The Intelligent Border: Fast. Agile. Secure.

Original broadcast 9/24/25

Presented by EY

The latest episode of Modernizing Government: The EY Insight explores how data, cloud, and emerging technologies are reshaping the mission of U.S. Customs and Border Protection (CBP) and the federal government at large. Francis Rose hosts discussions with George Kaczmarskyj, Principal for Government and Public Sector at EY, and Mark James, Executive Director of the Enterprise Cloud Services Division at CBP. Filmed on location at the EY Center for Government Modernization, the conversations highlight lessons learned from commercial sectors like financial services, the importance of data governance and trust, CBP’s cloud migration journey, the adoption of AI and edge computing, and the future of secure, agile border operations. Together, they shed light on how a fast, agile, and secure intelligent border is being built.

Data as an Enterprise Asset: Building Trust for the Intelligent Border

The modernization of border security begins with one essential foundation: data. In the opening conversation of The Intelligent Border: Fast. Agile. Secure., Francis Rose spoke with George Kaczmarskyj, Principal for Government and Public Sector at EY, about the parallels between commercial industry and government when it comes to managing and governing data as an enterprise asset.

Kaczmarskyj noted that some of the most important lessons for government come from the financial services industry. After the 2008 financial crash, regulators and institutions realized that a lack of collaboration and data sharing across front, middle, and back-office functions had left them blind to systemic risks. The solution, he explained, was to treat data as an enterprise asset, backed by investments in governance, quality, and architecture. That long-term effort has positioned financial services to take full advantage of advanced analytics and artificial intelligence (AI).

For government, particularly in mission-critical areas like law enforcement and border protection, the lessons are clear. Agencies must build trust in their data. That trust is achieved through integrity, accessibility, and quality. When leaders can rely on the accuracy of their information, they can apply advanced tools with confidence—whether that’s AI-driven analysis or decision support at the edge.

Kaczmarskyj outlined three key investment areas: governance, quality, and architecture. Governance means establishing accountability structures to determine who owns data, where it resides, and how it is managed. Quality involves implementing policies, tools, and continuous improvements to ensure reliability. Architecture requires building infrastructure to store, rationalize, and make data accessible. The technology, he pointed out, is not the most difficult part. Rather, the challenges lie in organizational processes and prioritization. Agencies must decide which data matters most to the mission, focus their resources there, and avoid being overwhelmed by the exponential growth of information.

While federal agencies are improving at both ingesting new data and curating older archives, the pace of data creation outstrips capacity. Borrowing again from financial services, Kaczmarskyj urged prioritization—deciding what data has the greatest mission impact. For border security, that means identifying datasets that most directly affect enforcement, safety, and decision-making.

The conversation closed with a recognition that modernization is not about technology alone. It is about culture, process, and disciplined investment. As Kaczmarskyj emphasized, building trust in data ensures that government professionals can apply analytics and AI in ways that strengthen the mission, just as financial services firms did to stabilize and strengthen their industry after crisis.

Key Takeaways

• Treating data as an enterprise asset is essential for mission success.

• Governance, quality, and architecture are the three critical investments for building data trust.

• Prioritizing which data matters most helps agencies manage overwhelming growth and prepares them for AI adoption.

CBP’s Cloud Transformation: Agility, AI, and the Future of Border Security

In the second segment of The Intelligent Border: Fast. Agile. Secure., Francis Rose sat down with Mark James, Executive Director of the Enterprise Cloud Services Division at U.S. Customs and Border Protection (CBP), joined again by George Kaczmarskyj of EY. The discussion detailed CBP’s remarkable cloud migration journey, its embrace of artificial intelligence (AI), and its forward-looking approach to edge computing and cybersecurity.

James described CBP’s cloud journey, which began in 2017 with the goal of moving out of legacy data centers under the Federal Data Center Consolidation Act and Cloud First/Cloud Smart initiatives. At the time, CBP faced the challenge of migrating over 276 applications with limited cloud experience. They approached the effort in three tiers: low-hanging fruit that could move quickly, applications designed natively for the cloud, and complex legacy systems that required modernization. By 2019, CBP had made significant progress, but the scale of the effort became clear. Today, 85% of CBP applications and over 40% of its databases—representing more than 25 petabytes of data—are in the cloud. That shift has enabled agility and scalability that were once unimaginable. For example, tariff changes announced by the administration can now be operationalized within minutes rather than months.

Agility and scalability, James emphasized, have transformed CBP’s ability to respond to mission needs. With cloud infrastructure, CBP can scale resources up or down instantly, track costs to the penny, and deliver capabilities at the speed of policy and operational demands. What once required long procurement cycles and static environments is now dynamic, efficient, and mission-aligned. Kaczmarskyj tied this back to the importance of data prioritization, noting that agencies must distinguish between the “defensive” use of data—protecting mission objectives—and the “offensive” use, where analytics and insights anticipate emerging needs. CBP’s cloud infrastructure supports both.

When CBP began its migration, zero trust was not yet a dominant concept. Today, it is central to the agency’s security posture. James explained how CBP evolved from perimeter-based models to a layered zero trust architecture that applies authentication, authorization, and monitoring at every level. Tools like Okta have helped implement these controls across cloud and edge environments. The shift has extended beyond cloud to operational technology at the border itself. CBP applies zero trust principles to edge devices and data sources, ensuring that security remains robust even in contested or remote environments.

One of CBP’s most ambitious initiatives is the deployment of edge computing. At ports of entry and along vast stretches of U.S. borders—including remote areas in Alaska and the Southwest—connectivity challenges make centralized data processing impractical. Instead, CBP pushes computing and AI models to the edge, allowing officers to process sensor data—video, ground sensors, cameras—in real time. James compared this to military strategies for distributed computing, while Kaczmarskyj noted parallels in energy and transportation industries, where real-time sensor feeds support predictive maintenance and operational safety. Both agreed that managing streaming sensor data requires new strategies for aggregation, governance, and timely decision-making. Streaming data is ephemeral—useful for immediate insights but less so for long-term storage. Agencies must balance real-time analysis with the need to capture patterns and trends for future analysis.

Artificial intelligence has been one of the greatest successes of CBP’s cloud transformation. By leveraging platforms like Databricks, SageMaker, and Vertex AI, CBP can build and deploy AI models rapidly. This has empowered not just developers, but also frontline officers who use AI-enabled tools to perform tasks more efficiently. The challenge now, James said, is governance. With AI demand surging across CBP, establishing clear controls and frameworks is critical to ensure responsible and effective use. Kaczmarskyj added that AI governance, like data governance, is an area where investments in people and processes will be just as important as technology.

As CBP prepares for the next phase, both James and Kaczmarskyj highlighted the importance of planning for technologies that may not yet be fully mature. AI at the edge is one such frontier—where video feeds from drones or sensors may need to be processed locally rather than pushed to the cloud. Lessons from autonomous vehicles and commercial industries provide guidance, but government will face unique mission requirements and constraints.

The discussion closed with a caution: success will depend on more than technology. Investments in governance, process, and culture will determine whether agencies can fully leverage the promise of cloud, AI, and edge computing. As James and Kaczmarskyj made clear, CBP’s journey is not only transforming border operations, but also serving as a model for how government can modernize to meet the challenges of a fast-changing world.

Key Takeaways

• CBP has migrated 85% of applications and 40% of databases (25+ petabytes of data) to the cloud, enabling agility and scalability.

• Zero trust and edge computing are central to securing and operationalizing data at ports of entry and along remote borders.

• AI has become a force multiplier, but governance is critical to ensure responsible, mission-aligned use.