U.S. border security agencies are faced with the challenge of managing vast amounts of data and increasingly complex threats, while public expectations call for both heightened security and accountability.
Zach Beus, national security lead at i2 Group, a Harris Computer company, suggests leveraging artificial intelligence, data integration, and unified analytic standards to transition from reactive to proactive operations.
Addressing Data Fragmentation
Beus, who has a background as an intelligence officer for the National Geospatial-Intelligence Agency, emphasized that border authorities’ challenge is not merely the volume of data but its diverse and siloed nature.
He pointed out that agencies such as Customs and Border Protection (CBP) and Immigration and Customs Enforcement (ICE) gather a wide array of data from various sources, including shipping manifests and social media. However, much of this data remains compartmentalized, hindering efficient analysis.
“We need to start shifting from siloed databases toward platforms that more easily integrate structured, semi-structured, and unstructured sources of data,” Beus stated. He also highlighted the importance of federated search capabilities for improving efficiency in data analysis.
Integration and Governance
Independent studies reinforce the need for breaking down data silos. A 2025 Gartner report identifies legacy systems and fragmented data as significant obstacles to the effective application of artificial intelligence in public sector missions.
Analysts stress that integration and governance are critical to success, not just new tools.
The Impact of AI on Analysis
Artificial intelligence, according to Beus, can significantly alter the role of analysts
Artificial intelligence, according to Beus, can significantly alter the role of analysts. By utilizing machine learning and natural language processing (NLP), tasks such as entity resolution and pattern detection can be automated, allowing analysts to focus on more complex assessments.
“AI changes the role of an analyst from finding a needle in a haystack to interpreting why that needle matters,” Beus noted.
The ISC² AI Pulse Survey (2025) echoes this transformation, finding that 70 percent of security professionals using AI report improved team effectiveness and a shift towards higher-value tasks.
Establishing AI Standards
Despite the potential advantages, Beus warns against rapid adoption of AI without setting clear standards, highlighting the legal and operational risks of unstandardized AI usage. “If there’s not a common approach, we might get into some really big problems,” he said, underscoring the need for transparency and uniform protocols.
The Cloud Security Alliance’s “State of AI and Security” survey (2024) highlights similar concerns, with many IT and security experts endorsing the need for standardized AI practices to maintain trust and accountability.
Balancing Security and Civil Liberties
Beus exemplified how AI reduces the number of analysts needed for data sorting
AI's role in border operations must consider security and civil liberties. As Beus explained, trust is crucial for AI acceptance, and oversight measures are being introduced to ensure accountability.
Agencies are adopting frameworks to explain AI decision-making, thereby reinforcing ethical practices.
AI also offers resource allocation advantages. Beus exemplified how AI reduces the number of analysts needed for data sorting, allowing for more strategic and long-term assessments.
Innovative Tools for Analysts
In response to these developments, i2 Group has been updating its Analyst’s Notebook platform. New capabilities include natural language processing for document analysis, automated insights from spreadsheets, and geospatial mapping for real-time visualization of movements.
“Our focus is making the analyst less of a data manager and more of an analyst,” Beus commented, highlighting the importance of tools that simplify visualization and collaboration.
Collaborative Efforts in Border Security
Beus emphasizes that no single solution fits all border security challenges. Effective partnerships, combining advanced tools with legacy integration, are essential. “Their missions are incredibly complex,” he remarked, stressing the value of intelligence-led strategies in enhancing border management.
Conclusively, as border management becomes more technologically sophisticated, Beus believes that leveraging both human expertise and technological advancements is vital. “We’re in a really good position right now to leverage both people and technologies,” he concluded.
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U.S. border security agencies are under pressure to adapt to a new intelligence reality: an environment where data volumes are exploding, threats are increasingly sophisticated, and public expectations demand both security and accountability.
According to Zach Beus, national security lead at i2 Group, a Harris Computer company, the solution lies in harnessing artificial intelligence, data integration, and shared analytic standards to shift from reactive to proactive operations.
Beus, a former intelligence officer with the National Geospatial-Intelligence Agency who has supported missions in Afghanistan, Latin America and on the U.S.-Mexico border, said the challenge facing border authorities is not simply one of size.
“It’s not just that the data is large,” he told BizTechReports in a recent vidcast interview. “It’s that it’s diverse, fast-moving, fractured, and siloed. Agencies have more information than ever before, but they can’t always use it effectively.”
