The new AI Risk Factors No One is Talking About

AI Has Entered the Chat… and the Risk Stack

In boardrooms, risk meetings, and LinkedIn thought pieces, one theme dominates: AI is changing everything. Fast.

But for all the noise, one question keeps getting missed: What happens when AI goes wrong?

Most companies are too overwhelmed to answer. They’re caught in an OODA loop—trying to Observe, Orient, Decide, and Act in a landscape that shifts by the week. Policy is lagging. Tools are being trialed on the fly. Processes are being layered on top of already complex systems. Meanwhile, employees are being asked to move faster, smarter, more creatively—without the clarity, training, or support they actually need.

And the result? The seeds of new, invisible risk are being sown across every part of the business.

Most headlines focus on big-picture fears: AI-generated misinformation, bias in training data, nation-state attacks, or mass job displacement. These are real and urgent.

But what about the risks your people face today?

• Misuse of generative AI tools

• Shadow AI usage across departments

• Misconfigurations of AI agents or copilots

• Inadvertent data sharing with third-party platforms

• Loss of IP and sensitive information through casual use

The truth? AI workforce risk is skyrocketing, and many organizations aren’t even measuring it.

Here’s what no one is talking about—but should be:

• Misalignment of Risk Leadership: Legal, IT, and Security may each have different views on AI risk, creating confusion.

• Cultural Invisibility: Employees using tools without realizing they are creating risk (or simply not knowing it’s against policy) or unclear tolerance of digital risk. 

• Digital Exhaustion: Employees are overloaded by change. The less agility you have as an organization, the more risk AI accelerates.

• Overconfidence in Tools: Many believe AI tools are secure or "smart enough" to prevent errors—until they don't.

• Lack of Safety Signals: Few employees receive nudges, guidance, or feedback about AI usage.

AI doesn’t just amplify productivity. It amplifies whatever your culture allows.

AI is like planting a lush, fast-growing garden. The flowers bloom faster than we imagined. But buried in the soil are toxic seeds we didn’t see—invisible to the naked eye, but guaranteed to take root if left unattended.

These are the human risk factors: unclear expectations, conflicting signals, unmeasured behaviors, and a culture that hasn’t caught up to the speed of technology.

Can AI fix itself? Possibly. But it won’t happen automatically. It needs context, constraint, and conscious culture-building around it.

If you want to manage AI risk, you can’t wait for a breach to see the shape of it.

You need to:

1. Map Workforce AI Risk Factors

   • Who is using AI? For what? With what data?

   • Where are the riskiest behaviors, misunderstandings, or shortcuts?

2. Measure AI Enablement and Shadow Usage

   • Track readiness and risk indicators across roles, teams, and tools

   • Identify gaps in transparency, training, and approved access

3. Assess Your Digital Risk Culture

   • Is there psychological safety to report Shadow AI usage?

   • Are teams aligned on the ethical, secure, and strategic use of AI?

4. Invest in AI-Aware Awareness

   • Go beyond compliance. Help people understand AI mistakes, misuse, and the ripple effects of their digital choices

Information security. Data loss prevention. Governance and compliance. These are foundational.

But the core of AI risk management? It’s about human behavior. How people understand, engage with, and adapt to the new world of AI tools.

The time you’re not dedicating to education, awareness, and safe usage? That’s time your AI risk debt is quietly compounding.

We help organizations measure, map, and manage that risk—with tools built for human factors, cyber culture, and organizational resilience.

Don’t wait until your AI garden goes to seed. Get ahead of the risk. Let’s grow something safer.