I’ve spent most of my career trying to understand people through the signals and images they leave behind. Long before ambient data and smartphones reshaped our digital lives, my work in ISR and Electronic Warfare involved interpreting whatever emissions, optical signatures, and spectral clues we could capture and turning them into a coherent story about intent, movement, and behavior. Whether it came from radio waves, full-motion video, or hyperspectral sensors, the goal was the same: piece together patterns that revealed what someone was doing and why.

Over time, the environment shifted. Devices multiplied, networks expanded, and digital behavior became woven into everyday life. As the technology evolved, so did the methods of collection and analysis. I eventually moved from broader, strategic collection into more tactical operations, where the focus narrowed. Instead of tracking large regional patterns, we were examining granular signatures and building very specific targeting pictures. The mission was still about understanding the story, but the way we assembled that story changed with every new device, every new platform, and every new digital habit people adopted.

Back then, we weren’t targeting advertising data or commercial behavioral models, especially before the smartphone era. Those systems existed in small pockets, but not at the scale or sophistication we see today, and certainly not in the environments where we were operating. On the intelligence side, we could only imagine having access to the kind of psychographic and behavioral detail that now comes standard through everyday apps and services.

And that’s what led me to Ambient Data Surveillance, or ADS. It’s one of the most overlooked components of modern digital life, not because it’s hidden, but because it feels normal. ADS isn’t covert. It isn’t exotic. It’s simply built into how the internet works. But the insights it produces – the behavioral patterns, preferences, beliefs, and motivations – are often more revealing than anything we captured through traditional signals or imagery intelligence.

This is the environment we live in now: a digital landscape where routine behaviors generate continuous data, and that data can be modeled, sold, and repurposed in ways most people never think about.

What ADS Really Is

Ambient Data Surveillance is the continuous, usually passive collection of behavioral and contextual information through the digital services we use every day. It doesn’t rely on espionage or technical compromise. It doesn’t require a breach or a backdoor. It simply exists because modern technology is built to observe, measure, and personalize. And we’ve opted in.

Every interaction we make online or through our devices – every tap, pause, search, location check, or scroll – feeds into this system. ADS is less about the data point itself and more about the pattern those points create over time. It reveals preferences, motivations, routines, and the subtle psychological drivers behind them.

Importantly, ADS doesn’t just map consistency; it also highlights the moments when behavior changes. A sudden shift in content consumption, a new pattern of late-night searches, a break from typical location-linked routines, or even an unusual sequence of clicks can all flag anomalies in a person’s digital behavior. These deviations can be more revealing than the behavior itself because they point to shifts in mindset, stress, intent, or circumstance. In many cases, an anomaly in what someone consumes online can be as significant as an anomaly in how a device behaves on the spectrum.

This is why ADS is so different from traditional surveillance. UTS shows where devices are and how they move through space. ADS shows what the person behind the device is paying attention to, how they think, what they’re drawn to, and what might influence their next decision. One maps presence, the other maps intent.

The most important thing to understand is that ADS wasn’t designed for intelligence or security. It was built for advertising and engagement. That’s what makes it so powerful. It’s everywhere, built into apps and platforms we never question, collecting a level of behavioral detail that would have been unimaginable in earlier eras of signals intelligence.

And because ADS is so deeply embedded into daily life, most people never recognize it for what it is: a commercial system that has quietly evolved into one of the most comprehensive behavioral intelligence engines in history.

How ADS Works

You don’t need an engineering background to understand how ADS operates. Behind the scenes, it follows a simple cycle: collect, connect, interpret, and repurpose. The details get complicated, but the logic is fairly straightforward.

Data Starts Everywhere

• Mobile apps and the ad software built into them
• Browsers and third-party trackers
• Location services
• Wi-Fi networks
• Loyalty programs
• Connected devices, from watches to cars
• Everything is tied to convenience or personalization

Each source extracts a different slice of a person’s digital behavior. No single piece is very revealing on its own, but together they form the outline of a life.