Breaking down silos
Customs and Border Protection (CBP), Immigration and Customs Enforcement (ICE), and other agencies collect shipping manifests, travel records, sensor feeds, financial intelligence, and even social media data. But much of that information remains trapped in isolated databases, slowing analysis.
“We need to start shifting from siloed databases toward platforms that more easily integrate structured, semi-structured and unstructured sources of data,” Beus said. He added that federated search capabilities could help analysts conduct a single query across multiple jurisdictions, dramatically improving efficiency.
“When I was an analyst, I’d sometimes have to perform searches 16 times across different systems on the same person,” he said. “That’s not sustainable.”
Independent surveys
Independent surveys underscore the urgency of breaking down silos. A 2025 Gartner study on government productivity and AI warned that legacy systems and fragmented data remain the biggest obstacles to unlocking the full potential of artificial intelligence in public sector missions — including intelligence and other national security applications.
Analysts concluded that integration and governance, not just new tools, are essential for success.
Role of AI
Beus argued that artificial intelligence can redefine how analysts work. Machine learning and natural language processing (NLP) can automate tasks like entity resolution, link analysis, and pattern detection, allowing humans to concentrate on higher-level assessments.
“AI changes the role of an analyst from finding a needle in a haystack to interpreting why that needle matters,” he said. “Instead of just answering who, what, when and where, analysts can now focus on the why — intent, context and long-term implications.”
Industry data reflects this shift. The ISC² AI Pulse Survey (2025) found that 70 percent of security professionals using AI-enabled tools reported improved team effectiveness, with most saying the technology freed them from repetitive data sorting and let them focus on higher-value tasks.
Establishing standards
Still, Beus cautioned against moving too fast without establishing standards. A lack of common protocols for using AI could create legal and operational risks.
“At some point, whether you’re a local police department or the CIA, you may be asked in a court of law how you derived information from AI,” he said. “If there’s not a common approach, we might get into some really big problems.”
That concern is widely shared. The Cloud Security Alliance’s “State of AI and Security” survey (2024) found that while 63 percent of IT and security pioneers expect AI to significantly enhance threat detection, many stressed the need for transparency and standardization to maintain trust and accountability.
Security, civil liberties, and the workforce
Indeed, trust will play a key role in encouraging acceptance and adoption of AI in border operations, because the mission itself raises ethical and policy considerations. “The government will need to balance national security and civil liberties,” Beus said.
The good news is that growing maturity around how AI applications are used is being accompanied by new oversight measures designed to ensure transparency and accountability. Agencies are beginning to adopt explainability frameworks and audit practices that help demonstrate how algorithms arrive at their findings, reinforcing ethical utilization in sensitive missions.
Reallocating scarce resources
As those concerns are addressed, agencies can focus on how AI can reduce workloads and reallocate scarce resources. “For instance, it might have taken a hundred analysts to sift through or scan manifest logs, but now it takes 10 analysts,” he explained.
“So now we have 90 analysts that can do other things. They can look for long-term intelligence challenges. They can conduct strategic assessments that previously weren’t possible because we didn’t have the human capital to do it. Now we can be much more cutting edge — and from a policy standpoint, that’s a significant change.”
Tools for the analyst community
i2 Group, which has served defense, law enforcement and intelligence organizations for more than 30 years, is updating its flagship Analyst’s Notebook platform to meet these challenges. New features include:
- Natural Language Processing: Analysts can drag and drop unstructured documents, and the system automatically extracts entities, links and properties.
- Automated Insights: Data from spreadsheets can be normalized and visualized instantly, producing dashboards that highlight critical connections.
- Geospatial Mapping: Movement of phones, vehicles or people can be visualized in near real time, providing predictive insights into trafficking or migration patterns.
“Our focus is making the analyst less of a data manager and more of an analyst,” Beus said. “We want to give them tools that simplify visualization, collaboration and sharing — whether that’s through digital files, PowerPoint decks, or wall-sized maps for operational planning.”
Partnerships as an imperative
Beus stressed that border security has no one-size-fits-all solution. Agencies need ecosystems of partnerships that blend cutting-edge tools with legacy integration expertise. “Their missions are incredibly complex,” he said.
“The most effective partnerships are those that combine AI and graph analytics with the ability to connect old and new technologies under real-world constraints.”
Intelligence-led methods
As border management grows more high-profile and technologically intensive, Beus sees intelligence-led methods as essential.
“We’re in a really good position right now to leverage both people and technologies,” he concluded. “We just have to put the right emphasis at the right time to support the analysts on the front lines.”
