Let’s talk about AI safety tools…
As generative AI adoption accelerates across business functions, so does the pressure on IT, Security, and Compliance leaders to keep usage safe, compliant, and auditable.
The problem? Most off-the-shelf tools weren’t built for this.
You don’t just need another firewall or DLP system.
You need a layer that understands how people actually use AI—and helps them use it responsibly.
What Makes AI Tool Procurement Challenging
The truth of the matter is — organizations are grappling with the unchecked proliferation of AI tools—often embedded in tools without coordination. TechRadar warns this “AI sprawl” increases inefficiencies, costs, and governance gaps. The solution? A unified approach that emphasizes tool interoperability, centralized governance, and streamlined compliance across AI ecosystems.
As generative AI features become part of everyday tools, procurement playbooks need serious updates. Reuters recommends reviewing and pushing back on vendor terms—especially regarding rights to customer inputs/outputs, confidentiality obligations, IP control, and service-level agreements with GenAI providers.
Lastly, corporate tools are evolving: AI governance platforms now include model inventories, real-time usage monitoring, risk scoring (e.g. bias, privacy), policy enforcement, regulatory alignment (e.g., NIST, EU AI Act), and audit-ready documentation. Thus, FairNow stresses the importance of requiring model cards from AI vendors—a concise overview of model performance, biases, training methods, and limitations. This clarity is crucial for trust, debugging, and regulatory confidence.
That said, here’s our take on what to look for in an AI safety solution that works in practice—not just in theory.
1. Visibility Without Surveillance
The best tools give you insight into how AI is being used—without compromising user trust.
✅ What to look for:
- Browser-level monitoring that detects risky patterns like PII pasting or file uploads
- Anonymized or role-based logs (not screen recording or keylogging)
- Insight into tools being used (e.g. ChatGPT, Claude, Bard) and prompt risk categories
🚫 Red flag:
- Heavy-handed monitoring that feels invasive and erodes employee trust
2. Real-Time Guidance, Not Just Blocklists
You can’t block your way to safety. Employees will always find new tools—and workarounds.
✅ What to look for:
- Prompt-level guidance in the flow of work
- Contextual nudges (“This might contain sensitive data”)
- Pre-submit friction: lightweight warnings, not hard stops
🚫 Red flag:
- Tools that only operate at the network or API level with no browser awareness
3. Support for Shadow AI Use
Let’s be honest—AI use is already happening in the shadows. Your safety tool should help you surface it, not punish it.
✅ What to look for:
- Detection of unsanctioned tools or risky prompt types
- Data on volume, tool usage trends, and risk by department
- Options to guide, not block, early adopters
🚫 Red flag:
- Zero tolerance design that forces employees underground
4. Lightweight Deployment and Fast Time-to-Value
Security tools shouldn’t require six months of onboarding or deep endpoint installs.
✅ What to look for:
- Browser extension or cloud-native deployment
- Configurable out of the box, with role-based rulesets
- Works across Chrome, Edge, and enterprise SaaS
🚫 Red flag:
- Complex deployment requiring fleet management or OS-level integration
5. Built-In Policy Alignment
A good AI safety tool reinforces your governance framework—not replaces it.
✅ What to look for:
- Ability to reflect your AI use policy in real-time prompts
- Custom rule creation based on your industry or data classification standards
- Integration with existing compliance systems (e.g. GRC tools)
🚫 Red flag:
- Tools that assume one-size-fits-all policies
Bonus: Questions to Ask Vendors
- “How do you differentiate between sensitive and non-sensitive prompts?”
- “How does your tool reinforce, rather than police, user behavior?”
- “Can we test with anonymized live data before committing to full deployment?”
How Tripwire Fits In
Tripwire was built for the realities of AI use at work.
It’s a browser-based layer that monitors, nudges, and informs—without surveillance, without friction, and without assuming people will read a 14-page policy before using ChatGPT.
It’s AI safety—practical, behavioral, and human-aware.
The right AI safety tool isn’t just about preventing worst-case scenarios.
It’s about enabling the best-case ones—safely.
Wanna learn more? Check these out:
- Learn more about our solution through the post: Introducing Tripwire
- Apply for early access and get our exclusive whitepaper