Tune in May 13th at 8:30p on WJLA 24/7 News or Watch it here.
Presented by Booz Allen
Driving Outcomes Through Data explores how federal agencies are embracing data-centric strategies to transform mission delivery, accelerate modernization, and unlock the full potential of emerging technologies. Filmed on location at The Helix, Booz Allen’s Center for Innovation in Washington, D.C., the program features top technology leaders from the public and private sectors sharing insights on cloud transformation, agentic AI, fraud prevention, and data governance. Through a series of dynamic conversations, the program captures how agencies are aligning digital infrastructure with mission needs to deliver real results for the American people.
Cloud and the Mission: Scaling for the Future
Richard Crowe, Civil Sector President at Booz Allen, opens the program with a look at how cloud adoption has matured across government. Agencies have moved beyond migration into more mission-focused, multi-cloud environments. Crowe explains that the most forward-leaning agencies are making cloud decisions based on mission criticality, performance needs, and resilience. He highlights the growing use of edge computing, scalable delivery models, and hybrid architectures to meet real-time mission requirements. Crowe also stresses the importance of open architecture and data provenance, especially as agencies prepare for broader AI deployment. With citizen services and national security on the line, he argues that government demands a level of reliability and security that often exceeds that of the private sector.
Key Takeaways:
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Agencies are embracing multi-cloud environments tailored to mission-specific needs.
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Edge computing and scalable delivery are critical for time-sensitive, distributed operations.
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Open architectures and data provenance are foundational to secure, AI-ready modernization.
Realizing Cloud’s Potential as a True Transformation Accelerator
Larry Taxson, Digital Capabilities Delivery Executive at the CIA, discusses how the agency’s modernization strategy has evolved into a global, multi-cloud architecture. He explains how the CIA is layering managed services and AI capabilities—particularly small language models—into cloud environments to support specialized intelligence missions. Taxson shares how real-time analytics and edge capabilities are extending mission execution even into space. He emphasizes that successful digital transformation depends on strong collaboration between mission stakeholders, cloud service providers, and integrators, each bringing unique insights to the table. CIA’s journey reflects a broader shift in government from isolated systems to flexible, scalable, and secure cloud ecosystems.
Key Takeaways:
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CIA is leveraging multi-cloud platforms, managed services, and AI to support global operations.
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Edge and space-based computing are extending the reach and impact of cloud systems.
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Collaboration between agencies, integrators, and cloud providers drives mission-aligned innovation.
Digital Transformation: Improving Government Efficiency through Data
Matt Carroll, CEO of Immuta, explains how data democratization requires strong classification, access controls, and dynamic monitoring to ensure secure, mission-aligned use. Dan Tucker, Senior Vice President of Data and AI Engineering at Booz Allen, outlines the modern data stack, including observability, semantic layers, and interoperability across data domains. Austin Gerig, Chief Data Officer at the SEC, shares how the agency’s data strategy, developed under the Evidence Act, is already yielding results—highlighting a landmark insider trading detection initiative. The panel collectively reinforces that data strategy, governance, and tooling must work in concert to empower users and enable scale.
Key Takeaways:
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Data classification, access governance, and observability are critical to trusted data sharing.
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Semantic layers enable machine understanding and scalable analytics.
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The SEC’s use of strategic data governance directly enabled major enforcement actions.
Harnessing Agentic AI for Critical Federal Missions
Shane Shaneman, Senior AI Strategist at NVIDIA and Sahil Sanghvi, Vice President, Chief Technology Office at Booz Allen describe how agentic AI is moving beyond traditional automation to autonomous systems capable of executing complex tasks. Shaneman defines agentic AI as a leap forward from prompt-based chat tools—enabling digital agents to learn tasks, collaborate with other agents, and operate independently. Sanghvi emphasizes that access to contextualized data, governed by identity and usage policy, is essential to enabling these systems. Both speakers stress that successful adoption requires a balance between short-term pilots and long-term, secure, scalable infrastructure that can adapt as mission needs evolve.
Key Takeaways:
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Agentic AI enables autonomous agents to perform complex tasks without human orchestration.
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Secure, contextualized access to data through a semantic layer is foundational to success.
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A strategic blend of short-term experimentation and long-term infrastructure is essential.
AI-Enabled Delivery of Mission-Critical Software Systems
Sanjeev “Sonny” Bhagowalia, CIO at U.S. Customs and Border Protection, shares how CBP processes over 50 billion daily data exchanges across 1,700+ locations. He explains how the agency is embedding edge computing, cloud infrastructure, and AI directly into frontline operations—from ports of entry to air and marine assets. Bhagowalia stresses the importance of authoritative data sources, agile IT integration, and co-located development teams that work hand-in-hand with mission operators. He also highlights CBP’s leadership in post-quantum cryptography and wearables, pushing the boundaries of secure, field-ready innovation.
Key Takeaways:
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CBP leverages AI, edge computing, and cloud to support real-time decisions at the border.
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Embedding IT teams with operational units ensures agile, mission-driven development.
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CBP is pioneering post-quantum cryptography to secure future-state architectures.
Digital Transformation Protects Against Fraud, Waste, and Abuse
Jared Smith, Chief Statistician at the U.S. GAO, outlines how agencies are modernizing fraud detection by embedding risk mitigation into day-to-day workflows. He emphasizes that successful fraud prevention starts with intentional strategies—identifying risk areas, assigning ownership, and ensuring relevant data is accessible and actionable. Smith discusses the use of large language models to analyze unstructured data and flag anomalies that may indicate fraud. He cautions that while the tools are promising, strong foundations—such as clean data, clear governance, and close IT collaboration—are essential to scale.
Key Takeaways:
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Fraud risk management must be built into agency operations from the ground up.
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LLMs offer exciting new ways to analyze narratives and identify suspicious behavior.
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Agencies must first build strong data governance and collaboration frameworks to succeed.