Small Pieces Become a Profile

Once collected, these fragments don’t stay isolated. They’re shared, sold, and cross-referenced across platforms. Identity isn’t confirmed by a single data point; it’s assembled through repetition and correlation. Over time, these systems become very good at knowing who’s who, even when people think they’re anonymous.

Behavior Gets Modeled

From there, the data is fed into algorithms that look for patterns. They pay attention to timing, habits, preferences, the content you pause on, and the things you ignore. The goal isn’t to store every action, but to understand the behavior behind it. Eventually, the system can predict what you’re likely to do next, often with surprising accuracy.

Psychographics Give It Meaning

This is where ADS shifts from observation to influence. The models start to map personality traits, emotional tendencies, political leanings, life-stage markers, and susceptibility to certain types of messaging. The intent isn’t just to see what someone does, but why they do it, and what might change their behavior.

The Data Gets Repurposed

Finally, the information gets packaged and distributed. Some of it goes to advertisers, some to data brokers, and some to organizations looking for any type of advantage – commercial, political, or operational. This part makes people uncomfortable, but it’s the reality: ADS creates a behavioral dataset that anyone, including foreign actors or criminal groups, can obtain if they know where to look and have money to pay for it.

The entire system is built around one idea: human behavior is predictable when you have enough data, and ADS provides more data than any intelligence discipline ever has.

Why ADS Matters: The Infrastructure of Influence

ADS isn’t just a system for collecting data; it’s the foundation that shapes what people see, what they pay attention to, and how they move through the digital world. Most of the influence is subtle. It happens quietly, through recommendations, curated feeds, targeted ads, suggested videos, and search results that have been tailored to your profile long before you type anything. This is where ADS becomes far more than a privacy issue. It becomes a behavioral issue.

As ADS models mature, they don’t just track what you’re doing. They try to anticipate where your attention is going next. They look at the posts you linger on, the categories you scroll past, the conversations you return to, and the emotional tone of the content you choose. Over time, the system becomes good at recognizing your interests, stressors, insecurities, beliefs, ambitions, and the small psychological cues that influence how you respond to information.

This is the part most people overlook.

Influence doesn’t begin with a message. It begins with understanding the mindset of the person receiving it.

ADS gives organizations the ability to tailor messaging with a degree of precision that would have been impossible a decade ago. And it’s not only advertisers who benefit. Political campaigns, advocacy groups, malicious actors, foreign intelligence services, disinformation networks, and criminal organizations all leverage behavioral data to make their messaging more effective. The danger isn’t that ADS always manipulates people. The danger is that it can, and often, without the person realizing it.

ADS enables:

• micro-targeted political content
• emotionally calibrated persuasion
• selective visibility of narratives
• tailored influence operations
• social and ideological segmentation
• content strategies designed to amplify division or unity

None of this requires a breach, a hack, or a compromise. It only requires access to the behavioral data people give away every day.

This is what makes ADS so significant. It doesn’t operate at the level of devices or networks; that’s UTS. ADS operates at the level of cognition and emotion. It shapes the environment around a person’s attention and gently nudges them toward certain choices, beliefs, or reactions.

Understanding ADS means understanding that the digital world is no longer a neutral space. It’s structured around models built from our own behavior, and those models can be used to persuade, steer, or influence at scale.

How ADS Enables Threat Actors

ADS was never intentionally designed for intelligence or exploitation, but it has become incredibly useful to anyone looking for insight into people or organizations. The same behavioral data that helps advertising platforms decide which video to show next can also reveal patterns, relationships, and vulnerabilities to actors with very different intentions.

Nation-State Adversaries

Foreign intelligence services have learned to treat commercial data as a shortcut. Instead of relying solely on traditional collection, they can buy or illicitly obtain datasets that reveal:

• movements of military personnel
• the routines of diplomats and attachés
• the travel habits of intelligence officers
• undisclosed personal or professional associations
• location-linked anomalies in high-risk environments
• psychographic tendencies that support targeting or influence

Open-source reporting has shown that commercial app data has exposed the presence and movement of U.S. forces in multiple overseas locations. No hacking was required. The data was simply available to anyone who knew where to acquire it.

