AI didn’t storm in with board approval or a security checklist. It crept in unnoticed, drafting emails faster than you can read them, generating code on the fly, automating workflows behind the scenes, and empowering support teams with tools that feel harmless – until they aren’t.
This is how Shadow AI takes hold, not as a project, but as behaviour. And that is exactly why it has become one of the most dangerous risks most businesses are carrying today.
Shadow AI refers to any artificial intelligence system operating without security oversight, approval or governance.
It includes employees using tools like ChatGPT, Copilot, Perplexity or Claude for client work. It includes AI features silently embedded inside SaaS platforms.
It includes teams training internal models on company data without understanding where that data goes. It includes external AI agents with excessive access and bots that can read sensitive information, send emails, create files or delete them entirely. These systems are productive, efficient and largely invisible. And invisibility is where risk lives.
This risk is no longer theoretical. Threat actors are already weaponising AI in real world attacks. AI driven phishing campaigns now scale faster and adapt faster than human led operations ever could. Malware is being generated and reshaped continuously to evade traditional detection.
Self-learning agents are probing cloud environments for weak identity controls. Credentials are stolen and abused quietly.
Employees are impersonated convincingly across email, chat and even voice. These attacks are already happening, and J2 is seeing them in live environments.
The uncomfortable truth is that cyber resilience is no longer just about users, devices and networks. It is about understanding the behaviour of machines that act on your behalf.
Non-human identities now move data, make decisions and trigger actions at speed. When those identities are not visible or governed, they become perfect entry points for attackers.
Gartner identifies shadow AI as a critical blind spot for CIOs and cybersecurity leaders. A survey of cybersecurity decision-makers showed that 69 % of organisations suspect or have evidence of employees using prohibited AI tools, and Gartner predicts that by 2030 more than 40 % of enterprises will experience security or compliance incidents linked to unauthorized shadow AI.
J2 helps organisations bring this risk back into view. That means detecting when AI tools access sensitive systems, monitoring bot and non-human identity behaviour, flagging unusual activity across cloud and SaaS platforms and identifying Shadow AI before it becomes a liability.
It also means spotting AI driven attack techniques rather than relying solely on known malware patterns, and responding quickly when automation causes real world damage.
AI innovation does not need to stop, but it does need to be visible, governed and secured. If your organisation is using AI, officially or unofficially, now is the moment to take visibility seriously. You cannot protect what you cannot see.
