Walk the floor at AI+ Expo and you’ll see no shortage of innovation. But you’ll also hear a lot of buzzwords. For decision-makers evaluating CUAS (counter-uncrewed aerial system) solutions, it’s easy to get lost in the noise. What’s real? What’s marketing fluff? And how do you know if AI is actually making a system smarter—or just making it sound smarter?

At Hidden Level, we’ve been deploying real-world AI-powered airspace monitoring for years. Our systems are actively tracking and helping defeat hostile drones across the U.S. and beyond. If you're looking to cut through the clutter and understand what AI is truly doing for drone defense, this breakdown will help.

Key Takeaways Include:

The most effective AI depends on data—lots of data

AI is only as effective as the data it’s built on—and our RF sensors deliver more of the right data than any other aerial sensing technology. Compared to video or acoustics, RF sensing provides richer signal intelligence, better low-altitude fidelity, and continuous coverage that captures both cooperative and non-cooperative emitters.

RF Sensing Unlocks the AI Advantage

With the right data, AI can accelerate detection, fill in tracking gaps, reduce false positives, and intelligently prioritize threats. As systems evolve, AI will also automate key decisions—especially in high-pressure environments like the battlefield—turning milliseconds into mission-critical action.

Ask Two Questions to Cut Through the Hype

As modern uncrewed aerial systems (UASs) are used as weapons or for other nefarious activities, AI is quickly becoming a differentiator between CUAS systems designed to deliver airspace safety and security. But just how do you assess the AI capabilities of various CUAS systems? Ask two key questions:

1. What data do your AI models utilize?

Ask what raw sensor data is available, how it is filtered, and how it is used. Understand how adaptable the AI system is in adding data from other sensors or sources. The more data an AI model has available to it—both real-time and historical—the better able AI will be to learn and adapt without human intervention.

2. What functions are your AI models providing?

Beyond great algorithms that perform valuable functions, the true value of AI is in learning and adapting. CUAS systems can detect, track, and classify UASs; assess potential threats; prioritize targets; and in some systems, automate response. For each discrete function, ask for details about how AI is enabling that function to learn and adapt. Does it help reduce the time to perform a function? Does it improve accuracy and how well it works as its experience grows?

Five Ways AI Powers Smarter Airspace Control

Detection and Tracking

AI speeds detection of UASs through RF fingerprinting, whether they are cooperative, non-cooperative, RF-silent, or using deceptive techniques, such as link encryption or spoofing. AI combines multiple sensing sources together—holistic sensor fusion—and provides the most comprehensive airspace awareness through pattern recognition and incorporating environmental intelligence. CUAS systems utilizing complex predictive models that consider RF characteristics, operator behavior prediction, real-time trajectory data, and topographical terrain data anticipate a flight path and help locate operators when they are out of detection range. AI could even be used to anticipate UASs before they launch using known and predictive RF signatures and patterning.

Classification

Advanced algorithms and proprietary machine learning techniques combined with a deep dataset of historical data accurately classify UAS, virtually eliminating false positives. And as UAS technologies evolve, so does our AI. For example, as new drone types or weapons are introduced, AI can quickly detect and adapt to novel signals, craft types, or other anomalies, and train new algorithms by using stored historical and live data. The speed of AI autonomy can be the difference between successful deterrence and catastrophic outcomes.

Threat Assessment

AI is instrumental in accelerating decision making by determining potential targets and threat intent of nefarious or otherwise unknown drones and alerting airspace security personnel. Assessing the capacity of a drone to enact damage by evaluating intention based on distance, directionality, size, and speed determines the urgency of response. As new and emerging threat profiles are identified, AI can rapidly reprogram software-defined sensors to enable rapid detection and response.

Target Prioritization

AI simplifies the decision-making process by cutting through the clutter to present clear decision points, identifying genuine threats more effectively. By analyzing RF data streams and UAS behavior, AI provides personnel with a single source of information and a consolidated view of risk-prioritized targets in complex scenarios. AI can also inform the positioning of security assets and strategies through predictive intelligence based on past experiences.

Autonomous Systems Management

The promise of AI in airspace monitoring is to enable autonomous real-time safety and security at digital speeds. AI is automating air traffic control systems to improve safety and amplify the capabilities of human operators. End users can even enable AI-powered systems to automate instantaneous threat response through integration of various sensing and countermeasures.

‍

Hidden Level Data Powers the Smartest CUAS AI

At Hidden Level, we believe superior detection starts with superior data. That’s why our systems are built not just to sense, but to deliver the richest, most actionable datasets in the CUAS space—fueling AI models with both the quantity and quality needed to truly perform.

Our multi-function passive RF sensors operate across an exceptionally wide frequency band (400MHz to 6 GHz), capturing more relevant RF activity than narrow band or single-purpose systems. They run continuously—not episodically—creating persistent, high-fidelity data sets ideal for machine learning. Each sensor is capable of generating hundreds of terabytes of RF data per day, capturing signal activity from both cooperative and non-cooperative emitters across large regional areas.

But we don’t stop at raw data. Hidden Level also delivers extensive post-processing support, enriching these massive datasets with labeled events, contextual metadata, and operator-specific insights. This makes our data not only voluminous, but directly usable for training, refining, and validating adaptive AI models.

Our distributed sensor networks each generate millions of signal events per day—fueling AI that detects earlier, classifies more accurately, and responds faster to real-world threats. Simply put—better data makes better AI. And no one delivers data like Hidden Level.

Smarter Defense Starts with Smarter Data

AI has the potential to transform airspace security—but only when paired with the right foundation. Hidden Level delivers that foundation through high-fidelity, high-volume RF data and deep operational expertise. Our passive sensor networks are already driving real-world results, enabling faster detection, sharper classification, and more confident decision-making.

In an environment where buzzwords are easy and results are rare, we bring substance. We’re not just talking about AI—we’re powering it with unmatched sensing infrastructure, enriched metadata, and continuous support to help operators stay a step ahead.

Whether you're evaluating vendors or building the next generation of CUAS systems, ask the tough questions and demand the data to back it up.

Let’s talk about how we can help you turn AI promise into airspace protection.

If you are at SCSP's AI+ EXPO, swing by booth #1013 to continue the conversation.