For a nation-state adversary, ADS acts as a form of persistent, low-cost situational awareness; an ambient picture of people and units that would have taken significant resources to build in the past.

Criminal Organizations

Criminal groups rarely need sophisticated tools. ADS gives them something far more efficient:

• Indicators of wealth or lifestyle
• Predictable routines
• Time-of-day activity patterns
• Relationship networks
• Vulnerabilities linked to health, addiction, or financial stress
• Personal information that supports social engineering
• Occupancy risks for burglary or targeting

Some criminals already use data brokers to identify potential victims, selecting people based on purchasing behavior, life events, or perceived vulnerabilities. These uses aren’t theoretical. They’ve been documented repeatedly across open-source investigations.

ADS allows criminals to filter the world the same way advertisers do, but with very different goals.

Corporate and Competitive Intelligence

In the private sector, ADS can expose far more than companies realize. Behavioral and operational signatures often reveal:

• supply chain disruptions before they’re public
• executive travel linked to deals or negotiations
• hiring patterns that signal expansion or contraction
• employee sentiment and internal stress indicators
• workflow timing and facility activity
• market strategy shifts
• potential insider threat behavior

Competitors and third-party intelligence firms already use these datasets to gain an advantage. When cross-referenced with UTS signals, ADS becomes a powerful tool for anticipating business moves or uncovering operational blind spots.

High-risk industries such as energy, law, defense contracting, logistics, and finance are especially exposed because their activity patterns are more valuable and more heavily monitored by adversarial actors.

Impact Across Society

ADS isn’t a niche issue reserved for governments or major corporations. Its influence stretches across daily life, professional environments, and national security. The impact looks different in each domain, but the underlying dynamic is the same: behavioral visibility creates exposure.

Defense and Intelligence

For the defense community, ADS introduces a type of vulnerability that traditional counterintelligence frameworks were never designed to address. Even when service members follow strict OPSEC guidelines, their digital behavior continues generating a constant stream of commercial data in the background; data that can be purchased, aggregated, modeled, and analyzed by anyone with the resources or the intent.

ADS reveals much more than a person’s routine. It reveals identity.

Commercial datasets can expose:

• unit-level activity patterns
• deployment cycles and dwell timing
• social networks within and around units
• personal stress signals and lifestyle indicators
• repeated visits to sensitive or high-risk locations
• cross-platform behavior that ties personas together

Attribution Through Data Exhaust

Attribution used to be difficult. Analysts had to connect signals, habits, and fragments of intelligence across multiple domains. ADS changes that calculation. Behavioral data like app usage, mobility patterns, browsing categories, purchase habits, and general device usage can link a real identity to an online persona, an alias, or even a device previously considered unconnected.

For military personnel, intelligence officers, and anyone working under a cover or compartmented identity, this becomes a direct risk. A commercial dataset doesn’t care about compartmentalization; it simply resolves the pattern.

Association Mapping at Scale

ADS also makes associations easier to map. A person’s connections – friends, partners, coworkers, recurring contacts, even casual acquaintances – become visible through shared behaviors, synchronized movements, overlapping interests, and co-located device activity.

An intelligence service doesn’t need to penetrate classified systems to understand a network anymore. They can infer association from repeated digital proximity, shared consumption patterns, or behavioral co-occurrences that recur over time.

This level of visibility would have required enormous collection resources in the past. Now it’s bought in bulk.

Operational Impact

When attribution and association come together, the exposure becomes structural. ADS can support:

• identifying hidden relationships or compromised networks
• tracking travel linked to sensitive operations
• inferring mission tempo
• profiling units or organizations through behavioral signatures
• spotting anomalies that may suggest preparation, stress, or impending activity

Even in environments where UTS exposure is minimized, ADS continues to build the human picture behind the device. The result isn’t a single point of compromise. It’s a persistent, evolving behavioral portrait of the force.

