23 June 2026
For years, organisations have treated tracking cookies and artificial intelligence as separate issues. Tracking technologies were viewed primarily through the lens of privacy regulation and digital marketing, while artificial intelligence was seen as an emerging productivity tool. Increasingly, however, these two technologies are converging in ways that create a much more challenging cybersecurity environment.
Tracking Cookies Were Never Harmless
Traditional tracking cookies have always collected behavioural information. Websites record where users come from, what they search for, which pages they visit and how long they spend on each activity. Individually, much of this information appears harmless. In aggregate, however, it forms a surprisingly detailed picture of an individual’s habits, interests and relationships.
Artificial intelligence changes the significance of this information. Modern AI systems excel at identifying patterns, correlating seemingly unrelated data and constructing profiles that humans would struggle to assemble manually. AI systems can now combine and analyse information from previously separate databases at scale. They can transform browsing histories, advertising identifiers, device fingerprints, geolocation data and social interactions into detailed behavioural models that predict interests, preferences and even future actions.
Why AI Changes the Equation
This convergence has consequences that extend well beyond targeted advertising. Detailed profiles may assist attackers in crafting highly convincing phishing campaigns. AI-generated emails and messages can be tailored to an individual’s habits, language and interests, making social engineering attacks significantly more difficult to detect. Attackers no longer need to rely on broad campaigns when they can generate personalised approaches with minimal effort.
The problem grows because modern websites contain an enormous number of tracking technologies. Many organisations run dozens of third-party scripts on their sites without fully understanding what Many organisations run dozens of third-party scripts on their websites. They often do not fully understand what those scripts collect or where the data ends up. Analytics providers, advertising networks and customer engagement platforms frequently receive this information. AI systems can then combine and analyse it. The resulting insights may have little connection to the original purpose for collecting the data.
The risks are not limited to malicious actors. Legitimate organisations may themselves create unintended exposures. AI systems trained on large volumes of customer interactions and behavioural data can inadvertently reveal sensitive information or create profiles that exceed the expectations of users. The combination of pervasive tracking and increasingly capable AI raises difficult questions about consent, transparency and data minimisation.
Traditional cybersecurity frameworks have tended to focus on protecting systems from unauthorised access, malware and network attacks. Yet many of the emerging risks associated with AI and tracking technologies arise from authorised collection and lawful processing. Organisations can gather, share and analyse information through existing systems and remain technically compliant, yet still create outcomes that users regard as intrusive or unsafe.
As a result, organisations may need to rethink their approach to cyber risk. Questions that once belonged primarily to privacy teams are becoming security questions. Asset registers may need to include third-party scripts and tracking mechanisms. Organisations should consider how attackers could combine publicly available information, behavioural data and AI capabilities. Data minimisation is an important part of that defence. Once seen mainly as a privacy principle, it now serves as a cybersecurity control as well.
From Marketing Profiles to Personal Intelligence
The convergence of AI and tracking technologies illustrates a broader shift occurring across cybersecurity. The greatest risks are no longer always those associated with breaking into systems. Increasingly, they arise from the ability to connect, analyse and exploit information that organisations have willingly collected. In a world where artificial intelligence can turn fragments of behavioural data into detailed knowledge, the old assumption that “it is only a cookie” may prove dangerously outdated.
