A deputy general counsel once told me that during their AI risk training, her team had reviewed a new AI-based customer support tool. The vendor’s documentation looked flawless, the privacy section thorough, the compliance certifications impressive. Still, one of her newer team members hesitated. “Can we ask where the data labeling was done?” she asked quietly.
It turned out the vendor’s training data had been outsourced across multiple jurisdictions, one of which lacked adequate data protection safeguards. That single question, asked by a curious mid-level lawyer, prevented an exposure that would have taken months to unwind.
Spotting AI risk is no longer the exclusive job of the GC. It is a shared language every lawyer in the department must speak fluently. The goal is to make AI awareness a reflex rather than a specialty.
Turn Legal Teams into Pattern Recognizers
The first step is to move from issue spotting to pattern recognition. AI risks rarely appear in isolation. They travel in clusters. A biased model often hides a data privacy issue, an over-trained algorithm often conceals an IP problem, and a generative model’s output might carry privilege risk if training data included internal communications.
Hold a recurring AI Risk Radar session once a month. Choose one current project or vendor relationship and walk through it collectively. Ask three questions. What AI elements are present? What data is being used or produced? What could go wrong if those elements malfunctioned? Over time, the team learns to see AI risk not as a new category of law but as a variation on familiar themes of duty, consent, and ownership.
Pattern recognition turns abstract fears into tangible questions. The habit builds confidence, curiosity, and discernment.
Teach the Red Flags Until They Become Reflex
Every team needs a shared checklist. Begin with five core red flags that should trigger a deeper look.
The project uses or references an algorithm or model that is not fully explainable.
The system relies on third-party data, especially if training data provenance is unclear.
AI tools are deployed without defined human review or escalation steps.
The output could influence employment, pricing, or other rights-sensitive decisions.
Any vendor promises that human oversight is unnecessary.
Print this checklist and circulate it widely. Post it in internal channels and include it in contract intake forms. The goal is not to slow the business but to prompt better questions earlier.
When team members can recite these triggers by memory, AI risk awareness stops being an occasional project and becomes a cultural reflex.
Build Confidence Through Simulation
Awareness grows fastest through practice. Once a quarter, host a 60-minute simulation. Present a realistic scenario such as a marketing team wanting to use an AI copywriting tool or a data team proposing to train an internal model on customer feedback. Divide the legal team into small groups and ask them to identify possible risks and mitigation strategies.
When you debrief, focus on the reasoning behind each answer. Reward the thought process more than the outcome. Over time, your lawyers learn to articulate not just what feels risky but why. This ability to explain risk in simple, practical terms is what executives value most.
Empower Judgment, Not Fear
A common mistake in risk training is overemphasis on prohibition. If every conversation ends with “we can’t do that,” the team will stop asking questions. Replace fear with ownership. Teach your lawyers to frame feedback as “safe if” rather than “unsafe because.”
For example, instead of saying “we can’t use this AI vendor because it touches customer data,” say “we can use this if the vendor allows contractual audit rights and if data is properly anonymized.” This small linguistic shift changes the department’s culture from gatekeeping to partnership.
The GC’s job is not to turn lawyers into AI experts but into problem solvers who can assess context and propose pathways forward.
Institutionalize What the Team Learns
Create an internal AI risk log that collects real examples from your organization. Each time someone spots a potential issue such as biased data, missing consent, or overbroad model training, capture the facts, how it was found, and how it was resolved. Review the log quarterly and distill recurring themes into a one-page AI Lessons Learned memo.
This living archive becomes your most valuable governance tool. It transforms isolated incidents into shared institutional wisdom and helps onboard new team members quickly.
Model Calm, Curious Leadership
The way you handle AI risk discussions shapes your team’s behavior. When you model calm curiosity rather than alarm, your team learns that AI issues are manageable. When you praise thoughtful questions more than quick answers, you teach humility and rigor.
At leadership meetings, reference examples from your own team’s vigilance. Give credit by name. Recognition reinforces the behavior you want repeated.
A team that knows its GC values insight over fear will surface concerns early, speak up confidently, and treat AI risk as a problem to manage, not a secret to hide.
The Leadership Standard
AI awareness is the new legal literacy. The GCs who will succeed in the next decade will not be those who know every regulation but those who can cultivate teams that learn faster than the risks evolve.
Teaching your team to spot AI risk is not an academic exercise. It is the foundation of modern legal leadership: seeing what others miss, staying calm when others react, and creating a culture where curiosity is protection.
If your lawyers know how to ask the right questions before the world does, you have already won half the battle.