Law Enforcement

For law enforcement, ADS introduces visibility that affects both personal safety and operational effectiveness. In recent years, that exposure has grown even more pronounced. Social and political dynamics, especially in border regions, transit corridors, and areas near ports of entry, have increased the operational visibility of officers and investigative teams. Criminal organizations have become more sophisticated in how they observe, track, and react to law enforcement presence, often using the same commercial datasets that advertisers rely on. Officers generate digital behavior like anyone else, but adversaries now have more ways to interpret those behaviors and turn them into opportunities.

ADS reveals more than routine. It exposes the rhythms, habits, and digital signatures that surround law enforcement work, both on and off the clock. These behavioral patterns can be analyzed to understand how officers operate, where they spend time, and when they’re likely to be active.

Criminal organizations exploit ADS to identify:

• daily and weekly routines
• off-duty locations and habits
• shift changes and predictable patrol windows
• investigative team associations
• recurring travel or surveillance activity
• personal vulnerabilities that support harassment or intimidation
• routes used by undercover or plainclothes units

For investigative and tactical units, ADS exposure can impact operations. Changes in officers’ digital behavior – travel anomalies, new device patterns, late-night searches, or unusual communications with certain apps – can signal operational tempo or upcoming actions. Criminal networks that monitor commercial data streams can spot these shifts long before law enforcement makes overt contact.

Criminal Exploitation

Modern criminal groups don’t need advanced SIGINT capabilities. Many rely on commercially available data brokers, compromised app ecosystems, and off-the-shelf analytics tools to gather information. Some use browsing behavior, mobility datasets, or cross-platform identifiers to detect undercover activity, track narcotics teams, or anticipate raids. Others simply use ADS to identify officers’ families or personal routines for intimidation or coercion.

This type of exploitation doesn’t require a breach. It only requires access.

Operational Impact

ADS affects officer safety in ways that traditional situational awareness training wasn’t built for. It influences how investigations can be compromised, how patterns in digital behavior reveal operational tempo, and how officers’ personal lives create opportunities for adversarial groups. Even when an agency protects its internal systems, ADS continues to map the human layer around those systems, generating visibility that criminals can leverage.

Law enforcement agencies often focus on cybercrime prevention and technical protections, but ADS introduces a parallel challenge: behavioral visibility that adversaries can use to map, anticipate, or counter law enforcement actions.

Corporate Sector

Companies often underestimate how much of their internal activity becomes visible through ADS. The data doesn’t expose the content of internal meetings or communications, but it reveals the behavioral shape of the organization: how people move, when they collaborate, where they travel, and how work gets done.

Those signals can uncover:

• executive travel linked to sensitive negotiations
• energy usage rhythms tied to manufacturing cycles
• employee stress or dissatisfaction
• emerging insider risk indicators
• office occupancy and operational patterns
• supply chain timing and vulnerabilities
• market posture before public announcements
• opportunities for social engineering

In competitive markets, these types of insights are extremely valuable. That’s why corporate intelligence firms buy commercial data the same way marketers do. And in high-risk sectors – law, energy, finance, logistics, defense contracting – the exposure can directly affect negotiating leverage, security posture, and operational resilience.

ADS turns internal dynamics into observable behavior, even if the company never shares anything publicly.

Civil Society

For individuals, ADS is woven into the fabric of everyday life. It’s present when we scroll, shop, travel, search, or simply carry a device from one place to another. Most people accept this as the cost of convenience, but the long-term impact is more meaningful than it appears.

ADS contributes to:

• loss of privacy by default
• micro-targeted persuasion
• personalized misinformation
• emotional manipulation
• behavioral shaping through curated feeds
• algorithmic reinforcement loops
• detailed profiling by organizations that the individual has never interacted with

The immediate risk isn’t always obvious. It’s not someone stealing data. It’s the fact that a person’s digital behavior is constantly analyzed to predict how they think, what they believe, and what they might do next.

Outside the U.S., the consequences can be even more severe. Authoritarian regimes already leverage similar data streams for population control, suppression of dissent, and political coercion. While the American system is commercial first and governmental second, the underlying mechanisms are similar, and the visibility they create is the same.

ADS is part of the modern social contract, but we didn’t negotiate the terms.

