16 February Blog

The AI You Don’t See Is the One That Should Worry You Most

​Many organisations confidently state that they understand how artificial intelligence is being used within their business. There may be approved tools, documented use cases, and even internal policies guiding responsible adoption.
Yet time and again, when organisations take a closer look, they are surprised — sometimes alarmed — by just how much uncontrolled or unsanctioned AI use is already happening under the surface.
This isn’t usually malicious. It’s human.
The Rise of “Shadow AI”
Just as shadow IT emerged when technology outpaced governance, we are now firmly in the era of shadow AI.
Employees are:

• Using public AI tools to draft emails, reports, or presentations
• Uploading sensitive data to get “quick insights”
• Relying on AI for decision support outside approved processes
• Experimenting with free or personal subscriptions unknown to IT or security

Often, this happens with the best of intentions — to save time, improve quality, or simply keep up with workload pressures.
But intention does not reduce risk.
Why Leadership Often Underestimates AI Usage
There are several reasons organisations misjudge the true extent of AI use:
1. AI is easy to access
No procurement process. No deployment. Just a browser and an idea.
2. Staff don’t see it as “technology risk”
Many view AI as a productivity tool, not something that falls under cybersecurity, privacy, or governance.
3. Policies lag behind behaviour
Even where AI policies exist, they’re often high-level, unclear, or poorly communicated.
4. AI adoption is happening faster than oversight
The speed of AI innovation has outpaced traditional risk and control frameworks.
The result? A growing gap between what leadership thinks is happening and what actually is.
The Hidden Risks of Uncontrolled AI Use
Unmanaged AI adoption can quietly introduce significant risk, including:

• Data leakage — confidential or regulated information shared externally
• IP loss — proprietary knowledge used to train third-party models
• Compliance breaches — privacy, financial, or industry obligations overlooked
• Inaccurate outputs — decisions influenced by hallucinated or biased responses
• Reputational damage — misuse becoming public before governance catches up

What makes this especially challenging is that these risks are often invisible — until something goes wrong.
This Is a Governance and Culture Issue, Not Just a Technical One
Trying to “block AI” rarely works. Employees will find ways around restrictions if the business value is clear.
A more effective approach starts with recognising that:

• AI use is already embedded in daily work
• People want to do the right thing but need clarity
• Trust, education, and enablement matter as much as controls

Organisations that succeed don’t just ask “What tools are being used?”
They ask:

• Why are people turning to AI?
• What problems are they trying to solve?
• How do we enable safe, approved, and transparent use?

Gaining Visibility Without Killing Innovation
Practical steps organisations can take include:

• Conducting AI usage discovery and risk reviews
• Updating policies to be practical, human-readable, and role-specific
• Training staff on safe AI use, not just prohibitions
• Clearly defining approved tools and data boundaries
• Embedding AI considerations into existing cyber and risk governance

Most importantly, organisations need to signal that they care — not just about compliance, but about helping staff use powerful tools safely and confidently.
Final Thought
The biggest AI risk for most organisations isn’t the technology they’ve approved.
It’s the AI they don’t know about — quietly shaping decisions, handling data, and influencing outcomes every day.
Visibility, governance, and a human-centric approach are no longer optional. They are essential to building trust, resilience, and long-term value in an AI-enabled workplace.
This Blog was written using AI!