers Club’s 5th Annual Artificial Intelligence Summit on March 21 and hear federal leaders and industry experts discuss the latest developments in the field.

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