The ADS-UTS Interlock

ADS and UTS often get discussed separately, but in practice, they work together. UTS shows where devices are in space, how they move, and when their behavior changes. ADS shows what the person behind the device is paying attention to, how they think, and what might influence them. Each layer reveals something different, but the real visibility comes from how the two interact.

Presence + Behavior = Narrative

UTS provides the physical and technical footprint:

• Location/movement
• Timing
• Identity
• Emissions
• Device presence
• Associations
• Anomalies linked to operational activity

ADS provides the cognitive and behavioral footprint:

• Interests
• Motivations
• Emotional drivers
• Digital routines
• Relationships
• Content-linked anomalies

When those footprints overlap, they create a narrative that is far more complete than anything either system can generate on its own. A movement pattern without context is just a route. A behavioral pattern without location is just a preference. Together, they reveal intent.

Anomalies Become Easier to See

One of the most important connections between ADS and UTS is anomaly detection. A device that suddenly goes quiet is suspicious on the UTS side. But a person whose content patterns abruptly change is suspicious on the ADS side.

When both anomalies align, the signal becomes unmistakable.

This is where operational activity becomes visible. Even if one dataset is well protected, the other continues generating behavioral clues.

Identity Becomes Harder to Hide

Even well-trained personnel struggle to mask both layers. Someone might be disciplined about device usage (UTS) but still reveal intentions or stress through their digital behavior (ADS). Or they may be careful about what they search or consume (ADS) but expose themselves through mobility or emissions (UTS).

For foreign intelligence services, criminal networks, and commercial data brokers, these two layers don’t need to be collected from the same source. They simply need to overlap. The datasets stitch themselves together.

The Organization Becomes Visible Too

The interlock doesn’t only reveal individuals. When enough behavioral and technical signatures are aggregated, it can outline the rhythm of a unit, business, law enforcement agency, or diplomatic mission. You can see when an organization is preparing for something, how its tempo shifts, when stress rises, and when operations go quiet.

This is why the ADS-UTS interlock is more than a privacy concern. It has direct implications for operational security, national security, competitive advantage, supply chain integrity, personal safety, and the way organizations manage risk.

Together, ADS and UTS form the operational core of the Ubiquitous Surveillance Ecosystem described in Part I. They are the mechanisms that give USE its reach, depth, and permanence. Understanding them separately reveals how each layer creates visibility; understanding them together shows why USE has become the defining feature of the modern digital landscape. These systems aren’t theoretical. They’re active, interoperable, and shaping the environment around every organization and individual today.

CohēCiv’s Perspective

At CohēCiv, we view ADS and UTS through a simple lens: technology may capture the data, but human behavior creates it. The visibility that organizations struggle with today isn’t the result of a single device or platform. It’s the result of countless small habits, preferences, routines, and digital decisions that accumulate into a picture more detailed than most people expect.

Firewalls and encryption still matter, but they can’t shield the behavioral layer that ADS and UTS reveal. That’s why we focus so heavily on understanding how people interact with technology and how those interactions scale into organizational exposure. The problem isn’t just technical. It’s cognitive, operational, and cultural.

Defending against modern surveillance requires knowing what the systems see, how they interpret behavior, and how small choices influence the larger narrative built around a person or a team. Once you understand the structure of that visibility, you can begin to reduce unnecessary exposure and make more deliberate decisions about how you engage with the digital world.

Our approach isn’t about fear or restriction. It’s about awareness.

When organizations recognize their behavioral footprint, they gain the ability to manage it. And in a world shaped by ADS and UTS, that awareness is one of the most valuable assets they can have.

Closing

ADS and UTS have changed the way individuals, organizations, and entire societies are seen. They operate quietly in the background, collecting and interpreting the small signals that define modern life. Understanding these systems doesn’t require technical expertise. It requires recognizing that digital behavior – what we do, when we do it, and how consistently we repeat it – is now part of the operational landscape.

This article is part of Beyond Firewalls, a series exploring the human dimension of digital risk and the systems that shape our visibility in a connected world. For leaders, operators, and professionals across every sector, the challenge is the same: learn to see the environment as it truly exists, not as we wish it were.

Because in a world defined by behavioral data, clarity is protection.