AI at the Checkpoint: TSA's Quiet Bet on Faster, Smarter Security

NASHVILLE, TN – June 16, 2026 – Travelers rushing through Nashville International Airport (BNA) this week may not notice anything different about the security checkpoint. The familiar gray bins, conveyor belts, and Computed Tomography (CT) scanners look the same as ever. But behind the scenes, a significant evolution in airport security is being put to the test. The Transportation Security Administration (TSA), in a close partnership with the Department of Homeland Security's (DHS) Science and Technology Directorate (S&T), is conducting a field assessment of an Artificial Intelligence software developed by the firm SeeTrue. It’s a quiet but critical step in a long journey to make security screening faster, more effective, and less burdensome for both passengers and officers.

This demonstration isn't about flashy new hardware; it's about the software running inside the machines. The technology, known as "Image on Alarm Only" (IOAO), aims to fundamentally change the workflow that has defined checkpoint security for two decades. Instead of a human officer scrutinizing the X-ray image of every single carry-on bag, SeeTrue's AI does the initial heavy lifting. It autonomously analyzes the detailed 3D images produced by the CT scanners, and only flags bags containing potential threats for human review. Bags deemed clear by the algorithm can, in theory, proceed without a human ever looking at the image. The goal is a paradigm shift from manual inspection of all to targeted verification of the few, a move that promises substantial gains in both efficiency and security effectiveness.

From Lab to Lane: The Mechanics of IOAO

The core of the SeeTrue system lies in its ability to augment, not replace, existing infrastructure. The AI software is designed to be hardware-agnostic, integrating with the advanced CT scanners that TSA has been steadily rolling out across the nation's airports. These scanners, a major upgrade from older 2D X-ray machines, provide a wealth of data by creating a three-dimensional model of a bag’s contents, which can be rotated and examined from any angle. This rich dataset is the perfect fuel for a sophisticated AI.

The IOAO process is deceptively simple in concept but complex in execution. The AI is trained on vast libraries of images containing thousands of types of prohibited items—from firearms and knives to explosives—as well as countless examples of benign objects. It learns to distinguish a harmless laptop from a potential explosive device with a high degree of accuracy. For the majority of bags that contain no threats, the system gives an automated all-clear. For the small fraction that trigger an alarm, the CT image is instantly routed to a TSA officer’s monitor, with the potential threat highlighted for immediate assessment. This frees up officers from the mentally taxing and repetitive task of clearing hundreds of mundane scans, allowing them to focus their training and expertise on resolving actual alarms.

This approach directly tackles the operational challenge of human fatigue, a known factor in screening errors. An AI doesn't get tired or distracted after hours on the job. While the system is not infallible, its consistent performance provides a baseline of security that is difficult to maintain across thousands of officers over millions of screening events. The Nashville demonstration is designed to validate this performance in a live, unpredictable airport environment.

The Partnership Powering Progress

This technology didn't appear at the airport overnight. Its presence at BNA is the result of a multi-year, methodical collaboration between the private and public sectors. In May 2023, SeeTrue was brought into a Cooperative Research & Development Agreement (CRADA) with the DHS S&T's Transportation Security Laboratory (TSL). The TSL, a federal lab dedicated to advancing transportation security solutions, put the AI through its paces in a controlled environment, validating its detection capabilities against rigorous government standards.

Following successful lab tests and a previous operational demonstration at Harry Reid International Airport in Las Vegas, the system earned its spot for further evaluation in Nashville. This phased approach—from lab to limited field test to broader operational assessment—is a hallmark of how DHS vets and adopts new technology. It’s a deliberate process designed to mitigate risk and ensure that new solutions are not just innovative, but also robust, reliable, and operationally sound.

"We are excited to work with DHS S&T and TSA to bring Image on Alarm Only (IOAO) into a live demonstration on our journey to make screening fast and secure," said Assaf Frenkel, SeeTrue's Co-Founder and CEO, in a statement. His gratitude towards the government partners underscores the symbiotic relationship required to move security tech from concept to reality. For the government, it provides access to cutting-edge innovation from the private sector. For companies like SeeTrue, it offers a crucial pathway to validation and market access.

The Operational Calculus: Throughput, Staffing, and Privacy

For airport operators and the flying public, the most anticipated benefit is speed. By automating the clearance of most bags, IOAO has the potential to dramatically increase passenger throughput at the checkpoint. This could mean shorter lines, less stress, and a better overall passenger experience—a key priority for airports competing for travelers. One security analyst noted, "The goal is to make the security process as seamless as possible without compromising safety. Automation is the only viable path to achieving that at scale."

Operationally, the technology shifts the role of the TSA officer from a universal screener to a specialized adjudicator. This has significant implications for staffing and training. Rather than needing a large pool of officers for primary image review, agencies can deploy personnel more strategically, focusing on alarm resolution, secondary screening, and passenger assistance. The human element remains critical; the AI flags potential threats, but a trained officer makes the final call and conducts any necessary physical inspection.

However, the implementation of AI in such a critical public function is not without its challenges. The system's accuracy is paramount. A high rate of false positives could negate efficiency gains by bogging down officers with unnecessary reviews. Conversely, a false negative represents a security failure. Continuous algorithm training and refinement are essential. Furthermore, privacy advocates are watching closely. While the system analyzes images of property, not people, the collection and analysis of any data on a mass scale raises valid questions about storage, access, and potential misuse. Ensuring robust data protection protocols and transparency will be as important as the technology's detection rate for earning public trust.

Navigating a Competitive and Regulatory Landscape

SeeTrue is a prominent player, but it is not alone. The aviation security market is a competitive field where established defense and security giants like Leidos, Rapiscan, and Smiths Detection are all investing heavily in their own AI and automation capabilities. Many are building proprietary AI into their own scanner hardware. SeeTrue’s strategy as a software-first company, designed to integrate with various hardware platforms, offers airports a degree of flexibility and may accelerate adoption by leveraging existing capital investments in CT scanners.

The ultimate gatekeepers are regulatory bodies. In Europe, SeeTrue has already achieved a key milestone with its approval from the European Civil Aviation Conference (ECAC) for a related automated detection standard. The ongoing TSA and DHS evaluations serve a similar purpose in the United States. A successful outcome in Nashville could place the software on a qualified products list, effectively giving a green light for any U.S. airport to procure and deploy the technology.

The path forward will likely be a gradual one. Pending the results of this assessment, a wider, phased rollout could begin, with the technology appearing at more airports over the next several years. This deliberate pace reflects the immense responsibility of securing the nation's airways. The quiet trial in Nashville is more than just a test of a new algorithm; it is a carefully managed step toward a future where airport security is driven by intelligent, data-informed execution.