The modern battlefield isn’t confined to war zones overseas, it’s evolving rapidly along the U.S. border. Criminal organizations like the Juarez and Sinaloa cartels are leveraging commercial technology, decentralized networks, and real-time adaptability in ways that challenge traditional intelligence models. At the center of this shift is a growing gap between how threats evolve and how intelligence systems respond.
Former military intelligence specialist, Stefano Ritondale, and current the Chief Intelligence Officer at Artorias joins the podcast to provide insights on UAV threats, OSINT, and strategic implications for the U.S. from a national security perspective.
Legacy AI and the Blind Spot Problem
Federal intelligence agencies have invested heavily in AI-driven systems, but many of these tools were built for structured environments: terror networks, state actors, and historical datasets. Cartels don’t operate that way. They move fast, adapt constantly, and rely heavily on informal, open channels of communication. That creates a dangerous mismatch. Legacy AI systems often prioritize structured data like reports, signals intelligence, and known patterns, while missing the dynamic signals emerging in real time across social media, encrypted messaging apps, and even drone footage shared online. The result is a blind spot where the most immediate threats are often the least visible.
The Drone Evolution Gap
Cartels are no longer just using drones for surveillance. They’re deploying them for human smuggling coordination, cross-border reconnaissance, and potentially more advanced operations. The pace of innovation is uneven—and not in the U.S.’s favor. While cartel groups can rapidly adopt off-the-shelf technology and modify it within days or weeks, U.S. counter-UAS capabilities are often slowed by procurement cycles, regulatory constraints, and legacy systems. This creates a persistent lag. In practical terms, by the time a countermeasure is deployed, the threat has already evolved.
OSINT as a Force Multiplier
Open-source intelligence is one of the most underutilized tools in the intelligence ecosystem. Cartel activity is increasingly visible in open channels, including TikTok videos, Telegram posts, drone footage, and local reporting. Analysts tracking these signals in real time can often identify patterns and emerging threats before they surface in classified channels. Yet OSINT remains siloed. Agencies often treat it as supplementary rather than operational, and insights generated from open sources don’t always flow seamlessly into decision-making pipelines. Integrating OSINT directly into all-source intelligence workflows and treating it as actionable in real time would significantly improve threat detection and response.
The El Paso Airspace Signal
The reported closure of airspace in the El Paso region to deploy counter-UAS systems reflects a significant escalation. This is not simply precautionary—it signals that drone activity tied to cartel operations has reached a level where traditional law enforcement measures are no longer sufficient. For residents and local agencies, it underscores that airspace is now an active domain of criminal activity and that federal response measures are evolving to meet that reality.
Cartels have always evolved, but the pace has accelerated in recent years. Groups like Juarez and Sinaloa have shifted between drones, tunnels, and decentralized smuggling routes while rapidly adopting commercial technologies faster than governments can regulate them. At the same time, they have reduced reliance on centralized command structures, making disruption more difficult and increasing their resilience against enforcement efforts.
Risks to U.S. Law Enforcement
For law enforcement in regions like El Paso, the threat landscape is becoming more complex. The risks are not only physical but also informational and technological. Agencies face limited visibility into real-time cartel movements, increased use of drones for surveillance against law enforcement, and the growing weaponization of commercially available tools. These challenges are compounded by intelligence gaps created by fragmented data systems and slow integration of emerging information sources.
The Case for a Dedicated OSINT Capability
One of the most compelling solutions is the creation of a dedicated OSINT-focused intelligence capability. Currently, open-source intelligence efforts are fragmented across the Department of Defense, DHS, and the broader Intelligence Community. While each entity collects and analyzes open-source data, coordination is inconsistent and often inefficient. A more centralized and operationally focused approach would allow for faster aggregation of real-time data, improved dissemination of actionable intelligence, and a stronger connection between analysis and field operations.
Cartel operations now sit at the intersection of criminal enterprise and hybrid warfare. Addressing this reality requires rethinking intelligence architecture from the ground up. Modernization efforts must focus on integrating AI systems capable of processing unstructured, real-time data, reducing silos around OSINT, and expanding counter-UAS capabilities that can keep pace with rapid technological change. Equally important is accelerating procurement and deployment timelines so that defensive capabilities are not perpetually lagging behind evolving threats.
The United States is not facing a static adversary, but an adaptive, technology-enabled network operating in increasingly visible ways. Closing the gap will require more than incremental improvements. It will require a fundamental shift in how intelligence is collected, analyzed, and operationalized. The challenge is not a lack of information, it is the ability to recognize and act on it fast enough. In many cases, the warning signs are already there, hiding in plain sight.
